Author: "Schneider, A" - Searchworks@Jio Institute Digital Library Search Results

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793,671 results on '"Schneider, A"'

101. Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain Generalization

Author: Peng, Kunyu, Wen, Di, Saquib, Sarfraz M., Chen, Yufan, Zheng, Junwei, Schneider, David, Yang, Kailun, Wu, Jiamin, Roitberg, Alina, and Stiefelhagen, Rainer
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: Open-Set Domain Generalization (OSDG) is a challenging task requiring models to accurately predict familiar categories while minimizing confidence for unknown categories to effectively reject them in unseen domains. While the OSDG field has seen considerable advancements, the impact of label noise--a common issue in real-world datasets--has been largely overlooked. Label noise can mislead model optimization, thereby exacerbating the challenges of open-set recognition in novel domains. In this study, we take the first step towards addressing Open-Set Domain Generalization under Noisy Labels (OSDG-NL) by constructing dedicated benchmarks derived from widely used OSDG datasets, including PACS and DigitsDG. We evaluate baseline approaches by integrating techniques from both label denoising and OSDG methodologies, highlighting the limitations of existing strategies in handling label noise effectively. To address these limitations, we propose HyProMeta, a novel framework that integrates hyperbolic category prototypes for label noise-aware meta-learning alongside a learnable new-category agnostic prompt designed to enhance generalization to unseen classes. Our extensive experiments demonstrate the superior performance of HyProMeta compared to state-of-the-art methods across the newly established benchmarks. The source code of this work is released at https://github.com/KPeng9510/HyProMeta., Comment: The source code of this work is released at https://github.com/KPeng9510/HyProMeta
Published: 2024

102. Learning to Play Against Unknown Opponents

Author: Arunachaleswaran, Eshwar Ram, Collina, Natalie, and Schneider, Jon
Subjects: Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning
Abstract: We consider the problem of a learning agent who has to repeatedly play a general sum game against a strategic opponent who acts to maximize their own payoff by optimally responding against the learner's algorithm. The learning agent knows their own payoff function, but is uncertain about the payoff of their opponent (knowing only that it is drawn from some distribution $\mathcal{D}$). What learning algorithm should the agent run in order to maximize their own total utility? We demonstrate how to construct an $\varepsilon$-optimal learning algorithm (obtaining average utility within $\varepsilon$ of the optimal utility) for this problem in time polynomial in the size of the input and $1/\varepsilon$ when either the size of the game or the support of $\mathcal{D}$ is constant. When the learning algorithm is further constrained to be a no-regret algorithm, we demonstrate how to efficiently construct an optimal learning algorithm (asymptotically achieving the optimal utility) in polynomial time, independent of any other assumptions. Both results make use of recently developed machinery that converts the analysis of learning algorithms to the study of the class of corresponding geometric objects known as menus.
Published: 2024

103. Euclid: Early Release Observations of diffuse stellar structures and globular clusters as probes of the mass assembly of galaxies in the Dorado group

Author: Urbano, M., Duc, P. -A., Saifollahi, T., Sola, E., Lançon, A., Voggel, K., Annibali, F., Baes, M., Bouy, H., Cantiello, Michele, Carollo, D., Cuillandre, J. -C., Dimauro, P., Erwin, P., Ferguson, A. M. N., Habas, R., Hilker, M., Hunt, L. K., Kluge, M., Larsen, S. S., Liu, Q., Marchal, O., Marleau, F. R., Massari, D., Müller, O., Peletier, R. F., Poulain, M., Rejkuba, M., Schirmer, M., Stone, C., Zöller, R., Altieri, B., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Battaglia, P., Branchini, E., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Degaudenzi, H., De Lucia, G., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Faustini, F., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., George, K., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Moscardini, L., Nakajima, R., Neissner, C., Nichol, R. C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Scaramella, R., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Williams, O. R., Zucca, E., Bolzonella, M., Burigana, C., Mora, A., and Scottez, V.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Deep surveys reveal tidal debris and associated compact stellar systems. Euclid's unique combination of capabilities (spatial resolution, depth, and wide sky coverage) will make it a groundbreaking tool for galactic archaeology in the local Universe, bringing low surface brightness (LSB) science into the era of large-scale astronomical surveys. Euclid's Early Release Observations (ERO) demonstrate this potential with a field of view that includes several galaxies in the Dorado group. In this paper, we aim to derive from this image a mass assembly scenario for its main galaxies: NGC 1549, NGC 1553, and NGC 1546. We detect internal and external diffuse structures, and identify candidate globular clusters (GCs). By analysing the colours and distributions of the diffuse structures and candidate GCs, we can place constraints on the galaxies' mass assembly and merger histories. The results show that feature morphology, surface brightness, colours, and GC density profiles are consistent with galaxies that have undergone different merger scenarios. We classify NGC 1549 as a pure elliptical galaxy that has undergone a major merger. NGC 1553 appears to have recently transitioned from a late-type galaxy to early type, after a series of radial minor to intermediate mergers. NGC 1546 is a rare specimen of galaxy with an undisturbed disk and a prominent diffuse stellar halo, which we infer has been fed by minor mergers and then disturbed by the tidal effect from NGC 1553. Finally, we identify limitations specific to the observing conditions of this ERO, in particular stray light in the visible and persistence in the near-infrared bands. Once these issues are addressed and the extended emission from LSB objects is preserved by the data-processing pipeline, the Euclid Wide Survey will allow studies of the local Universe to be extended to statistical ensembles over a large part of the extragalactic sky., Comment: 25 pages, 20 figures
Published: 2024

104. Width bounds and Steinhaus property for unit groups of continuous rings

Author: Bernard, Josefin and Schneider, Friedrich Martin
Subjects: Mathematics - Group Theory, Mathematics - Rings and Algebras, 22A05, 37B02, 06C20, 16E50
Abstract: We prove an algebraic decomposition theorem for the unit group $\mathrm{GL}(R)$ of an arbitrary non-discrete irreducible, continuous ring $R$ (in von Neumann's sense), which entails that every element of $\mathrm{GL}(R)$ is both a product of $7$ commutators and a product of $16$ involutions. Combining this with further insights into the geometry of involutions, we deduce that $\mathrm{GL}(R)$ has the so-called Steinhaus property with respect to the natural rank topology, thus every homomorphism from $\mathrm{GL}(R)$ to a separable topological group is necessarily continuous. Due to earlier work, this has further dynamical ramifications: for instance, for every action of $\mathrm{GL}(R)$ by homeomorphisms on a non-void metrizable compact space, every element of $\mathrm{GL}(R)$ admits a fixed point in the latter. In particular, our results answer two questions by Carderi and Thom, even in generalized form., Comment: 61 pages, no figures
Published: 2024

105. Sensitivity-Adapted Closed-Loop Optimization for High-Fidelity Controlled-Z Gates in Superconducting Qubits

Author: Glaser, Niklas J., Roy, Federico A., Tsitsilin, Ivan, Koch, Leon, Bruckmoser, Niklas, Schirk, Johannes, Romeiro, João H., Huber, Gerhard B. P., Wallner, Florian, Singh, Malay, Krylov, Gleb, Marx, Achim, Södergren, Lasse, Schneider, Christian M. F., Werninghaus, Max, and Filipp, Stefan
Subjects: Quantum Physics
Abstract: Achieving fast and high-fidelity qubit operations is crucial for unlocking the potential of quantum computers. In particular, reaching low gate errors in two-qubit gates has been a long-standing challenge in the field of superconducting qubits due to their typically long duration relative to coherence times. To realize fast gates, we utilize the hybridization between fixed-frequency superconducting qubits with a strongly interacting coupler mode that is tunable in frequency. To reduce population leakage during required adiabatic passages through avoided level crossings, we employ a sensitivity-adaptive closed-loop optimization method to design complex pulse shapes. We compare the performance of Gaussian-square, Fourier-series, and piecewise-constant-slope (PiCoS) pulse parametrizations and are able to reach 99.9 % controlled-Z gate fidelity using a 64 ns long Fourier-series pulse defined by only seven parameters. These high-fidelity values are achieved by analyzing the optimized pulse shapes to identify and systematically mitigate signal-line distortions in the experiment. To improve the convergence speed of the optimization we implement an adaptive cost function, which continuously maximizes the sensitivity. The demonstrated method can be used for tune-up and recalibration of superconducting quantum processors.
Published: 2024

106. Task-Driven Co-Design of Mobile Manipulators

Author: Schneider, Raphael, Honerkamp, Daniel, Welschehold, Tim, and Valada, Abhinav
Subjects: Computer Science - Robotics
Abstract: Recent interest in mobile manipulation has resulted in a wide range of new robot designs. A large family of these designs focuses on modular platforms that combine existing mobile bases with static manipulator arms. They combine these modules by mounting the arm in a tabletop configuration. However, the operating workspaces and heights for common mobile manipulation tasks, such as opening articulated objects, significantly differ from tabletop manipulation tasks. As a result, these standard arm mounting configurations can result in kinematics with restricted joint ranges and motions. To address these problems, we present the first Concurrent Design approach for mobile manipulators to optimize key arm-mounting parameters. Our approach directly targets task performance across representative household tasks by training a powerful multitask-capable reinforcement learning policy in an inner loop while optimizing over a distribution of design configurations guided by Bayesian Optimization and HyperBand (BOHB) in an outer loop. This results in novel designs that significantly improve performance across both seen and unseen test tasks, and outperform designs generated by heuristic-based performance indices that are cheaper to evaluate but only weakly correlated with the motions of interest. We evaluate the physical feasibility of the resulting designs and show that they are practical and remain modular, affordable, and compatible with existing commercial components. We open-source the approach and generated designs to facilitate further improvements of these platforms.
Published: 2024

107. Search for lepton flavor-violating decay modes $B^0\to K_S^0\tau^\pm\ell^\mp~(\ell=\mu, e)$ with hadronic $B$-tagging at Belle and Belle II

Author: Belle, Collaborations, Belle II, Adachi, I., Adamczyk, K., Aggarwal, L., Ahmed, H., Aihara, H., Akopov, N., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becherer, F., Becker, J., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhardwaj, V., Bhuyan, B., Bianchi, F., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dong, X., Dorigo, M., Dossett, D., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Granderath, S., Graziani, E., Greenwald, D., Gruberová, Z., Guan, Y., Gudkova, K., Haide, I., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Inguglia, G., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobi, D., Jacobs, W. W., Jaffe, D. E., Jang, E. -J., Ji, Q. P., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kaleta, M., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, D., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lai, Y. -T., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Lewis, P. M., Li, C., Li, L. K., Li, Q. M., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Lin, S., Liu, M. H., Liu, Q. Y., Liu, Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Luo, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Mehta, R., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Miyake, H., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakamura, K. R., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Nishida, S., Ogawa, S., Ono, H., Onuki, Y., Otani, F., Pakhlova, G., Paoloni, E., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., Rauls, N., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Robertson, S. H., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Savinov, V., Scavino, B., Schneider, S., Schnell, G., Schwanda, C., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Spataro, S., Spruck, B., Song, W., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Strube, J., Sue, Y., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Wakai, M., Wallner, S., Wang, M. -Z., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Wiechczynski, J., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yelton, J., Yin, J. H., Yoshihara, K., Yuan, C. Z., Yuan, J., Zani, L., Zeng, F., Zhang, B., Zhou, J. S., Zhou, Q. D., Zhu, L., Zhukova, V. I., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We present the first search for the lepton flavor-violating decay modes $B^0 \rightarrow K_S^0 \tau^\pm \ell^\mp~(\ell=\mu, e)$ using the 711 fb$^{-1}$ and 365 fb$^{-1}$ data samples recorded by the Belle and Belle II detectors, respectively. We use a hadronic $B$-tagging technique, and search for the signal decay in the system recoiling against the fully reconstructed $B$ meson. We find no evidence for $B^0 \rightarrow K_S^0 \tau^\pm \ell^\mp$ decays and set 90\% confidence level upper limits on the branching fractions in the range of $[0.8,\,3.6]\times10^{-5}$.
Published: 2024

108. LearnLM: Improving Gemini for Learning

Author: LearnLM Team, Modi, Abhinit, Veerubhotla, Aditya Srikanth, Rysbek, Aliya, Huber, Andrea, Wiltshire, Brett, Veprek, Brian, Gillick, Daniel, Kasenberg, Daniel, Ahmed, Derek, Jurenka, Irina, Cohan, James, She, Jennifer, Wilkowski, Julia, Alarakyia, Kaiz, McKee, Kevin R., Wang, Lisa, Kunesch, Markus, Schaekermann, Mike, Pîslar, Miruna, Joshi, Nikhil, Mahmoudieh, Parsa, Jhun, Paul, Wiltberger, Sara, Mohamed, Shakir, Agarwal, Shashank, Phal, Shubham Milind, Lee, Sun Jae, Strinopoulos, Theofilos, Ko, Wei-Jen, Wang, Amy, Anand, Ankit, Bhoopchand, Avishkar, Wild, Dan, Pandya, Divya, Bar, Filip, Graham, Garth, Winnemoeller, Holger, Nagda, Mahvish, Kolhar, Prateek, Schneider, Renee, Zhu, Shaojian, Chan, Stephanie, Yadlowsky, Steve, Sounderajah, Viknesh, and Assael, Yannis
Subjects: Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: Today's generative AI systems are tuned to present information by default rather than engage users in service of learning as a human tutor would. To address the wide range of potential education use cases for these systems, we reframe the challenge of injecting pedagogical behavior as one of \textit{pedagogical instruction following}, where training and evaluation examples include system-level instructions describing the specific pedagogy attributes present or desired in subsequent model turns. This framing avoids committing our models to any particular definition of pedagogy, and instead allows teachers or developers to specify desired model behavior. It also clears a path to improving Gemini models for learning -- by enabling the addition of our pedagogical data to post-training mixtures -- alongside their rapidly expanding set of capabilities. Both represent important changes from our initial tech report. We show how training with pedagogical instruction following produces a LearnLM model (available on Google AI Studio) that is preferred substantially by expert raters across a diverse set of learning scenarios, with average preference strengths of 31\% over GPT-4o, 11\% over Claude 3.5, and 13\% over the Gemini 1.5 Pro model LearnLM was based on.
Published: 2024

109. Focal Plane of the Arcus Probe X-Ray Spectrograph

Author: Grant, Catherine E., Bautz, Marshall W., Miller, Eric D., Foster, Richard F., LaMarr, Beverly, Malonis, Andrew, Prigozhin, Gregory, Schneider, Benjamin, Leitz, Christopher, and Falcone, Abraham D.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract: The Arcus Probe mission concept provides high-resolution soft X-ray and UV spectroscopy to reveal feedback-driven structure and evolution throughout the universe with an agile response capability ideal for probing the physics of time-dependent phenomena. The X-ray Spectrograph (XRS) utilizes two nearly identical CCD focal planes to detect and record X-ray photons from the dispersed spectra and zero-order of the critical angle transmission gratings. In this paper we describe the Arcus focal plane instrument and the CCDs, including laboratory performance results, which meet observatory requirements., Comment: 11 pages, 7 figures; to be published in JATIS
Published: 2024
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110. Linguistic Features Extracted by GPT-4 Improve Alzheimer's Disease Detection based on Spontaneous Speech

Author: Heitz, Jonathan, Schneider, Gerold, and Langer, Nicolas
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: Alzheimer's Disease (AD) is a significant and growing public health concern. Investigating alterations in speech and language patterns offers a promising path towards cost-effective and non-invasive early detection of AD on a large scale. Large language models (LLMs), such as GPT, have enabled powerful new possibilities for semantic text analysis. In this study, we leverage GPT-4 to extract five semantic features from transcripts of spontaneous patient speech. The features capture known symptoms of AD, but they are difficult to quantify effectively using traditional methods of computational linguistics. We demonstrate the clinical significance of these features and further validate one of them ("Word-Finding Difficulties") against a proxy measure and human raters. When combined with established linguistic features and a Random Forest classifier, the GPT-derived features significantly improve the detection of AD. Our approach proves effective for both manually transcribed and automatically generated transcripts, representing a novel and impactful use of recent advancements in LLMs for AD speech analysis., Comment: Accepted at the 31st International Conference on Computational Linguistics (COLING 2025)
Published: 2024

111. Terrestrial Very-Long-Baseline Atom Interferometry: Summary of the Second Workshop

Author: Abdalla, Adam, Abe, Mahiro, Abend, Sven, Abidi, Mouine, Aidelsburger, Monika, Alibabaei, Ashkan, Allard, Baptiste, Antoniadis, John, Arduini, Gianluigi, Augst, Nadja, Balamatsias, Philippos, Balaz, Antun, Banks, Hannah, Barcklay, Rachel L., Barone, Michele, Barsanti, Michele, Bason, Mark G., Bassi, Angelo, Bayle, Jean-Baptiste, Baynham, Charles F. A., Beaufils, Quentin, Beldjoudi, Slyan, Belic, Aleksandar, Bennetts, Shayne, Bernabeu, Jose, Bertoldi, Andrea, Bigard, Clara, Bigelow, N. P., Bingham, Robert, Blas, Diego, Bobrick, Alexey, Boehringer, Samuel, Bogojevic, Aleksandar, Bongs, Kai, Bortoletto, Daniela, Bouyer, Philippe, Brand, Christian, Buchmueller, Oliver, Buica, Gabriela, Calatroni, Sergio, Calmels, Lo, Canizares, Priscilla, Canuel, Benjamin, Caramete, Ana, Caramete, Laurentiu-Ioan, Carlesso, Matteo, Carlton, John, Carman, Samuel P., Carroll, Andrew, Casariego, Mateo, Chairetis, Minoas, Charmandaris, Vassilis, Chauhan, Upasna, Chen, Jiajun, Luisa, Maria, Chiofalo, Ciampini, Donatella, Cimbri, Alessia, Clad, Pierre, Coleman, Jonathon, Constantin, Florin Lucian, Contaldi, Carlo R., Corgier, Robin, Dash, Bineet, Davies, G. J., de Rham, Claudia, De Roeck, Albert, Derr, Daniel, Dey, Soumyodeep, Di Pumpo, Fabio, Djordjevic, Goran S., Doebrich, Babette, Dornan, Peter, Doser, Michael, Drougakis, Giannis, Dunningham, Jacob, Duspayev, Alisher, Easo, Sajan, Eby, Joshua, Efremov, Maxim, Elertas, Gedminas, Ellis, John, Entin, Nicholas, Fairhurst, Stephen, Fani, Mattia, Fassi, Farida, Fayet, Pierre, Felea, Daniel, Feng, Jie, Flack, Robert, Foot, Chris, Freegarde, Tim, Fuchs, Elina, Gaaloul, Naceur, Gao, Dongfeng, Gardner, Susan, Garraway, Barry M., Alzar, Carlos L. Garrido, Gauguet, Alexandre, Giese, Enno, Gill, Patrick, Giudice, Gian F., Glasbrenner, Eric P., Glick, Jonah, Graham, Peter W., Granados, Eduardo, Griffin, Paul F., Gue, Jordan, Guellati-Khelifa, Saida, Gupta, Subhadeep, Gupta, Vishu, Hackermueller, Lucia, Haehnelt, Martin, Hakulinen, Timo, Hammerer, Klemens, Hanimeli, Ekim T., Harte, Tiffany, Hartmann, Sabrina, Hawkins, Leonie, Hees, Aurelien, Herbst, Alexander, Hird, Thomas M., Hobson, Richard, Hogan, Jason, Holst, Bodil, Holynski, Michael, Hosten, Onur, Hsu, Chung Chuan, Huang, Wayne Cheng-Wei, Hughes, Kenneth M., Hussain, Kamran, Huetsi, Gert, Iovino, Antonio, Isfan, Maria-Catalina, Janson, Gregor, Jeglic, Peter, Jetzer, Philippe, Jiang, Yijun, Juzeliunas, Gediminas, Kaenders, Wilhelm, Kalliokoski, Matti, Kehagias, Alex, Kilian, Eva, Klempt, Carsten, Knight, Peter, Koley, Soumen, Konrad, Bernd, Kovachy, Tim, Krutzik, Markus, Kumar, Mukesh, Kumar, Pradeep, Labiad, Hamza, Lan, Shau-Yu, Landragin, Arnaud, Landsberg, Greg, Langlois, Mehdi, Lanigan, Bryony, Poncin-Lafitte, Christophe Le, Lellouch, Samuel, Leone, Bruno, Lewicki, Marek, Lien, Yu-Hung, Lombriser, Lucas, Asamar, Elias Lopez, Lopez-Gonzalez, J. Luis, Lowe, Adam, Lu, Chen, Luciano, Giuseppe Gaetano, Lundblad, Nathan, Monjaraz, Cristian de J. Lpez, Mackoit-Sinkeviien, Maena, Maggiore, Michele, Majumdar, Anirban, Makris, Konstantinos, Maleknejad, Azadeh, Marchant, Anna L., Mariotti, Agnese, Markou, Christos, Matthews, Barnaby, Mazumdar, Anupam, McCabe, Christopher, Meister, Matthias, Mentasti, Giorgio, Menu, Jonathan, Messineo, Giuseppe, Meyer-Hoppe, Bernd, Micalizio, Salvatore, Migliaccio, Federica, Millington, Peter, Milosevic, Milan, Mishra, Abhay, Mitchell, Jeremiah, Morley, Gavin W., Mouelle, Noam, Mueller, Juergen, Newbold, David, Ni, Wei-Tou, Niehof, Christian, Noller, Johannes, Odzak, Senad, Oi, Daniel K. L., Oikonomou, Andreas, Omar, Yasser, Overstreet, Chris, Pahl, Julia, Paling, Sean, Pan, Zhongyin, Pappas, George, Pareek, Vinay, Pasatembou, Elizabeth, Paternostro, Mauro, Pathak, Vishal K., Pelucchi, Emanuele, Santos, Franck Pereira dos, Peters, Achim, Pichery, Annie, Pikovski, Igor, Pilaftsis, Apostolos, Pislan, Florentina-Crenguta, Plunkett, Robert, Poggiani, Rosa, Prevedelli, Marco, Veettil, Vishnupriya Puthiya, Rafelski, Johann, Raidal, Juhan, Raidal, Martti, Rasel, Ernst Maria, Renaux-Petel, Sebastien, Richaud, Andrea, Rivero-Antunez, Pedro, Rodzinka, Tangui, Roura, Albert, Rudolph, Jan, Sabulsky, Dylan, Safronova, Marianna S., Sakellariadou, Mairi, Salvi, Leonardo, Sameed, Muhammed, Sarkar, Sumit, Schach, Patrik, Schaeffer, Stefan Alaric, Schelfhout, Jesse, Schilling, Manuel, Schkolnik, Vladimir, Schleich, Wolfgang P., Schlippert, Dennis, Schneider, Ulrich, Schreck, Florian, Schwartzman, Ariel, Schwersenz, Nico, Sergijenko, Olga, Sfar, Haifa Rejeb, Shao, Lijing, Shipsey, Ian, Shu, Jing, Singh, Yeshpal, Sopuerta, Carlos F., Sorba, Marianna, Sorrentino, Fiodor, Spallicci, Alessandro D. A. M, Stefanescu, Petruta, Stergioulas, Nikolaos, Stoerk, Daniel, Stroehle, Jannik, Sunilkumar, Hrudya Thaivalappil, Tam, Zoie, Tandon, Dhruv, Tang, Yijun, Tell, Dorothee, Tempere, Jacques, Temples, Dylan J., Thampy, Rohit P, Tietje, Ingmari C., Tino, Guglielmo M., Tinsley, Jonathan N., Mircea, Ovidiu Tintareanu, Tkalec, Kimberly, Tolley, Andrew J., Tornatore, Vincenza, Torres-Orjuela, Alejandro, Treutlein, Philipp, Trombettoni, Andrea, Ufrecht, Christian, Urrutia, Juan, Valenzuela, Tristan, Valerio, Linda R., van der Grinten, Maurits, Vaskonen, Ville, Vazquez-Aceves, Veronica, Veermae, Hardi, Vetrano, Flavio, Vitanov, Nikolay V., von Klitzing, Wolf, Wald, Sebastian, Walker, Thomas, Walser, Reinhold, Wang, Jin, Wang, Yan, Weidner, C. A., Wenzlawski, Andr, Werner, Michael, Woerner, Lisa, Yahia, Mohamed E., Yazgan, Efe, Cruzeiro, Emmanuel Zambrini, Zarei, M., Zhan, Mingsheng, Zhang, Shengnan, Zhou, Lin, and Zupanic, Erik
Subjects: High Energy Physics - Experiment, Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology, Physics - Atomic Physics
Abstract: This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/
Published: 2024

112. Rydberg states and new resonant states of the imidogen molecule NH: pathways for nitrogen release

Author: Ghosh, Raju, Choudhuryt, Binayak Samaddar, Mezei, Janos Zsolt, Schneider, Ioan F., Pop, Nicolina, and Chakrabarti, Kalyan
Subjects: Physics - Atomic Physics, Physics - Plasma Physics, Quantum Physics
Abstract: Neutral resonant states of molecules play a very important role in the dissociation dynamics and other electronic processes that occur via intermediate capture into these states. With the goal of identifying resonant states, and their corresponding widths, of the imidogen molecule NH as a function of internuclear distance, we have performed detailed R-matrix calculations on the e + NH+ system. In a previous work, we had identified bound states of NH and Feshbach resonances in the e + NH+ system at a single geometry, namely the NH+ equilibrium Re = 2.0205 a0 . Here we present a much more detailed work by repeating the calculation on over 60 internuclear distances to obtain the corresponding potential energy curves. The bound states for nine symmetries have been detailed many of which, particularly the singlet states, were never studied before. Several resonant states of different symmetries, which were unknown until now, have been systematically identified and their widths calculated in the present work, which proved much more challenging due to presence of many avoided crossings. It is hoped that the bound and the new resonant states obtained here will open up other molecular dynamics studies, since for several dissociative processes, although experimental data existed for more than a decade, these are still uncorroborated due to absence of molecular data, and hence subsequent theoretical calculations., Comment: 11 pages, 10 figures, 2 tables
Published: 2024

113. Measurement of the branching fraction and $\it CP$-violating asymmetry of the decay $B^{0} \rightarrow \pi^{0} \pi^{0}$ using $387$ million bottom-antibottom meson pairs in Belle II data

Author: Belle II Collaboration, Adachi, I., Aggarwal, L., Ahmed, H., Aihara, H., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becherer, F., Becker, J., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhardwaj, V., Bhuyan, B., Bianchi, F., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dong, X., Dorigo, M., Dossett, D., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Epifanov, D., Eppelt, J., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Frey, A., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Granderath, S., Graziani, E., Greenwald, D., Gruberová, Z., Guan, Y., Gudkova, K., Haide, I., Halder, S., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jackson, P., Jacobi, D., Jacobs, W. W., Jang, E. -J., Ji, Q. P., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kalita, D., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kim, Y. J., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, D., Kumar, M., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lai, Y. -T., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Lautenbach, K., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Levit, D., Lewis, P. M., Li, C., Li, L. K., Li, Q. M., Li, W. Z., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Lin, S., Liu, M. H., Liu, Q. Y., Liu, Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Maity, S., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matsuda, T., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Mehta, R., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Miyake, H., Mizuk, R., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Niebuhr, C., Nishida, S., Ogawa, S., Ono, H., Onuki, Y., Otani, F., Pakhlov, P., Pakhlova, G., Paoloni, E., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., RajG, V., Rauls, N., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Sato, Y., Savinov, V., Scavino, B., Schmitt, C., Schneider, S., Schnepf, M., Schwanda, C., Schwartz, A. J., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shen, C. P., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Song, W., Spataro, S., Spruck, B., Starič, M., Stavroulakis, P., Stroili, R., Strube, J., Sue, Y., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Tonelli, D., Torassa, E., Trabelsi, K., Tsaklidis, I., Uchida, M., Ueda, I., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Vossen, A., Wakai, M., Wallner, S., Wang, E., Wang, M. -Z., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yang, S. B., Yelton, J., Yin, J. H., Yoshihara, K., Yuan, J., Zani, L., Zeng, F., Zhang, B., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhukova, V. I., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We measure the branching fraction and $\it CP$-violating flavor-dependent rate asymmetry of $B^{0} \to \pi^{0} \pi^{0}$ decays reconstructed using the Belle II detector in an electron-positron collision sample containing $387 \times 10^{6}$ $B\overline{B}$ pairs. Using an optimized event selection, we find $126\pm 20$ signal decays in a fit to background-discriminating and flavor-sensitive distributions. The resulting branching fraction is $(1.25 \pm 0.23)\times 10^{-6}$ and the $\it CP$-violating asymmetry is $0.03 \pm 0.30$.
Published: 2024

114. Episodic super-Eddington accretion as a clue to Overmassive Black Holes in the early Universe

Author: Trinca, Alessandro, Valiante, Rosa, Schneider, Raffaella, Juodžbalis, Ignas, Maiolino, Roberto, Graziani, Luca, Lupi, Alessandro, Natarajan, Priyamvada, Volonteri, Marta, and Zana, Tommaso
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Early JWST observations are providing growing evidence for a ubiquitous population of accreting supermassive black holes (BHs) at high redshift, many of which appear overmassive compared to the empirically-derived local scaling relation between black hole mass and host galaxy stellar mass. In this study, we leverage predictions from the semi-analytical Cosmic Archaeology Tool (CAT) to reconstruct the evolutionary pathways for this overmassive BH population, investigating how they assemble over cosmic time and interact with their host galaxies. We find that the large $M_{\rm BH}-M_{\rm star}$ ratios can be explained if light and heavy BH seeds grow by short, repeated episodes of super-Eddington accretion, triggered by major galaxy mergers. On average, we find that BH-galaxy co-evolution starts in earnest only at $z < 8$, when $\simeq 30\%$ of the final galaxy stellar mass has formed outside the massive black hole host. Our model suggests that super-Eddington bursts of accretion last between $0.5-3$ Myr, resulting in a duty cycle of $1-4 \%$ for the target BH sample. The boost in luminosity of BHs undergoing super-Eddington accretion helps explaining the luminosity function of Active Galactic Nuclei observed by JWST. At the same time, a large population of these overmassive BHs are predicted to be inactive, with Eddington ratio $\lambda_{\rm Edd} < 0.05$, in agreement with recent observations., Comment: 15 pages, 6 figures. Submitted to A&A
Published: 2024

115. Measurement of $CP$ asymmetry in $B_s^0 \to D_s^{\mp} K^{\pm}$ decays

Author: LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Bellee, V., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Godinez, J. Castro, Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collins, P., Colombo, T., Colonna, M., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Davidson, A., Davies, J. E., Davis, A., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Epple, E., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Führing, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. 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W., Wang, Y., Wang, Y. W., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, C., Whitehead, M., Whiter, E., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. R. J., Williams, R., Williams, Z., Wilson, F. F., Wislicki, W., Witek, M., Witola, L., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, Y., Wu, Z., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xu, A., Xu, J., Xu, L., Xu, M., Xu, Z., Yang, D., Yang, K., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yin, X., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenesini, F., Zeng, C., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhao, Y., Zharkova, A., Zhelezov, A., Zheng, S. Z., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.
Subjects: High Energy Physics - Experiment
Abstract: A measurement of the $CP$-violating parameters in $B_s^0 \to D_s^{\mp} K^{\pm}$ decays is reported, based on the analysis of proton-proton collision data collected by the LHCb experiment corresponding to an integrated luminosity of $6\,\mathrm{fb}^{-1}$ at a centre-of-mass energy of $13 \,\mathrm{TeV}$. The measured parameters are $C_f = 0.791 \pm 0.061 \pm 0.022$, $A_f^{\Delta\Gamma} = -0.051 \pm 0.134 \pm 0.058$, $A_{\overline{f}}^{\Delta\Gamma} = -0.303 \pm 0.125 \pm 0.055$, $S_f = -0.571 \pm 0.084 \pm 0.023$ and $S_{\overline{f}} = -0.503 \pm 0.084 \pm 0.025$, where the first uncertainty is statistical and the second systematic. Together with the value of the Bs mixing phase $-2\beta_s$, these parameters are used to obtain a measurement of the CKM angle $\gamma$ equal to $ (74\pm12)^\circ$ modulo $180^{\circ}$, where the uncertainty contains both statistical and systematic contributions. This result is combined with the previous LHCb measurement in this channel using $3\,\mathrm{fb}^{-1}$ resulting in a determination of $\gamma= (81^{+12}_{-11})^\circ$., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3575/ (LHCb public pages)
Published: 2024

116. Measurement of $CP$ asymmetries in $\Lambda_b^0\to ph^{-}$ decays

Author: LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bottalico, E., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Brandenburg, J. D., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonincontri, L., Marcos, M. Burgos, Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collaviti, S., Collins, P., Colombo, T., Colonna, M., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Darze, G., Davidson, A., Davies, J. E., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. 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P., Moron, J., Morren, W., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Niu, Q., Nogarolli, P., Nogga, P., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Okhrimenko, O., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Osthues, D., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Paciolla, F., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Pan, X., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. 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Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Alvarez, A. Rodriguez, Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogachev, A., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Vidal, A. Romero, Romolini, G., Ronchetti, F., Rong, T., Rotondo, M., Roy, S. R., Rudolph, M. S., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Sborzacchi, F., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schiller, M., Schindler, H., Schmelling, M., Schmidt, B., Schmitt, S., Schmitz, H., Schneider, O., Schopper, A., Schulte, N., Schulte, S., Schune, M. H., Schwemmer, R., Schwering, G., Sciascia, B., Sciuccati, A., Segal, I., Sellam, S., Semennikov, A., Senger, T., Soares, M. Senghi, Sergi, A., Serra, N., Sestini, L., Seuthe, A., Shang, Y., Shangase, D. M., Shapkin, M., Sharma, R. S., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Shevchenko, V., Shi, B., Shi, Q., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Coutinho, R. Silva, Simi, G., Simone, S., Skidmore, N., Skwarnicki, T., Slater, M. W., Smallwood, J. C., Smith, E., Smith, K., Smith, M., Snoch, A., Lavra, L. Soares, Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Sommerfeld, N. S., Song, R., Song, Y., Song, Y. S., De Almeida, F. L. Souza, De Paula, B. Souza, Norella, E. Spadaro, Spedicato, E., Speer, J. 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J., Veltri, M., Venkateswaran, A., Verdoglia, M., Vesterinen, M., Benet, D. Vico, Villalba, P. Vidrier, Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, H., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Y. W., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, C., Whitehead, M., Whiter, E., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. J., Williams, M. R. J., Williams, R., Williams, Z., Wilson, F. F., Winn, M., Wislicki, W., Witek, M., Witola, L., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, X., Wu, Y., Wu, Z., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xing, T. X., Xu, A., Xu, L., Xu, M., Xu, Z., Yang, K., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yin, X., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenesini, F., Zeng, C., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhang, Z., Zhao, Y., Zhelezov, A., Zheng, S. Z., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.
Subjects: High Energy Physics - Experiment
Abstract: A search for $CP$ violation in $\Lambda_b^0\rightarrow pK^-$ and $\Lambda_b^0\rightarrow p\pi^-$ decays is presented using the full Run 1 and Run 2 data samples of $pp$ collisions collected with the LHCb detector, corresponding to an integrated luminosity of 9 $\mathrm{fb}^{-1}$ at center-of-mass energies of 7, 8, and 13 TeV. For the Run 2 data sample, the $CP$-violating asymmetries are measured to be $A_{CP}^{pK^-} = (-1.4 \pm 0.7 \pm 0.4)\%$ and $A_{CP}^{p\pi^-} = (0.4 \pm 0.9 \pm 0.4)\%$, where the first uncertainty is statistical and the second is systematic. Following significant improvements in the evaluation of systematic uncertainties compared to the previous LHCb measurement, the Run 1 dataset is reanalyzed to update the corresponding results. When combining the Run 2 and updated Run 1 measurements, the final results are found to be $A_{CP}^{pK^-} = (-1.1 \pm 0.7 \pm 0.4)\%$ and $A_{CP}^{p\pi^-} = (0.2 \pm 0.8 \pm 0.4)\%$, constituting the most precise measurements of these asymmetries to date., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3533/ (LHCb public pages)
Published: 2024

117. Ultrafast demagnetization in ferromagnetic materials: Origins and progress

Author: Chen, Xiaowen, Adam, Roman, Bürgler, Daniel E., Wang, Fangzhou, Lu, Zhenyan, Pan, Lining, Heidtfeld, Sarah, Greb, Christian, Liu, Meihong, Liu, Qingfang, Wang, Jianbo, Schneider, Claus M., and Cao, Derang
Subjects: Condensed Matter - Materials Science, Condensed Matter - Other Condensed Matter, High Energy Physics - Experiment, Physics - Applied Physics, Physics - Optics
Abstract: Since the discovery of ultrafast demagnetization in Ni thin films in 1996, laser-induced ultrafast spin dynamics have become a prominent research topic in the field of magnetism and spintronics. This development offers new possibilities for the advancement of spintronics and magnetic storage technology. The subject has drawn a substantial number of researchers, leading to a series of research endeavors. Various models have been proposed to elucidate the physical processes underlying laser-induced ultrafast spin dynamics in ferromagnetic materials. However, the potential origins of these processes across different material systems and the true contributions of these different origins remain challenging in the realm of ultrafast spin dynamics. This predicament also hinders the development of spintronic terahertz emitters. In this review, we initially introduce the different experimental methods used in laser-induced ultrafast spin dynamics. We then systematically explore the magnetization precession process and present seven models of ultrafast demagnetization in ferromagnetic materials. Subsequently, we discuss the physical processes and research status of four ultrafast demagnetization origins (including spin-flipping, spin transport, non-thermal electronic distribution, and laser-induced lattice strain). Since attosecond laser technique and antiferromagnetic materials exhibit promising applications in ultrahigh-frequency spintronics, we acknowledge the emerging studies used by attosecond pules and studies on ultrafast spin dynamics in antiferromagnets, noting the significant challenges that need to be addressed in these burgeoning field.
Published: 2024
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118. Intermediate Relation Size Bounds for Select-Project-Join Query Plans: Asymptotically Tight Characterizations

Author: Chen, Hubie and Schneider, Markus
Subjects: Computer Science - Databases
Abstract: We study the problem of statically optimizing select-project-join (SPJ) plans where unary key constraints are allowed. A natural measure of a plan, which we call the output degree and which has been studied previously, is the minimum degree of a polynomial bounding the plan's output relation, as a function of the input database's maximum relation size. This measure is, by definition, invariant under passing from a plan to another plan that is semantically equivalent to the first. In this article, we consider a plan measure which we call the intermediate degree; this measure is defined to be the minimum degree bounding the size of all intermediate relations computed during a plan's execution -- again, as a function of the input database's maximum relation size. We present an algorithm that, given an SPJ plan $q$ and a set $\Sigma$ of unary keys, computes an SPJ plan $q'$ that is semantically equivalent to $q$ (over databases satisfying $\Sigma$) and that has the minimum intermediate degree over all such semantically equivalent plans. For the types of plans considered, we thus obtain a complete and effective understanding of intermediate degree.
Published: 2024

119. Microscale deformation of intermetallic-Mg interface under shear loading

Author: Kanjilal, Anwesha, Aliramaji, Shamsa, Neuß, Deborah, Hans, Marcus, Schneider, Jochen M., Best, James P., and Dehm, Gerhard
Subjects: Condensed Matter - Materials Science
Abstract: While intermetallic (IM)-metal interfaces in metallic alloys are critical for tuning mechanical properties, they can also act as failure sites, underscoring the importance of determining their strength. This study reports on a novel microshear geometry, and demonstrates its applicability for testing the strength and deformation behavior of IM-metal interfaces in Mg-Al-Ca alloys, a key material for light weight automotive applications. The shear tests are applied to a model bi-layered system grown by magnetron sputtering, comprising of a CaMg2 film deposited onto a Mg layer. A parametric study was performed using finite element modeling to optimize the specimen dimensions. Subsequently, in situ microshear tests conducted inside a scanning electron microscope revealed an interface shear strength of ~136 MPa, and provided insights into the stages of deformation progression. Post mortem examination of the sheared interface revealed an irregular surface indicating ductile deformation at room temperature.
Published: 2024

120. Demonstrating Data-to-Knowledge Pipelines for Connecting Production Sites in the World Wide Lab

Author: Gorißen, Leon, Schneider, Jan-Niklas, Behery, Mohamed, Brauner, Philipp, Lennartz, Moritz, Kötter, David, Kaster, Thomas, Petrovic, Oliver, Hinke, Christian, Gries, Thomas, Lakemeyer, Gerhard, Ziefle, Martina, Brecher, Christian, and Häfner, Constantin
Subjects: Computer Science - Robotics, Computer Science - Machine Learning
Abstract: The digital transformation of production requires new methods of data integration and storage, as well as decision making and support systems that work vertically and horizontally throughout the development, production, and use cycle. In this paper, we propose Data-to-Knowledge (and Knowledge-to-Data) pipelines for production as a universal concept building on a network of Digital Shadows (a concept augmenting Digital Twins). We show a proof of concept that builds on and bridges existing infrastructure to 1) capture and semantically annotates trajectory data from multiple similar but independent robots in different organisations and use cases in a data lakehouse and 2) an independent process that dynamically queries matching data for training an inverse dynamic foundation model for robotic control. The article discusses the challenges and benefits of this approach and how Data-to-Knowledge pipelines contribute efficiency gains and industrial scalability in a World Wide Lab as a research outlook., Comment: 15 pages, 6 figures, submitted to CAiSE 2025
Published: 2024

121. Euclid: Field-level inference of primordial non-Gaussianity and cosmic initial conditions

Author: Andrews, A., Jasche, J., Lavaux, G., Leclercq, F., Finelli, F., Akrami, Y., Ballardini, M., Karagiannis, D., Valiviita, J., Bartolo, N., Cañas-Herrera, G., Casas, S., Granett, B. R., Pace, F., Paoletti, D., Porqueres, N., Sakr, Z., Sapone, D., Aghanim, N., Amara, A., Andreon, S., Baccigalupi, C., Baldi, M., Bardelli, S., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Faustini, F., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Hornstrup, A., Hudelot, P., Ilić, S., Jahnke, K., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Saglia, R., Sánchez, A. G., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Sefusatti, E., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Burigana, C., Scottez, V., Mancini, A. Spurio, and Viel, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: A primary target of the \Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of primordial non-Gaussianity would rule out the simplest models of cosmic inflation and transform our understanding of the origin of the Universe. This paper forecasts how well field-level inference of galaxy redshift surveys can constrain the amplitude of local primordial non-Gaussianity ($f_{NL}$), within a Bayesian hierarchical framework, in the upcoming \Euclid data. We design and simulate mock data sets and perform Markov chain Monte Carlo analyses using a full-field forward modelling approach. By including the formation history of the cosmic matter field in the analysis, the method takes into account all available probes of primordial non-Gaussianity, and goes beyond statistical summary estimators of $f_{NL}$. Probes include, for example, two-point and higher-order statistics, peculiar velocity fields, and scale-dependent galaxy biases. Furthermore, the method simultaneously handles systematic survey effects, such as selection effects, survey geometries, and galaxy biases. The forecast shows that the method can reach precision levels of up to $\sigma (f_{NL}) = 2.3$ (68.3\% CI, and at the grid resolution $\Delta L = 62.5\,h^{-1}$Mpc) with \Euclid data. We also provide data products, including realistic $N$-body simulations with nonzero values of $f_{NL}$ and maps of adiabatic curvature fluctuations. The results underscore the feasibility and advantages of field-level inference to constrain $f_{NL}$ in galaxy redshift surveys. Our approach consistently captures all the information available in the large-scale structure to constrain $f_{NL}$, and resolves the degeneracy between early-universe physics and late-time gravitational effects, while mitigating the impact of systematic and observational effects., Comment: 31 pages and 26 figures, 3 tables. Comments are welcome!
Published: 2024

122. Test of lepton flavour universality with $B^+ \to K^+\pi^+\pi^-\ell^+\ell^-$ decays

Author: LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bottalico, E., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Brandenburg, J. D., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonincontri, L., Marcos, M. Burgos, Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collaviti, S., Collins, P., Colombo, T., Colonna, M., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Darze, G., Davidson, A., Davies, J. E., Davis, A., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. 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R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. 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G., Spiridenkov, E., Spradlin, P., Sriskaran, V., Stagni, F., Stahl, M., Stahl, S., Stanislaus, S., Stefaniak, M., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sundfeld, D., Sutcliffe, W., Swallow, P. N., Swientek, K., Swystun, F., Szabelski, A., Szumlak, T., Tan, Y., Tang, Y., Tat, M. D., Terentev, A., Terzuoli, F., Teubert, F., Thomas, E., Thompson, D. J. D., Tilquin, H., Tisserand, V., T'Jampens, S., Tobin, M., Tomassetti, L., Tonani, G., Tong, X., Tork, T., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Urbach, B., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Cadenas, V. Valcarce, Valenti, G., Canudas, N. Valls, van Eldik, J., Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Laak, R., van Veghel, M., Vasquez, G., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Velthuis, J. J., Veltri, M., Venkateswaran, A., Verdoglia, M., Vesterinen, M., Benet, D. Vico, Villalba, P. Vidrier, Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, H., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Y. W., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, C., Whitehead, M., Whiter, E., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. J., Williams, M. R. J., Williams, R., Williams, Z., Wilson, F. F., Winn, M., Wislicki, W., Witek, M., Witola, L., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, X., Wu, Y., Wu, Z., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xing, T. X., Xu, A., Xu, L., Xu, M., Xu, Z., Yang, K., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yin, X., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenesini, F., Zeng, C., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhang, Z., Zhao, Y., Zhelezov, A., Zheng, S. Z., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.
Subjects: High Energy Physics - Experiment
Abstract: The first test of lepton flavour universality between muons and electrons using $B^+ \to K^+\pi^+\pi^-\ell^+\ell^-$ ($\ell=e,\mu$) decays is presented. The measurement is performed with data from proton-proton collisions collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to an integrated luminosity of $9\mathrm{fb}^{-1}$. The ratio of branching fractions between $B^+ \to K^+\pi^+\pi^-e^+e^-$ and $B^+ \to K^+\pi^+\pi^-\mu^+\mu^-$decays is measured in the dilepton invariant-mass-squared range $1.1 < q^2 < 7.0~\mathrm{GeV}^2/c^4$ and is found to be $R_{K\pi\pi}^{-1} = 1.31^{+0.18}_{-0.17} \;(\mathrm{stat})\;^{+0.12}_{-0.09} \;(\mathrm{syst})$, in agreement with the Standard Model prediction. The first observation of the $B^+ \to K^+\pi^+\pi^-e^+e^-$ decay is also reported., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/1606/ (LHCb public pages)
Published: 2024

123. Multilingual and Explainable Text Detoxification with Parallel Corpora

Author: Dementieva, Daryna, Babakov, Nikolay, Ronen, Amit, Ayele, Abinew Ali, Rizwan, Naquee, Schneider, Florian, Wang, Xintong, Yimam, Seid Muhie, Moskovskiy, Daniil, Stakovskii, Elisei, Kaufman, Eran, Elnagar, Ashraf, Mukherjee, Animesh, and Panchenko, Alexander
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital abusive speech remains a significant issue. One potential approach to address this challenge is automatic text detoxification, a text style transfer (TST) approach that transforms toxic language into a more neutral or non-toxic form. To date, the availability of parallel corpora for the text detoxification task (Logachevavet al., 2022; Atwell et al., 2022; Dementievavet al., 2024a) has proven to be crucial for state-of-the-art approaches. With this work, we extend parallel text detoxification corpus to new languages -- German, Chinese, Arabic, Hindi, and Amharic -- testing in the extensive multilingual setup TST baselines. Next, we conduct the first of its kind an automated, explainable analysis of the descriptive features of both toxic and non-toxic sentences, diving deeply into the nuances, similarities, and differences of toxicity and detoxification across 9 languages. Finally, based on the obtained insights, we experiment with a novel text detoxification method inspired by the Chain-of-Thoughts reasoning approach, enhancing the prompting process through clustering on relevant descriptive attributes., Comment: COLING 2025, main conference, long
Published: 2024

124. Predicting Internet Connectivity in Schools: A Feasibility Study Leveraging Multi-modal Data and Location Encoders in Low-Resource Settings

Author: Doerksen, Kelsey, Fibaek, Casper, Schneider, Rochelle, Kim, Do-Hyung, and Tingzon, Isabelle
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Social and Information Networks
Abstract: Internet connectivity in schools is critical to provide students with the digital literary skills necessary to compete in modern economies. In order for governments to effectively implement digital infrastructure development in schools, accurate internet connectivity information is required. However, traditional survey-based methods can exceed the financial and capacity limits of governments. Open-source Earth Observation (EO) datasets have unlocked our ability to observe and understand socio-economic conditions on Earth from space, and in combination with Machine Learning (ML), can provide the tools to circumvent costly ground-based survey methods to support infrastructure development. In this paper, we present our work on school internet connectivity prediction using EO and ML. We detail the creation of our multi-modal, freely-available satellite imagery and survey information dataset, leverage the latest geographically-aware location encoders, and introduce the first results of using the new European Space Agency phi-lab geographically-aware foundational model to predict internet connectivity in Botswana and Rwanda. We find that ML with EO and ground-based auxiliary data yields the best performance in both countries, for accuracy, F1 score, and False Positive rates, and highlight the challenges of internet connectivity prediction from space with a case study in Kigali, Rwanda. Our work showcases a practical approach to support data-driven digital infrastructure development in low-resource settings, leveraging freely available information, and provide cleaned and labelled datasets for future studies to the community through a unique collaboration between UNICEF and the European Space Agency phi-lab.
Published: 2024

125. Global electromagnetic gyrokinetic simulations of internal transport barriers in reversed-shear tokamaks

Author: Di Giannatale, Giovanni, Volčokas, Arnas, Ball, Justin, Bottino, Alberto, Brunner, Stephan, Griveaux, Philippe, Murugappan, Moahan, Hayward-Schneider, Thomas, and Villard, Laurent
Subjects: Physics - Plasma Physics
Abstract: This work aims at improving our understanding of the conditions enabling the development of an Internal transport barriers (ITB), using a more comprehensive physical model, including low-$\beta$ electromagnetic flux-driven simulations. Our key findings are that electron dynamics is crucial for ITB formation even in an ITG scenario and that having $q_{\text{min}}$ close to a lowest order rational value (2 in our simulations) to allow for eddies self-interaction is a necessary ingredient. Electron dynamics has two critical effects. First, it leads to a structure formation characterized by strong zonal flows shearing rate, reduction of turbulence and profile corrugation. Second, it leads to zonal current sheets that result in a broadening of the minimum-q region, qualitatively consistent with the flux-tube simulations of Vol\v{c}okas et al. [1]. Flux-driven simulations performed with $q_{\text{min}}=2$ reveal the development of the transport barrier in the ion channel, forming at inner and outer radial positions with respect to the $q_{\text{min}}$ position. The ITB formation in flux-driven setup is not recovered if $q_{\text{min}} = 2.03$. Additionally, a simulation at higher $\rho^*$ indicates that the extent of the flattened region of the q-profile due to turbulent self-interaction does not change proportionally to $\rho^*$ or to $\rho_i$, but somewhere in between. On the other hand, the input power required to achieve similar on-axis temperatures appears to exhibit almost GyroBohm scaling (for the two considered $\rho^*$ values). Furthermore, considering an initial q-profile with $q_{\text{min}} = 2.01$, flux-driven simulations show that partial self-interaction can evolve to complete self-interaction. This occurs due to turbulent-driven zonal currents that lower and flatten the q-profile down to $q_{\text{min}} = 2.0$, in line with what is reported in Vol\v{c}okas et al.[1].
Published: 2024

126. Search for $D^0$ meson decays to $\pi^+ \pi^- e^+ e^-$ and $K^+ K^- e^+ e^-$ final states

Author: LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Balboni, A., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. A., Belin, S., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bonacci, R. B., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bottalico, E., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Brandenburg, J. D., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonincontri, L., Marcos, M. Burgos, Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collaviti, S., Collins, P., Colombo, T., Colonna, M., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Darze, G., Davidson, A., Davies, J. E., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Führing, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. Gallas, Galli, D., Gambetta, S., Gandelman, M., Gandini, P., Ganie, B., Gao, H., Gao, R., Gao, T. Q., Gao, Y., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Gardner, P., Garg, K. G., Garrido, L., Gaspar, C., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghizzo, S., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Girardey, L., Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Fernandez, S. Gomez, Gomulka, W., Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., Govorkova, E., Grabowski, J. P., Cardoso, L. A. Granado, Graugés, E., Graverini, E., Grazette, L., Graziani, G., Grecu, A. T., Greeven, L. M., Grieser, N. A., Grillo, L., Gromov, S., Gu, C., Guarise, M., Guerry, L., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Hallett, G., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Harris, T. H., Hartmann, M., Hashmi, S., He, J., Hemmer, F., Henderson, C., Henderson, R. D. L., Hennequin, A. M., Hennessy, K., Henry, L., Herd, J., Gascon, P. Herrero, Heuel, J., Hicheur, A., Mendizabal, G. Hijano, Horswill, J., Hou, R., Hou, Y., Howarth, N., Hu, J., Hu, W., Hu, X., Huang, W., Hulsbergen, W., Hunter, R. J., Hushchyn, M., Hutchcroft, D., Idzik, M., Ilin, D., Ilten, P., Inglessi, A., Iniukhin, A., Ishteev, A., Ivshin, K., Jacobsson, R., Jage, H., Elles, S. J. Jaimes, Jakobsen, S., Jans, E., Jashal, B. K., Jawahery, A., Jevtic, V., Jiang, E., Jiang, X., Jiang, Y., Jiang, Y. J., John, M., Rajan, A. John Rubesh, Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lee, H., Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Lesser, E. D., Leverington, B., Li, A., Li, C., Li, H., Li, K., Li, L., Li, M., Li, P., Li, P. -R., Li, Q., Li, S., Li, T., Li, Y., Lian, Z., Liang, X., Libralon, S., Lin, C., Lin, T., Lindner, R., Linton, H., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, S., Liu, W., Liu, Y., Liu, Y. L., Ordonez, G. Loachamin, Salvia, A. Lobo, Loi, A., Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lu, Q., Lucarelli, C., Lucchesi, D., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. J., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Malczewski, J. J., Malde, S., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manganella, F. M., Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, E., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martel, L., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Gomez, D. Martinez, Santos, D. Martinez, Vidal, F. Martinez, Granollers, A. Martorell i, Massafferri, A., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., de Cos, J. Mazorra, Mazurek, M., McCann, M., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Meadows, B., Meier, G., Melnychuk, D., Meng, F. M., Merk, M., Merli, A., Garcia, L. Meyer, Miao, D., Miao, H., Mikhasenko, M., Milanes, D. A., Minotti, A., Minucci, E., Miralles, T., Mitreska, B., Mitzel, D. S., Modak, A., Moeser, L., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Cardenas, E. F. Molina, Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., Moron, J., Morren, W., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Niu, Q., Nogarolli, P., Nogga, P., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Okhrimenko, O., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Osthues, D., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Paciolla, F., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Pan, X., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Parmar, D., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Paul, A., Pawley, C. J., Pellegrino, A., Peng, J., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Da Costa, H. Pereira, Castro, A. Pereiro, Perret, P., Perrevoort, A., Perro, A., Peters, M. J., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Piccolo, L., Pietrzyk, B., Pietrzyk, G., Pilato, R. N., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Poeschl, T., Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Provenzano, D., Pugatch, V., Punzi, G., Qasim, S., Qian, Q. Q., Qian, W., Qin, N., Qu, S., Quagliani, R., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, De Oliveira, V. Ramos, Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Alvarez, A. Rodriguez, Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogachev, A., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Vidal, A. Romero, Romolini, G., Ronchetti, F., Rong, T., Rotondo, M., Roy, S. R., Rudolph, M. S., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Sborzacchi, F., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schiller, M., Schindler, H., Schmelling, M., Schmidt, B., Schmitt, S., Schmitz, H., Schneider, O., Schopper, A., Schulte, N., Schulte, S., Schune, M. H., Schwemmer, R., Schwering, G., Sciascia, B., Sciuccati, A., Segal, I., Sellam, S., Semennikov, A., Senger, T., Soares, M. Senghi, Sergi, A., Serra, N., Sestini, L., Seuthe, A., Shang, Y., Shangase, D. M., Shapkin, M., Sharma, R. S., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Shevchenko, V., Shi, B., Shi, Q., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Coutinho, R. Silva, Simi, G., Simone, S., Skidmore, N., Skwarnicki, T., Slater, M. W., Smallwood, J. C., Smith, E., Smith, K., Smith, M., Snoch, A., Lavra, L. Soares, Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Sommerfeld, N. S., Song, R., Song, Y., Song, Y. S., De Almeida, F. L. Souza, De Paula, B. Souza, Norella, E. Spadaro, Spedicato, E., Speer, J. G., Spiridenkov, E., Spradlin, P., Sriskaran, V., Stagni, F., Stahl, M., Stahl, S., Stanislaus, S., Stefaniak, M., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sundfeld, D., Sutcliffe, W., Swallow, P. N., Swientek, K., Swystun, F., Szabelski, A., Szumlak, T., Tan, Y., Tang, Y., Tat, M. D., Terentev, A., Terzuoli, F., Teubert, F., Thomas, E., Thompson, D. J. D., Tilquin, H., Tisserand, V., T'Jampens, S., Tobin, M., Tomassetti, L., Tonani, G., Tong, X., Tork, T., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Urbach, B., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Cadenas, V. Valcarce, Valenti, G., Canudas, N. Valls, van Eldik, J., Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Laak, R., van Veghel, M., Vasquez, G., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Velthuis, J. J., Veltri, M., Venkateswaran, A., Verdoglia, M., Vesterinen, M., Benet, D. Vico, Villalba, P. Vidrier, Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, H., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Y. W., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, C., Whitehead, M., Whiter, E., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. J., Williams, M. R. J., Williams, R., Williams, Z., Wilson, F. F., Winn, M., Wislicki, W., Witek, M., Witola, L., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, X., Wu, Y., Wu, Z., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xing, T. X., Xu, A., Xu, L., Xu, M., Xu, Z., Yang, K., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yin, X., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenesini, F., Zeng, C., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhang, Z., Zhao, Y., Zhelezov, A., Zheng, S. Z., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.
Subjects: High Energy Physics - Experiment
Abstract: A search for $D^0$ meson decays to the $\pi^+\pi^-e^+e^-$ and $K^+K^-e^+e^-$ final states is reported using a sample of proton-proton collisions collected by the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb$^{-1}$. The decay $D^0 \rightarrow \pi^+\pi^-e^+e^-$ is observed for the first time when requiring that the two electrons are consistent with coming from the decay of a $\phi$ or $\rho^0/\omega$ meson. The corresponding branching fractions are measured relative to the $D^0 \rightarrow K^-\pi^-[e^+e^-]_{\rho^0/\omega}$ decay, where the two electrons are consistent with coming from the decay of a $\rho^0$ or $\omega$ meson. No evidence is found for the $D^0 \rightarrow K^+K^-e^+e^-$ decay and world-best limits are set on its branching fraction. The results are compared to, and found to be consistent with, the branching fractions of the $D^0 \rightarrow \pi^+\pi^-\mu^+\mu^-$ and $D^0 \rightarrow K^+K^-\mu^+\mu^-$ decays recently measured by LHCb and confirm lepton universality at the current precision., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/1611/ (LHCb public pages)
Published: 2024

127. Comparison of Static Analysis Architecture Recovery Tools for Microservice Applications

Author: Schneider, Simon, Bakhtin, Alexander, Li, Xiaozhou, Soldani, Jacopo, Brogi, Antonio, Cerny, Tomas, Scandariato, Riccardo, and Taibi, Davide
Subjects: Computer Science - Software Engineering
Abstract: Architecture recovery tools help software engineers obtain an overview of the structure of their software systems during all phases of the software development life cycle. This is especially important for microservice applications because they consist of multiple interacting microservices, which makes it more challenging to oversee the architecture. Various tools and techniques for architecture recovery (also called architecture reconstruction) have been presented in academic and gray literature sources, but no overview and comparison of their accuracy exists. This paper presents the results of a multivocal literature review with the goal of identifying architecture recovery tools for microservice applications and a comparison of the identified tools' architectural recovery accuracy. We focused on static tools since they can be integrated into fast-paced CI/CD pipelines. 13 such tools were identified from the literature and nine of them could be executed and compared on their capability of detecting different system characteristics. The best-performing tool exhibited an overall F1-score of 0.86. Additionally, the possibility of combining multiple tools to increase the recovery correctness was investigated, yielding a combination of four individual tools that achieves an F1-score of 0.91. Registered report: The methodology of this study has been peer-reviewed and accepted as a registered report at MSR'24: arXiv:2403.06941
Published: 2024

128. Particle-in-cell methods in edge plasma physics: the PICLS code

Author: Bottino, Alberto, Stier, Annika, Boesl, Mathias, Hayward-Schneider, Thomas, Bergmann, Andreas, Coster, David, Brunner, Stephan, Di Giannatale, Giovanni, and Villard, Laurent
Subjects: Physics - Plasma Physics
Abstract: Over the past decades, multiple gyrokinetic codes have shown to be able to simulate turbulence and associated transport in the core of Tokamak devices. However, their application to the edge and scrape-off layer (SOL) region presents significant challenges. To date, only few codes and models have been adapted to SOL/edge conditions. To further study the SOL region in particular, with its steep temperature and density gradients as well as large fluctuation amplitudes, the full-f particle-in-cell code PICLS has been developed. PICLS is based on a full-f gyrokinetic model with linearised field equations, considers kinetic electrons and uses logical sheath boundary conditions. In the past, PICLS was verified by applying it to a well-studied 1D parallel transport problem during an edge-localized mode in the SOL under both collisionless and collisional conditions, for which a Lenard-Bernstein collision operator was implemented. PICLS recently was extended towards three spatial dimensions to study turbulence in open-field-line regions in slab and closed-field-line toroidal geometries. In this work, we will focus on the models and methods we used for extending the code towards three spatial dimensions, including validation efforts and comparisons with other existing codes in closed-field-line geometry
Published: 2024

129. Hyperband-based Bayesian Optimization for Black-box Prompt Selection

Author: Schneider, Lennart, Wistuba, Martin, Klein, Aaron, Golebiowski, Jacek, Zappella, Giovanni, and Merra, Felice Antonio
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Optimal prompt selection is crucial for maximizing large language model (LLM) performance on downstream tasks. As the most powerful models are proprietary and can only be invoked via an API, users often manually refine prompts in a black-box setting by adjusting instructions and few-shot examples until they achieve good performance as measured on a validation set. Recent methods addressing static black-box prompt selection face significant limitations: They often fail to leverage the inherent structure of prompts, treating instructions and few-shot exemplars as a single block of text. Moreover, they often lack query-efficiency by evaluating prompts on all validation instances, or risk sub-optimal selection of a prompt by using random subsets of validation instances. We introduce HbBoPs, a novel Hyperband-based Bayesian optimization method for black-box prompt selection addressing these key limitations. Our approach combines a structural-aware deep kernel Gaussian Process to model prompt performance with Hyperband as a multi-fidelity scheduler to select the number of validation instances for prompt evaluations. The structural-aware modeling approach utilizes separate embeddings for instructions and few-shot exemplars, enhancing the surrogate model's ability to capture prompt performance and predict which prompt to evaluate next in a sample-efficient manner. Together with Hyperband as a multi-fidelity scheduler we further enable query-efficiency by adaptively allocating resources across different fidelity levels, keeping the total number of validation instances prompts are evaluated on low. Extensive evaluation across ten benchmarks and three LLMs demonstrate that HbBoPs outperforms state-of-the-art methods.
Published: 2024

130. Statistical Downscaling via High-Dimensional Distribution Matching with Generative Models

Author: Wan, Zhong Yi, Lopez-Gomez, Ignacio, Carver, Robert, Schneider, Tapio, Anderson, John, Sha, Fei, and Zepeda-Núñez, Leonardo
Subjects: Computer Science - Machine Learning, Mathematics - Numerical Analysis, Physics - Atmospheric and Oceanic Physics
Abstract: Statistical downscaling is a technique used in climate modeling to increase the resolution of climate simulations. High-resolution climate information is essential for various high-impact applications, including natural hazard risk assessment. However, simulating climate at high resolution is intractable. Thus, climate simulations are often conducted at a coarse scale and then downscaled to the desired resolution. Existing downscaling techniques are either simulation-based methods with high computational costs, or statistical approaches with limitations in accuracy or application specificity. We introduce Generative Bias Correction and Super-Resolution (GenBCSR), a two-stage probabilistic framework for statistical downscaling that overcomes the limitations of previous methods. GenBCSR employs two transformations to match high-dimensional distributions at different resolutions: (i) the first stage, bias correction, aligns the distributions at coarse scale, (ii) the second stage, statistical super-resolution, lifts the corrected coarse distribution by introducing fine-grained details. Each stage is instantiated by a state-of-the-art generative model, resulting in an efficient and effective computational pipeline for the well-studied distribution matching problem. By framing the downscaling problem as distribution matching, GenBCSR relaxes the constraints of supervised learning, which requires samples to be aligned. Despite not requiring such correspondence, we show that GenBCSR surpasses standard approaches in predictive accuracy of critical impact variables, particularly in predicting the tails (99% percentile) of composite indexes composed of interacting variables, achieving up to 4-5 folds of error reduction.
Published: 2024

131. dsLassoCov: a federated machine learning approach incorporating covariate control

Author: Cao, Han, Anguita, Augusto, Warembourg, Charline, Escriba-Montagut, Xavier, Vrijheid, Martine, Gonzalez, Juan R., Cadman, Tim, Schneider-Lindner, Verena, Durstewitz, Daniel, Basagana, Xavier, and Schwarz, Emanuel
Subjects: Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning
Abstract: Machine learning has been widely adopted in biomedical research, fueled by the increasing availability of data. However, integrating datasets across institutions is challenging due to legal restrictions and data governance complexities. Federated learning allows the direct, privacy preserving training of machine learning models using geographically distributed datasets, but faces the challenge of how to appropriately control for covariate effects. The naive implementation of conventional covariate control methods in federated learning scenarios is often impractical due to the substantial communication costs, particularly with high-dimensional data. To address this issue, we introduce dsLassoCov, a machine learning approach designed to control for covariate effects and allow an efficient training in federated learning. In biomedical analysis, this allow the biomarker selection against the confounding effects. Using simulated data, we demonstrate that dsLassoCov can efficiently and effectively manage confounding effects during model training. In our real-world data analysis, we replicated a large-scale Exposome analysis using data from six geographically distinct databases, achieving results consistent with previous studies. By resolving the challenge of covariate control, our proposed approach can accelerate the application of federated learning in large-scale biomedical studies., Comment: 17 pages, 5 figures
Published: 2024

132. The Sloan Digital Sky Survey Reverberation Mapping Project: Insights on Maximizing Efficiency in Lag Measurements and Black-Hole Masses

Author: Homayouni, Y., Jiang, Yuanzhe, Brandt, W. N., Grier, C. J., Trump, Jonathan R., Shen, Yue, Horne, Keith, Hall, Patrick B., Anderson, Scott F., Ho, Luis C., and Schneider, D. P.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Multi-year observations from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project have significantly increased the number of quasars with reliable reverberation-mapping lag measurements. We statistically analyze target properties, light-curve characteristics, and survey design choices to identify factors crucial for successful and efficient RM surveys. Analyzing 172 high-confidence ("gold") lag measurements from SDSS-RM for the H$\beta$, MgII, and CIV emission lines, we find that the Durbin-Watson statistic (a statistical test for residual correlation) is the most significant predictor of light curves suitable for lag detection. Variability signal-to-noise ratio and emission-line placement on the detector also correlate with successful lag measurements. We further investigate the impact of observing cadence on survey design by analyzing the effect of reducing observations in the first year of SDSS-RM. Our results demonstrate that a modest reduction in observing cadence to $\sim$1.5 weeks between observations can retain approximately 90% of the lag measurements compared to twice-weekly observations in the initial year. Provided similar and uniform sampling in subsequent years, this adjustment has a minimal effect on the overall recovery of lags across all emission lines. These results provide valuable inputs for optimizing future RM surveys., Comment: 22 pages, 9 figures, and 3 tables. Submitted to the Astrophysical Journal
Published: 2024

133. Rendering-Refined Stable Diffusion for Privacy Compliant Synthetic Data

Author: Patwari, Kartik, Schneider, David, Sun, Xiaoxiao, Chuah, Chen-Nee, Lyu, Lingjuan, and Sharma, Vivek
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Growing privacy concerns and regulations like GDPR and CCPA necessitate pseudonymization techniques that protect identity in image datasets. However, retaining utility is also essential. Traditional methods like masking and blurring degrade quality and obscure critical context, especially in human-centric images. We introduce Rendering-Refined Stable Diffusion (RefSD), a pipeline that combines 3D-rendering with Stable Diffusion, enabling prompt-based control over human attributes while preserving posture. Unlike standard diffusion models that fail to retain posture or GANs that lack realism and flexible attribute control, RefSD balances posture preservation, realism, and customization. We also propose HumanGenAI, a framework for human perception and utility evaluation. Human perception assessments reveal attribute-specific strengths and weaknesses of RefSD. Our utility experiments show that models trained on RefSD pseudonymized data outperform those trained on real data in detection tasks, with further performance gains when combining RefSD with real data. For classification tasks, we consistently observe performance improvements when using RefSD data with real data, confirming the utility of our pseudonymized data.
Published: 2024

134. Polyhedral Discretizations for Elliptic PDEs

Author: Liu, Junyu, Panozzo, Daniele, Botsch, Mario, and Schneider, Teseo
Subjects: Computer Science - Graphics, Mathematics - Numerical Analysis
Abstract: We study the use of polyhedral discretizations for the solution of heat diffusion and elastodynamic problems in computer graphics. Polyhedral meshes are more natural for certain applications than pure triangular or quadrilateral meshes, which thus received significant interest as an alternative representation. We consider finite element methods using barycentric coordinates as basis functions and the modern virtual finite element approach. We evaluate them on a suite of classical graphics problems to understand their benefits and limitations compared to standard techniques on simplicial discretizations. Our analysis provides recommendations and a benchmark for developing polyhedral meshing techniques and corresponding analysis techniques.
Published: 2024

135. The Gauss image problem for pseudo-cones

Author: Schneider, Rolf
Subjects: Mathematics - Metric Geometry, 52A20
Abstract: The Gauss image problem for convex bodies asks for the existence of a convex body that "links" two given measures on the unit sphere in a certain way. We treat here a corresponding question for pseudo-cones, that is, for unbounded closed convex sets strictly contained in their recession cones., Comment: 17 pages
Published: 2024

136. Sparse autoencoders reveal selective remapping of visual concepts during adaptation

Author: Lim, Hyesu, Choi, Jinho, Choo, Jaegul, and Schneider, Steffen
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: Adapting foundation models for specific purposes has become a standard approach to build machine learning systems for downstream applications. Yet, it is an open question which mechanisms take place during adaptation. Here we develop a new Sparse Autoencoder (SAE) for the CLIP vision transformer, named PatchSAE, to extract interpretable concepts at granular levels (e.g. shape, color, or semantics of an object) and their patch-wise spatial attributions. We explore how these concepts influence the model output in downstream image classification tasks and investigate how recent state-of-the-art prompt-based adaptation techniques change the association of model inputs to these concepts. While activations of concepts slightly change between adapted and non-adapted models, we find that the majority of gains on common adaptation tasks can be explained with the existing concepts already present in the non-adapted foundation model. This work provides a concrete framework to train and use SAEs for Vision Transformers and provides insights into explaining adaptation mechanisms., Comment: A demo is available at github.com/dynamical-inference/patchsae
Published: 2024

137. Defects and Phases of Higher Rank Abelian GLSMs

Author: Brunner, Ilka, Roggenkamp, Daniel, and Schneider, Christian P. M.
Subjects: High Energy Physics - Theory, Mathematical Physics, Mathematics - Algebraic Geometry, Mathematics - Quantum Algebra
Abstract: We construct defects describing the transition between different phases of gauged linear sigma models with higher rank abelian gauge groups, as well as defects embedding these phases into the GLSMs. Our construction refers entirely to the sector protected by B-type supersymmetry, decoupling the gauge sector. It relies on an abstract characterization of such transition defects and does not involve an actual perturbative analysis. It turns out that the choices that are required to characterize consistent transition defects match with the homotopy classes of paths between different phases. Our method applies to non-anomalous as well as anomalous GLSMs, and we illustrate both cases with examples. This includes the GLSM associated to the resolution of the $A_N$ singularity and one describing the entire parameter space of $N = 2$ minimal models, in particular, the relevant flows between them. Via fusion with boundary conditions, the defects we construct yield functors describing the transport of D-branes on parameter space. We find that our results match with known results on D-brane transport., Comment: 37 pages
Published: 2024

138. Observation of Cosmic-Ray Anisotropy in the Southern Hemisphere with Twelve Years of Data Collected by the IceCube Neutrino Observatory

Author: Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguado, T., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Babu, R., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brisson-Tsavoussis, Z., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Cochling, C., Coleman, A., Coleman, P., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Esmail, W., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Gruchot, K., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamacher, L., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Hardy, A., Hayes, W., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hmaid, R., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kobayashi, Y., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kowalski, M., Kozynets, T., Krieger, N., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Mand, A., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Moy, A., Mukherjee, T., Naab, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Parrish, V., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Pyras, L., Raab, C., Rack-Helleis, J., Rad, N., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, E., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwirn, S., Sclafani, S., Seckel, D., Seen, L., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Simmons, A., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stachurska, J., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thorpe, A., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, M., Woodward, H., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zegarelli, A., Zhang, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We analyzed the 7.92$\times 10^{11}$ cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from May 13, 2011, when the fully constructed experiment started to take data, to May 12, 2023. This dataset provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100-300 TeV energy range.
Published: 2024

139. New Ultracool Companions to Nearby White Dwarfs

Author: Bravo, Alexia, Schneider, Adam C., Casewell, Sarah, Rothermich, Austin, Faherty, Jacqueline K., French, Jenni R., Bickle, Thomas P., Meisner, Aaron M., Kirkpatrick, J. Davy, Kuchner, Marc J., Burgasser, Adam J., Marocco, Federico, Debes, John H., Sainio, Arttu, Gramaize, Léopold, Kiwy, Frank, Jalowiczor, Peter A., and Abdullahi, Awab
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: We conducted a search for new ultracool companions to nearby white dwarfs using multiple methods, including the analysis of colors and examination of images in both the optical and the infrared. Through this process, we identified fifty-one previously unrecognized systems with candidate ultracool companions. Thirty-one of these systems are resolved in at least one catalog, and all but six are confirmed as co-moving companions via common proper motion and consistent parallax measurements (when available). We have followed up four co-moving companions with near-infrared spectroscopy and confirm their ultracool nature. The remaining twenty candidates are unresolved, but show clear signs of infrared excess which is most likely due to the presence of a cold, low-mass companion or a dusty circumstellar disk. Three of these unresolved systems have existing optical spectra that clearly show the presence of a cool stellar companion to the white dwarf primary via spectral decomposition. These new discoveries, along with our age estimates for the primary white dwarfs, will serve as valuable benchmark systems for future characterization of ultracool dwarfs., Comment: Accepted to the Astronomical Journal
Published: 2024

140. Going from 3D common-envelope simulations to fast 1D simulations

Author: Bronner, V. A., Schneider, F. R. N., Podsiadlowski, Ph., and Roepke, F. K.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract: One-dimensional (1D) methods for simulating the common-envelope (CE) phase offer advantages over three-dimensional (3D) simulations regarding their computational speed and feasibility. We present the 1D CE method from Bronner et al. (2024), including the results of the CE simulations of an asymptotic giant branch star donor. We further test this method in the massive star regime by computing the CE event of a red supergiant with a neutron-star mass and a black-hole mass companion. The 1D model can reproduce the orbital evolution and the envelope ejection from 3D simulations when choosing suitable values for the free parameters in the model. The best-fitting values differ from the expectations based on the low mass simulations, indicating that the free parameters depend on the structure of the giant star. The released recombination energy from hydrogen and helium helps to expand the envelope, similar to the low-mass CE simulations., Comment: 14 pages, 5 figures, accepted for publication in the Bulletin de la Soci\'et\'e Royale des Sciences de Li\`ege, Proceedings of the 41st Li\`ege Astrophysical Colloquium
Published: 2024

141. Magnetically-controlled Vortex Dynamics in a Ferromagnetic Superconductor

Author: Wilcox, Joseph Alec, Schneider, Lukas, Marchiori, Estefani, Plastovets, Vadim, Buzdin, Alexandre, Sahafi, Pardis, Jordan, Andrew, Budakian, Raffi, Ren, Tong, Veschunov, Ivan, Tamegai, Tsuyoshi, Friedemann, Sven, Poggio, Martino, and Bending, Simon John
Subjects: Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract: Ferromagnetic superconductors are exceptionally rare because the strong ferromagnetic exchange field usually destroys singlet superconductivity. EuFe$_2$(As$_{1-x}$P$_x$)$_2$, an iron-based superconductor with a maximum critical temperature of $\sim$25 K, is a unique material that exhibits full coexistence with ferromagnetic order below $T_\mathrm{FM} \approx 19$ K. The interplay between the two leads to a narrowing of ferromagnetic domains at higher temperatures and the spontaneous nucleation of vortices/antivortices at lower temperatures. Here we demonstrate how the underlying magnetic structure directly controls the superconducting vortex dynamics in applied magnetic fields. Just below $T_\mathrm{FM}$ we observe a pronounced temperature-dependent peak in both the coercivity and the creep activation energy, the latter becoming rapidly suppressed in large applied magnetic fields. We attribute this behaviour to the formation of vortex polarons arising from the unique interaction between free vortices and magnetic stripe domains. We present a theoretical description of the properties of vortex polarons that explains our main observations, showing how they lead to vortex trapping and an attractive vortex-vortex interaction at short distances. In stark contrast, strong magnetic irreversibility at low temperatures is linked to a critical current governed by giant flux creep over an activation barrier for vortex-antivortex annihilation near domain walls. Our work reveals unexplored new routes for the magnetic enhancement of vortex pinning with particularly important applications in high-current conductors for operation at high magnetic fields., Comment: 15 pages, 5 figures
Published: 2024

142. Spectroscopic Investigations of Multiple Environments in Er:CaWO4 through Charge Imbalance

Author: Becker, Fabian, Curtin, Catherine L., KC, Sudip, Schneider, Tim, Sauerzopf, Lorenz J. J., Elzeiny, Ibrahim, and Müller, Kai
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Quantum Physics
Abstract: We present a detailed spectroscopic study of the $^4\mathrm{I}_{13/2}$ and $^4\mathrm{I}_{15/2}$ Er$^{3+}$ multiplets of Er:CaWO$_4$ grown without a co-dopant. Using photoluminescence and photoluminescence excitation measurements, we find multiple environments into which the Erbium ions are incorporated in the crystal. For the four most prevalent environments, we provide a complete assignment of the $^4\mathrm{I}_{13/2}$ and $^4\mathrm{I}_{15/2}$ sublevel energies. Polarization-dependent absorption and emission spectroscopy allow us to identify the irreducible representations of the states and determine the dipole nature of transitions. In addition, we compare the different relaxation paths within $^4\mathrm{I}_{13/2}$ and $^4\mathrm{I}_{15/2}$ multiplets via line broadening and lifetime measurements. Finally, spectral, lifetime, and polarization measurements indicate similarities between the studied environments.
Published: 2024

143. Information borrowing in Bayesian clinical trials: choice of tuning parameters for the robust mixture prior

Author: Weru, Vivienn, Kopp-Schneider, Annette, Wiesenfarth, Manuel, Weber, Sebastian, and Calderazzo, Silvia
Subjects: Statistics - Methodology
Abstract: Borrowing historical data for use in clinical trials has increased in recent years. This is accomplished in the Bayesian framework by specification of informative prior distributions. One such approach is the robust mixture prior arising as a weighted mixture of an informative prior and a robust prior inducing dynamic borrowing that allows to borrow most when the current and external data are observed to be similar. The robust mixture prior requires the choice of three additional quantities: the mixture weight, and the mean and dispersion of the robust component. Some general guidance is available, but a case-by-case study of the impact of these quantities on specific operating characteristics seems lacking. We focus on evaluating the impact of parameter choices for the robust component of the mixture prior in one-arm and hybrid-control trials. The results show that all three quantities can strongly impact the operating characteristics. In particular, as already known, variance of the robust component is linked to robustness. Less known, however, is that its location can have a strong impact on Type I error rate and MSE which can even become unbounded. Further, the impact of the weight choice is strongly linked with the robust component's location and variance. Recommendations are provided for the choice of the robust component parameters, prior weight, alternative functional form for this component as well as considerations to keep in mind when evaluating operating characteristics.
Published: 2024

144. A Physics-Constrained Neural Differential Equation Framework for Data-Driven Snowpack Simulation

Author: Charbonneau, Andrew, Deck, Katherine, and Schneider, Tapio
Subjects: Computer Science - Machine Learning, Physics - Atmospheric and Oceanic Physics
Abstract: This paper presents a physics-constrained neural differential equation framework for parameterization, and employs it to model the time evolution of seasonal snow depth given hydrometeorological forcings. When trained on data from multiple SNOTEL sites, the parameterization predicts daily snow depth with under 9% median error and Nash Sutcliffe Efficiencies over 0.94 across a wide variety of snow climates. The parameterization also generalizes to new sites not seen during training, which is not often true for calibrated snow models. Requiring the parameterization to predict snow water equivalent in addition to snow depth only increases error to ~12%. The structure of the approach guarantees the satisfaction of physical constraints, enables these constraints during model training, and allows modeling at different temporal resolutions without additional retraining of the parameterization. These benefits hold potential in climate modeling, and could extend to other dynamical systems with physical constraints., Comment: This Work has been submitted to Artificial Intelligence for Earth Sciences. Copyright in this Work may be transferred without further notice
Published: 2024

145. Analysis, Design, and Fabrication of a High-Gain Low-Profile Metasurface Antenna Using Direct Feeding of Sievenpiper s HIS

Author: Ghaneizadeh, Alireza, Peik, Soeren F., Schneider, Martin, and Joodaki, Mojtaba
Subjects: Physics - Applied Physics, Computer Science - Emerging Technologies, Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control
Abstract: HISs have recently shown the ability to support leaky waves, and to excite plasmonic and HIS resonance frequency modes for use as an antenna. In this paper, we analyzed, designed, and fabricated a TMA by directly feeding edge-located HIS cells through a microstrip feeding network. In contrast to other metasurface antennas that necessitate an external antenna to excite metasurfaces, our approach is inspired by the TMA design methodology that directly feeds the HIS cells rather than using it as a reflector. We developed a circuit model for the proposed structure and compared the results with those obtained from full-wave simulations. In addition, our further objective was to simplify the structure based on the working principle of the proposed antenna. This objective was achieved by converting square patches into parallel strip lines, leading to an aperture efficiency of 0.77. This simplification also creates additional space to explore various resonant patterns on the top surface and the feeding network on the bottom surface of the TMA. Full-wave simulation results indicate that, despite the compact dimensions of the proposed array with 64 electrically small patch resonators (1.84{\lambda}*1.84{\lambda}*0.032{\lambda}, where{\lambda}is the free space wavelength at 6.0 GHz), it achieves a realized gain, HPBW of about 15.1 dBi and 28{\deg} respectively at 6 GHz. Finally, we constructed a prototype and conducted measurements to validate the design. Measured results demonstrate good agreement with simulation ones with a gain of about 13.5 (+-0.5) dBi and a HPBW of 27{\deg} at 6 GHz. The proposed TMA is scaled to fit within the required dimensions for smart handheld devices at higher frequencies, while maintaining high gain capability. The design s scalability, single-feed, and compact footprint make it optimal for diverse wireless communication systems, such as car to car communications.
Published: 2024

146. What should a neuron aim for? Designing local objective functions based on information theory

Author: Schneider, Andreas C., Neuhaus, Valentin, Ehrlich, David A., Makkeh, Abdullah, Ecker, Alexander S., Priesemann, Viola, and Wibral, Michael
Subjects: Computer Science - Information Theory, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract: In modern deep neural networks, the learning dynamics of the individual neurons is often obscure, as the networks are trained via global optimization. Conversely, biological systems build on self-organized, local learning, achieving robustness and efficiency with limited global information. We here show how self-organization between individual artificial neurons can be achieved by designing abstract bio-inspired local learning goals. These goals are parameterized using a recent extension of information theory, Partial Information Decomposition (PID), which decomposes the information that a set of information sources holds about an outcome into unique, redundant and synergistic contributions. Our framework enables neurons to locally shape the integration of information from various input classes, i.e. feedforward, feedback, and lateral, by selecting which of the three inputs should contribute uniquely, redundantly or synergistically to the output. This selection is expressed as a weighted sum of PID terms, which, for a given problem, can be directly derived from intuitive reasoning or via numerical optimization, offering a window into understanding task-relevant local information processing. Achieving neuron-level interpretability while enabling strong performance using local learning, our work advances a principled information-theoretic foundation for local learning strategies., Comment: 24 pages, 11 figures
Published: 2024

147. Dry Transfer Based on PMMA and Thermal Release Tape for Heterogeneous Integration of 2D-TMDC Layers

Author: Ghiami, Amir, Fiadziushkin, Hleb, Sun, Tianyishan, Tang, Songyao, Wang, Yibing, Mayer, Eva, Schneider, Jochen M., Piacentini, Agata, Lemme, Max C., Heuken, Michael, Kalisch, Holger, and Vescan, Andrei
Subjects: Physics - Applied Physics, Condensed Matter - Materials Science
Abstract: A reliable and scalable transfer of 2D-TMDCs (two-dimensional transition metal dichalcogenides) from the growth substrate to a target substrate with high reproducibility and yield is a crucial step for device integration. In this work, we have introduced a scalable dry-transfer approach for 2D-TMDCs grown by MOCVD (metal-organic chemical vapor deposition) on sapphire. Transfer to a silicon/silicon dioxide (Si/SiO$_2$) substrate is performed using PMMA (poly(methyl methacrylate)) and TRT (thermal release tape) as sacrificial layer and carrier, respectively. Our proposed method ensures a reproducible peel-off from the growth substrate and better preservation of the 2D-TMDC during PMMA removal in solvent, without compromising its adhesion to the target substrate. A comprehensive comparison between the dry method introduced in this work and a standard wet transfer based on potassium hydroxide (KOH) solution shows improvement in terms of cleanliness and structural integrity for dry-transferred layer, as evidenced by X-ray photoemission and Raman spectroscopy, respectively. Moreover, fabricated field-effect transistors (FETs) demonstrate improvements in subthreshold slope, maximum drain current and device-to-device variability. The dry-transfer method developed in this work enables large-area integration of 2D-TMDC layers into (opto)electronic components with high reproducibility, while better preserving the as-grown properties of the layers., Comment: 29 pages
Published: 2024

148. Asymptotics for the reciprocal and shifted quotient of the partition function

Author: Banerjee, Koustav, Paule, Peter, Radu, Cristian-Silviu, and Schneider, Carsten
Subjects: Mathematics - Number Theory, Computer Science - Symbolic Computation, Mathematics - Combinatorics, 05A16, 05A20, 11P82
Abstract: Let $p(n)$ denote the partition function. In this paper our main goal is to derive an asymptotic expansion up to order $N$ (for any fixed positive integer $N$) along with estimates for error bounds for the shifted quotient of the partition function, namely $p(n+k)/p(n)$ with $k\in \mathbb{N}$, which generalizes a result of Gomez, Males, and Rolen. In order to do so, we derive asymptotic expansions with error bounds for the shifted version $p(n+k)$ and the multiplicative inverse $1/p(n)$, which is of independent interest.
Published: 2024

149. Uncovering dynamics between SARS-CoV-2 wastewater concentrations and community infections via Bayesian spatial functional concurrent regression

Author: Sun, Thomas Y., Schedler, Julia C., Kowal, Daniel R., Schneider, Rebecca, Stadler, Lauren B., Hopkins, Loren, and Ensor, Katherine B.
Subjects: Statistics - Methodology, Statistics - Applications
Abstract: Monitoring wastewater concentrations of SARS-CoV-2 yields a low-cost, noninvasive method for tracking disease prevalence and provides early warning signs of upcoming outbreaks in the serviced communities. There is tremendous clinical and public health interest in understanding the exact dynamics between wastewater viral loads and infection rates in the population. As both data sources may contain substantial noise and missingness, in addition to spatial and temporal dependencies, properly modeling this relationship must address these numerous complexities simultaneously while providing interpretable and clear insights. We propose a novel Bayesian functional concurrent regression model that accounts for both spatial and temporal correlations while estimating the dynamic effects between wastewater concentrations and positivity rates over time. We explicitly model the time lag between the two series and provide full posterior inference on the possible delay between spikes in wastewater concentrations and subsequent outbreaks. We estimate a time lag likely between 5 to 11 days between spikes in wastewater levels and reported clinical positivity rates. Additionally, we find a dynamic relationship between wastewater concentration levels and the strength of its association with positivity rates that fluctuates between outbreaks and non-outbreaks.
Published: 2024

150. Euclid preparation: TBD. The impact of line-of-sight projections on the covariance between galaxy cluster multi-wavelength observable properties -- insights from hydrodynamic simulations

Author: Euclid Collaboration, Ragagnin, A., Saro, A., Andreon, S., Biviano, A., Dolag, K., Ettori, S., Giocoli, C., Brun, A. M. C. Le, Mamon, G. A., Maughan, B. J., Meneghetti, M., Moscardini, L., Pacaud, F., Pratt, G. W., Sereno, M., Borgani, S., Calura, F., Castignani, G., De Petris, M., Eckert, D., Lesci, G. F., Macias-Perez, J., Maturi, M., Amara, A., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Dubath, F., Dupac, X., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Fumana, M., George, K., Gillis, B., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meylan, G., Moresco, M., Munari, E., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Scaramella, R., Schneider, P., Schrabback, T., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Gracia-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bergamini, P., Blanchard, A., Blot, L., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., Costanzi, M., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hall, A., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Schultheis, M., Simon, P., Mancini, A. Spurio, Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Verza, G.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Cluster cosmology can benefit from combining multi-wavelength studies, which can benefit from characterising the correlation coefficients between different mass-observable relations. In this work, we aim to provide information on the scatter, the skewness, and the covariance of various mass-observable relations in galaxy clusters in cosmological hydrodynamic simulations. This information will help future analyses to better tackle accretion histories and projection effects and model mass observable relations for cosmology studies.We identify galaxy clusters in Magneticum Box2b simulations with mass $M_{\rm 200c}>10^{14} {\rm M}_\odot$ at redshift $z=0.24$ and $z=0.90$. Our analysis includes \Euclid-derived properties such as richness, stellar mass, lensing mass, and concentration. Additionally, we investigate complementary multi-wavelength data, including X-ray luminosity, integrated Compton-$y$ parameter, gas mass, and temperature. The impact of projection effects on mass-observable residuals and correlations is then examined. At intermediate redshift ($z=0.24$), projection effects impact lensing concentration, richness, and gas mass the most in terms of scatter and skewness of log-residuals of scaling relations. The contribution of projection effects can be significant enough to boost a spurious hot- vs. cold-baryons correlation and consequently hide underlying correlations due to halo accretion histories. At high redshift ($z=0.9$), the richness has a much lower scatter (of log-residuals), and the quantity that is most impacted by projection effects is the lensing mass. Lensing concentration reconstruction, in particular, is affected by deviations of the reduced-shear profile shape from the one derived by an NFW profile rather than interlopers in the line of sight., Comment: 26 pages, 22 figures, submitted to A&A, replied to referee comments
Published: 2024

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