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51. Very-high-energy $\gamma$-ray emission from young massive star clusters in the Large Magellanic Cloud

Author

Aharonian, F., Benkhali, F. Ait, Aschersleben, J., Ashkar, H., Backes, M., Martins, V. Barbosa, Batzofin, R., Becherini, Y., Berge, D., Bernlöhr, K., Böttcher, M., Bolmont, J., de Lavergne, M. de Bony, Borowska, J., Brose, R., Brown, A., Brun, F., Bruno, B., Burger-Scheidlin, C., Casanova, S., Celic, J., Cerruti, M., Chand, T., Chandra, S., Chen, A., Chibueze, J., Chibueze, O., Cotter, G., Cristofari, P., Devin, J., Djannati-Ataï, A., Djuvsland, J., Dmytriiev, A., Egberts, K., Einecke, S., Feijen, K., Filipovic, M., Fontaine, G., Funk, S., Gabici, S., Gallant, Y. A., Glicenstein, J. F., Glombitza, J., Grolleron, G., Haerer, L., Heß, B., Hinton, J. A., Hofmann, W., Holch, T. L., Horns, D., Huang, Zhiqiu, Jamrozy, M., Jankowsky, F., Jung-Richardt, I., Kasai, E., Katarzyński, K., Khatoon, R., Khélifi, B., Kluźniak, W., Komin, Nu., Kosack, K., Kostunin, D., Kundu, A., Lang, R. G., Stum, S. Le, Lemière, A., Lemoine-Goumard, M., Lenain, J. -P., Leuschner, F., Mackey, J., Marandon, V., Martí-Devesa, G., Marx, R., Mehta, A., Mitchell, A., Moderski, R., Moghadam, M. O., Mohrmann, L., Montanari, A., Moulin, E., de Naurois, M., Niemiec, J., Ohm, S., Olivera-Nieto, L., Wilhelmi, E. de Ona, Ostrowski, M., Panny, S., Pensec, U., Peron, G., Pühlhofer, G., Quirrenbach, A., Ravikularaman, S., Regeard, M., Reimer, A., Reimer, O., Ren, H., Renaud, M., Reville, B., Rieger, F., Rowell, G., Rudak, B., Ruiz-Velasco, E., Sabri, K., Sahakian, V., Salzmann, H., Santangelo, A., Sasaki, M., Schäfer, J., Schüssler, F., Schutte, H. M., Sol, H., Spencer, S., Stawarz, Ł., Steinmassl, S., Steppa, C., Streil, K., Sushch, I., Taylor, A. M., Terrier, R., Tsirou, M., Tsuji, N., van Eldik, C., Vecchi, M., Venter, C., Vink, J., Wagner, S. J., White, R., Wierzcholska, A., Zacharias, M., Zdziarski, A. A., Zech, A., and Żywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Tarantula Nebula in the Large Magellanic Cloud is known for its high star formation activity. At its center lies the young massive star cluster R136, providing a significant amount of the energy that makes the nebula shine so brightly at many wavelengths. Recently, young massive star clusters have been suggested to also efficiently produce high-energy cosmic rays, potentially beyond PeV energies. Here, we report the detection of very-high-energy $\gamma$-ray emission from the direction of R136 with the High Energy Stereoscopic System, achieved through a multicomponent, likelihood-based modeling of the data. This supports the hypothesis that R136 is indeed a very powerful cosmic-ray accelerator. Moreover, from the same analysis, we provide an updated measurement of the $\gamma$-ray emission from 30 Dor C, the only superbubble detected at TeV energies presently. The $\gamma$-ray luminosity above $0.5\,\mathrm{TeV}$ of both sources is $(2-3)\times 10^{35}\,\mathrm{erg}\,\mathrm{s}^{-1}$. This exceeds by more than a factor of 2 the luminosity of HESS J1646$-$458, which is associated with the most massive young star cluster in the Milky Way, Westerlund 1. Furthermore, the $\gamma$-ray emission from each source is extended with a significance of $>3\sigma$ and a Gaussian width of about $30\,\mathrm{pc}$. For 30 Dor C, a connection between the $\gamma$-ray emission and the nonthermal X-ray emission appears likely. Different interpretations of the $\gamma$-ray signal from R136 are discussed., Comment: 10+11 pages, 4+6 figures. Corresponding authors: L. Mohrmann, N. Komin

Published
2024
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52. Metal-silicate mixing in planetesimal collisions

Author

Shuai, Kang, Schäfer, Christoph M., Burger, Christoph, and Hui, Hejiu

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

Impacts between differentiated planetesimals are ubiquitous in protoplanetary discs and may mix materials from the core, mantle, and crust of planetesimals, thus forming stony-iron meteorites. The surface composition of the asteroid (16) Psyche represents a mixture of metal and non-metal components. However, the velocities, angles, and outcome regimes of impacts that mixed metal and silicate from different layers of planetesimals are debated. Our aim is to investigate the impacts between planetesimals that can mix large amounts of metal and silicate, and the mechanism of stony-iron meteorite formation. We used smooth particle hydrodynamics to simulate the impacts between differentiated planetesimals with various initial conditions that span different outcome regimes. In our simulations, the material strength was included and the effects of the states of planetesimal cores were studied. Using a statistical approach, we quantitatively analysed the distributions of metal and silicate after impacts. Our simulations modelled the mass, depth, and sources of the metal-silicate mixture in different impact conditions. Our results suggest that the molten cores in planetesimals could facilitate mixing of metal and silicate. Large amounts of the metal-silicate mixture could be produced by low-energy accretional impacts and high-energy erosive impacts in the largest impact remnant, and by hit-and-run and erosive impacts in the second-largest impact remnant. After impact, most of the metal-silicate mixture was buried at depth, consistent with the low cooling rates of stony-iron meteorites. Our results indicate that mesosiderites potentially formed in an erosive impact, while pallasites potentially formed in an accretional or hit-and-run impact. The mixing of metal and non-metal components on Psyche may also be the result of impacts.

Published
2024
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53. Multi-Modal Dataset Creation for Federated Learning with DICOM Structured Reports

Author

Tölle, Malte, Burger, Lukas, Kelm, Halvar, André, Florian, Bannas, Peter, Diller, Gerhard, Frey, Norbert, Garthe, Philipp, Groß, Stefan, Hennemuth, Anja, Kaderali, Lars, Krüger, Nina, Leha, Andreas, Martin, Simon, Meyer, Alexander, Nagel, Eike, Orwat, Stefan, Scherer, Clemens, Seiffert, Moritz, Seliger, Jan Moritz, Simm, Stefan, Friede, Tim, Seidler, Tim, and Engelhardt, Sandy

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Purpose: Federated training is often hindered by heterogeneous datasets due to divergent data storage options, inconsistent naming schemes, varied annotation procedures, and disparities in label quality. This is particularly evident in the emerging multi-modal learning paradigms, where dataset harmonization including a uniform data representation and filtering options are of paramount importance. Methods: DICOM structured reports enable the standardized linkage of arbitrary information beyond the imaging domain and can be used within Python deep learning pipelines with highdicom. Building on this, we developed an open platform for data integration and interactive filtering capabilities that simplifies the process of assembling multi-modal datasets. Results: In this study, we extend our prior work by showing its applicability to more and divergent data types, as well as streamlining datasets for federated training within an established consortium of eight university hospitals in Germany. We prove its concurrent filtering ability by creating harmonized multi-modal datasets across all locations for predicting the outcome after minimally invasive heart valve replacement. The data includes DICOM data (i.e. computed tomography images, electrocardiography scans) as well as annotations (i.e. calcification segmentations, pointsets and pacemaker dependency), and metadata (i.e. prosthesis and diagnoses). Conclusion: Structured reports bridge the traditional gap between imaging systems and information systems. Utilizing the inherent DICOM reference system arbitrary data types can be queried concurrently to create meaningful cohorts for clinical studies. The graphical interface as well as example structured report templates will be made publicly available.

Published
2024

54. Asymptotic and stability analysis of kinetic models for opinion formation on networks: an Allen-Cahn approach

Author

Burger, M., Loy, N., and Rossi, A.

Subjects
Physics - Physics and Society, Mathematical Physics
Abstract

We present the analysis of the stationary equilibria and their stability in case of an opinion formation process in presence of binary opposite opinions evolving according to majority-like rules on social networks. The starting point is a kinetic Boltzmann-type model derived from microscopic interactions rules for the opinion exchange among individuals holding a certain degree of connectivity. The key idea is to derive from the kinetic model an Allen-Cahn type equation for the fraction of individuals holding one of the two opinions. The latter can be studied by means of a linear stability analysis and by exploiting integral operator analysis. While this is true for ternary interactions, for binary interactions the derived equation of interest is a linear scattering equation, that can be studied by means of General Relative Entropy tools and integral operators.

Published
2024

55. H.E.S.S. observations of the 2021 periastron passage of PSR B1259-63/LS 2883

Author

Collaboration, H. E. S. S., Aharonian, F., Benkhali, F. Ait, Aschersleben, J., Ashkar, H., Backes, M., Martins, V. Barbosa, Batzofin, R., Becherini, Y., Berge, D., Bernlöhr, K., Böttcher, M., Boisson, C., Bolmont, J., de Lavergne, M. de Bony, Borowska, J., Bouyahiaoui, M., Brose, R., Brown, A., Brun, F., Bruno, B., Bulik, T., Burger-Scheidlin, C., Caroff, S., Casanova, S., Celic, J., Cerruti, M., Chand, T., Chandra, S., Chen, A., Chibueze, J., Chibueze, O., Cotter, G., Mbarubucyeye, J. Damascene, Devin, J., Djuvsland, J., Dmytriiev, A., Egberts, K., Einecke, S., Ernenwein, J. -P., Fontaine, G., Funk, S., Gabici, S., Gallant, Y. A., Glawion, D., Glicenstein, J. F., Goswami, P., Grolleron, G., Haerer, L., Heß, B., Hofmann, W., Holch, T. L., Holler, M., Huang, Zhiqiu, Jamrozy, M., Jankowsky, F., Joshi, V., Jung-Richardt, I., Kasai, E., Katarzyński, K., Khangulyan, D., Khatoon, R., Khélifi, B., Kluźniak, W., Komin, Nu., Kosack, K., Kostunin, D., Kundu, A., Lang, R. G., Stum, S. Le, Leitl, F., Lemière, A., Lemoine-Goumard, M., Lenain, J. -P., Leuschner, F., Mackey, J., Malyshev, D., Martí-Devesa, G., Marx, R., Mehta, A., Meintjes, P. J., Mitchell, A., Moderski, R., Mohrmann, L., Montanari, A., Moulin, E., Murach, T., de Naurois, M., Niemiec, J., Ohm, S., Wilhelmi, E. de Ona, Ostrowski, M., Panny, S., Panter, M., Parsons, R. D., Pensec, U., Peron, G., Prokhorov, D. A., Pühlhofer, G., Punch, M., Quirrenbach, A., Regeard, M., Reimer, A., Reimer, O., Reis, I., Ren, H., Rieger, F., Rudak, B., Ruiz-Velasco, E., Sahakian, V., Salzmann, H., Santangelo, A., Sasaki, M., Schäfer, J., Schüssler, F., Schutte, H. M., Shapopi, J. N. S., Spencer, S., Stawarz, Ł., Steenkamp, R., Steinmassl, S., Steppa, C., Streil, K., Sushch, I., Takahashi, T., Tanaka, T., Taylor, A. M., Terrier, R., Thorpe-Morgan, C., Tluczykont, M., Unbehaun, T., van Eldik, C., van Soelen, B., Vecchi, M., Venter, C., Vink, J., Wach, T., Wagner, S. J., Werner, F., Wierzcholska, A., Zacharias, M., Zdziarski, A. A., Zech, A., and Żywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

PSR B1259-63 is a gamma-ray binary system that hosts a pulsar in an eccentric orbit, with a 3.4 year period, around an O9.5Ve star. At orbital phases close to periastron passages, the system radiates bright and variable non-thermal emission. We report on an extensive VHE observation campaign conducted with the High Energy Stereoscopic System, comprised of ~100 hours of data taken from $t_p-24$ days to $t_p+127$ days around the system's 2021 periastron passage. We also present the timing and spectral analyses of the source. The VHE light curve in 2021 is consistent with the stacked light curve of all previous observations. Within the light curve, we report a VHE maximum at times coincident with the third X-ray peak first detected in the 2021 X-ray light curve. In the light curve -- although sparsely sampled in this time period -- we see no VHE enhancement during the second disc crossing. In addition, we see no correspondence to the 2021 GeV flare in the VHE light curve. The VHE spectrum obtained from the analysis of the 2021 dataset is best described by a power law of spectral index $\Gamma = 2.65 \pm 0.04_{\text{stat}}$ $\pm 0.04_{\text{sys}}$, a value consistent with the previous H.E.S.S. observations of the source. We report spectral variability with a difference of $\Delta \Gamma = 0.56 ~\pm~ 0.18_{\text{stat}}$ $~\pm~0.10_{\text{sys}}$ at 95% c.l., between sub-periods of the 2021 dataset. We also find a linear correlation between contemporaneous flux values of X-ray and TeV datasets, detected mainly after $t_p+25$ days, suggesting a change in the available energy for non-thermal radiation processes. We detect no significant correlation between GeV and TeV flux points, within the uncertainties of the measurements, from $\sim t_p-23$ days to $\sim t_p+126$ days. This suggests that the GeV and TeV emission originate from different electron populations., Comment: accepted to A&A

Published
2024

56. Beyond Individual Facts: Investigating Categorical Knowledge Locality of Taxonomy and Meronomy Concepts in GPT Models

Author

Burger, Christopher, Hu, Yifan, and Le, Thai

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract

The location of knowledge within Generative Pre-trained Transformer (GPT)-like models has seen extensive recent investigation. However, much of the work is focused towards determining locations of individual facts, with the end goal being the editing of facts that are outdated, erroneous, or otherwise harmful, without the time and expense of retraining the entire model. In this work, we investigate a broader view of knowledge location, that of concepts or clusters of related information, instead of disparate individual facts. To do this, we first curate a novel dataset, called DARC, that includes a total of 34 concepts of ~120K factual statements divided into two types of hierarchical categories, namely taxonomy and meronomy. Next, we utilize existing causal mediation analysis methods developed for determining regions of importance for individual facts and apply them to a series of related categories to provide detailed investigation into whether concepts are associated with distinct regions within these models. We find that related categories exhibit similar areas of importance in contrast to less similar categories. However, fine-grained localization of individual category subsets to specific regions is not apparent., Comment: 27 pages, 23 figures, 12 tables

Published
2024

57. The Effect of Similarity Measures on Accurate Stability Estimates for Local Surrogate Models in Text-based Explainable AI

Author

Burger, Christopher, Walter, Charles, and Le, Thai

Subjects
Computer Science - Machine Learning, Computer Science - Cryptography and Security
Abstract

Recent work has investigated the vulnerability of local surrogate methods to adversarial perturbations on a machine learning (ML) model's inputs, where the explanation is manipulated while the meaning and structure of the original input remains similar under the complex model. Although weaknesses across many methods have been shown to exist, the reasons behind why remain little explored. Central to the concept of adversarial attacks on explainable AI (XAI) is the similarity measure used to calculate how one explanation differs from another. A poor choice of similarity measure can lead to erroneous conclusions on the efficacy of an XAI method. Too sensitive a measure results in exaggerated vulnerability, while too coarse understates its weakness. We investigate a variety of similarity measures designed for text-based ranked lists, including Kendall's Tau, Spearman's Footrule, and Rank-biased Overlap to determine how substantial changes in the type of measure or threshold of success affect the conclusions generated from common adversarial attack processes. Certain measures are found to be overly sensitive, resulting in erroneous estimates of stability., Comment: 11 pages, 8 Tables (Minor edits for clarity and grammar)

Published
2024

58. New ACV variables discovered in the Zwicky Transient Facility survey

Author

Bauer-Fasching, B., Bernhard, K., Brändli, E., Burger, H., Eisele, B., Hümmerich, S., Neuhold, J., Paunzen, E., Piecka, M., Ratzenböck, S., and Prišegen, M.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

The manifestation of surface spots on magnetic chemically peculiar (mCP) stars is most commonly explained by the atomic diffusion theory, which requires a calm stellar atmosphere and only moderate rotation. While very successful and well described, this theory still needs to be revised and fine-tuned to the observations. Our study aims to enlarge the sample of known photometrically variable mCP stars (ACV variables) to pave the way for more robust and significant statistical studies. We derive accurate physical parameters for these objects and discuss our results in the framework of the atomic diffusion theory. We studied 1314 candidate ACV variables that were selected from the Zwicky Transient Factory catalogue of periodic variables based on light curve characteristics. We investigated these objects using photometric criteria, a colour-magnitude diagram, and spectroscopic data from the LAMOST and Gaia missions to confirm their status as ACV variables. We present a sample of 1232 new ACV variables, including information on distance from the Sun, mass, fractional age on the main sequence, fraction of the radius between the zero-age and terminal-age main sequence, and the equatorial velocity and its ratio to the critical velocity. Our results confirm that the employed selection process is highly effcient for detecting ACV variables. We have identified 38 stars with v(equ) in excess of 150 km/s (with extreme values up to 260 km/s). This challenges current theories that cannot explain the occurrence of such fast-rotating mCP stars., Comment: 11 pages, 4 figures, accepted for Astronomy & Astrophysics

Published
2024

59. Adversarial flows: A gradient flow characterization of adversarial attacks

Author

Weigand, Lukas, Roith, Tim, and Burger, Martin

Subjects
Computer Science - Machine Learning, Mathematics - Analysis of PDEs, 49Q20, 34A60, 68Q32, 65K15
Abstract

A popular method to perform adversarial attacks on neuronal networks is the so-called fast gradient sign method and its iterative variant. In this paper, we interpret this method as an explicit Euler discretization of a differential inclusion, where we also show convergence of the discretization to the associated gradient flow. To do so, we consider the concept of p-curves of maximal slope in the case $p=\infty$. We prove existence of $\infty$-curves of maximum slope and derive an alternative characterization via differential inclusions. Furthermore, we also consider Wasserstein gradient flows for potential energies, where we show that curves in the Wasserstein space can be characterized by a representing measure on the space of curves in the underlying Banach space, which fulfill the differential inclusion. The application of our theory to the finite-dimensional setting is twofold: On the one hand, we show that a whole class of normalized gradient descent methods (in particular signed gradient descent) converge, up to subsequences, to the flow, when sending the step size to zero. On the other hand, in the distributional setting, we show that the inner optimization task of adversarial training objective can be characterized via $\infty$-curves of maximum slope on an appropriate optimal transport space.

Published
2024

60. Cosmological parameters from the joint analysis of Density Split and Second Order Statistics: an Emulator based on the Halo Occupation Distribution

Author

Burger, Pierre A., Paillas, Enrique, and Hudson, Michael J.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

In this work, we develop a simulation-based model to predict the density split (DSS) and second-order shear and clustering statistics. A simulation-based model has the potential to model highly non-linear scales where current DSS models fail. To build this model, we use the $\texttt{AbacusSummit}$ N-body simulation suite from which we measure all necessary statistics and train an emulator based on $\texttt{CosmoPower}$. In that context, we discuss possible improvements for future emulators to make the measurement less noisy and biased, resulting in more accurate and precise model predictions. Regarding the emulator's accuracy, we find that the most important aspect is the average of the summary statistics over multiple-shot noise realizations of the foreground galaxies. However, these results probably depend on the chosen number density of the foreground galaxies. Regarding the parameter forecast based on preliminary LOWZxUNIONS data, we find that DSS has more constraining power to derive cosmological parameters and that the joint analysis with second-order statistics is particularly useful for extracting parameters of the galaxy-halo connection., Comment: 16 pages, 16 Figures, accepted at physical review D

Published
2024
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62. Multi-modal dataset creation for federated learning with DICOM-structured reports

Author

Tölle, Malte, Burger, Lukas, Kelm, Halvar, André, Florian, Bannas, Peter, Diller, Gerhard, Frey, Norbert, Garthe, Philipp, Groß, Stefan, Hennemuth, Anja, Kaderali, Lars, Krüger, Nina, Leha, Andreas, Martin, Simon, Meyer, Alexander, Nagel, Eike, Orwat, Stefan, Scherer, Clemens, Seiffert, Moritz, Seliger, Jan Moritz, Simm, Stefan, Friede, Tim, Seidler, Tim, and Engelhardt, Sandy

Published
2025
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66. Bispectral Index Alterations and Associations With Autonomic Changes During Hypnosis in Trauma Center Researchers: Formative Evaluation Study

Author

Dunham, C Michael, Burger, Amanda J, Hileman, Barbara M, Chance, Elisha A, and Hutchinson, Amy E

Subjects
Medicine
Abstract

BackgroundPrevious work performed by our group demonstrated that intermittent reductions in bispectral index (BIS) values were found during neurofeedback following mindfulness instructions. Hypnosis was induced to enhance reductions in BIS values. ObjectiveThis study aims to assess physiologic relaxation and explore its associations with BIS values using autonomic monitoring. MethodsEach session consisted of reading a 4-minute baseline neutral script and playing an 18-minute hypnosis tape to 3 researchers involved in the BIS neurofeedback study. In addition to BIS monitoring, autonomic monitoring was performed, and this included measures of electromyography (EMG), skin temperature, skin conductance, respiratory rate, expired carbon dioxide, and heart rate variability. The resulting data were analyzed using two-tailed t tests, correlation analyses, and multivariate linear regression analyses. ResultsWe found that hypnosis was associated with reductions in BIS (P

Published
2021
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73. De jonge zwangerschap

Author

Burger, N. B., van der Hoorn, M. L. P., Haak, Monique, editor, Bekker, Mireille, editor, Engels, Melanie, editor, and Huirne, Judith, editor

Published
2025
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75. Wavefront Threading Enables Effective High-Level Synthesis

Author

Pelton, Blake, Sapek, Adam, Eguro, Ken, Lo, Daniel, Forin, Alessandro, Humphrey, Matt, Xi, Jinwen, Cox, David, Karandikar, Rajas, Licht, Johannes de Fine, Babin, Evgeny, Caulfield, Adrian, and Burger, Doug

Subjects
Computer Science - Programming Languages
Abstract

Digital systems are growing in importance and computing hardware is growing more heterogeneous. Hardware design, however, remains laborious and expensive, in part due to the limitations of conventional hardware description languages (HDLs) like VHDL and Verilog. A longstanding research goal has been programming hardware like software, with high-level languages that can generate efficient hardware designs. This paper describes Kanagawa, a language that takes a new approach to combine the programmer productivity benefits of traditional High-Level Synthesis (HLS) approaches with the expressibility and hardware efficiency of Register-Transfer Level (RTL) design. The language's concise syntax, matched with a hardware design-friendly execution model, permits a relatively simple toolchain to map high-level code into efficient hardware implementations., Comment: Accepted to PLDI'24

Published
2024
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76. Analysis of Primal-Dual Langevin Algorithms

Author

Burger, Martin, Ehrhardt, Matthias J., Kuger, Lorenz, and Weigand, Lukas

Subjects
Mathematics - Optimization and Control, 35Q84, 47A52, 49N45, 60H10, 62F15, 65J22, 68U10
Abstract

We analyze a recently proposed class of algorithms for the problem of sampling from probability distributions $\mu^\ast$ in $\mathbb{R}^d$ with a Lebesgue density of the form $\mu^\ast(x) \propto \exp(-f(Kx)-g(x))$, where $K$ is a linear operator and $f,g$ convex and non-smooth. The method is a generalization of the primal-dual hybrid gradient optimization algorithm to a sampling scheme. We give the iteration's continuous time limit, a stochastic differential equation in the joint primal-dual variable, and its mean field limit Fokker-Planck equation. Under mild conditions, the scheme converges to a unique stationary state in continuous and discrete time. Contrary to purely primal overdamped Langevin diffusion, the stationary state in continuous time does not have $\mu^\ast$ as its primal marginal. Thus, further analysis is carried out to bound the bias induced by the partial dualization, and potentially correct for it in the diffusion. Time discretizations of the diffusion lead to implementable algorithms, but, as is typical in Langevin Monte Carlo methods, introduce further bias. We prove bounds for these discretization errors, which allow to give convergence results relating the produced samples to the target. We demonstrate our findings numerically first on small-scale examples in which we can exactly verify the theoretical results, and subsequently on typical examples of larger scale from Bayesian imaging inverse problems.

Published
2024

77. Thermalization and Criticality on an Analog-Digital Quantum Simulator

Author

Andersen, Trond I., Astrakhantsev, Nikita, Karamlou, Amir H., Berndtsson, Julia, Motruk, Johannes, Szasz, Aaron, Gross, Jonathan A., Schuckert, Alexander, Westerhout, Tom, Zhang, Yaxing, Forati, Ebrahim, Rossi, Dario, Kobrin, Bryce, Di Paolo, Agustin, Klots, Andrey R., Drozdov, Ilya, Kurilovich, Vladislav D., Petukhov, Andre, Ioffe, Lev B., Elben, Andreas, Rath, Aniket, Vitale, Vittorio, Vermersch, Benoit, Acharya, Rajeev, Beni, Laleh Aghababaie, Anderson, Kyle, Ansmann, Markus, Arute, Frank, Arya, Kunal, Asfaw, Abraham, Atalaya, Juan, Ballard, Brian, Bardin, Joseph C., Bengtsson, Andreas, Bilmes, Alexander, Bortoli, Gina, Bourassa, Alexandre, Bovaird, Jenna, Brill, Leon, Broughton, Michael, Browne, David A., Buchea, Brett, Buckley, Bob B., Buell, David A., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Cabrera, Anthony, Campero, Juan, Chang, Hung-Shen, Chen, Zijun, Chiaro, Ben, Claes, Jahan, Cleland, Agnetta Y., Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Das, Sayan, Debroy, Dripto M., De Lorenzo, Laura, Barba, Alexander Del Toro, Demura, Sean, Donohoe, Paul, Dunsworth, Andrew, Earle, Clint, Eickbusch, Alec, Elbag, Aviv Moshe, Elzouka, Mahmoud, Erickson, Catherine, Faoro, Lara, Fatemi, Reza, Ferreira, Vinicius S., Burgos, Leslie Flores, Fowler, Austin G., Foxen, Brooks, Ganjam, Suhas, Gasca, Robert, Giang, William, Gidney, Craig, Gilboa, Dar, Giustina, Marissa, Gosula, Raja, Dau, Alejandro Grajales, Graumann, Dietrich, Greene, Alex, Habegger, Steve, Hamilton, Michael C., Hansen, Monica, Harrigan, Matthew P., Harrington, Sean D., Heslin, Stephen, Heu, Paula, Hill, Gordon, Hoffmann, Markus R., Huang, Hsin-Yuan, Huang, Trent, Huff, Ashley, Huggins, William J., Isakov, Sergei V., Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Jordan, Stephen, Joshi, Chaitali, Juhas, Pavol, Kafri, Dvir, Kang, Hui, Kechedzhi, Kostyantyn, Khaire, Trupti, Khattar, Tanuj, Khezri, Mostafa, Kieferová, Mária, Kim, Seon, Kitaev, Alexei, Klimov, Paul V., Korotkov, Alexander N., Kostritsa, Fedor, Kreikebaum, John Mark, Landhuis, David, Langley, Brandon W., Laptev, Pavel, Lau, Kim-Ming, Guevel, Loïck Le, Ledford, Justin, Lee, Joonho, Lee, Kenny, Lensky, Yuri D., Lester, Brian J., Li, Wing Yan, Lill, Alexander T., Liu, Wayne, Livingston, William P., Locharla, Aditya, Lundahl, Daniel, Lunt, Aaron, Madhuk, Sid, Maloney, Ashley, Mandrà, Salvatore, Martin, Leigh S., Martin, Orion, Martin, Steven, Maxfield, Cameron, McClean, Jarrod R., McEwen, Matt, Meeks, Seneca, Miao, Kevin C., Mieszala, Amanda, Molina, Sebastian, Montazeri, Shirin, Morvan, Alexis, Movassagh, Ramis, Neill, Charles, Nersisyan, Ani, Newman, Michael, Nguyen, Anthony, Nguyen, Murray, Ni, Chia-Hung, Niu, Murphy Yuezhen, Oliver, William D., Ottosson, Kristoffer, Pizzuto, Alex, Potter, Rebecca, Pritchard, Orion, Pryadko, Leonid P., Quintana, Chris, Reagor, Matthew J., Rhodes, David M., Roberts, Gabrielle, Rocque, Charles, Rosenberg, Eliott, Rubin, Nicholas C., Saei, Negar, Sankaragomathi, Kannan, Satzinger, Kevin J., Schurkus, Henry F., Schuster, Christopher, Shearn, Michael J., Shorter, Aaron, Shutty, Noah, Shvarts, Vladimir, Sivak, Volodymyr, Skruzny, Jindra, Small, Spencer, Smith, W. Clarke, Springer, Sofia, Sterling, George, Suchard, Jordan, Szalay, Marco, Sztein, Alex, Thor, Douglas, Torres, Alfredo, Torunbalci, M. Mert, Vaishnav, Abeer, Vdovichev, Sergey, Villalonga, Benjamin, Heidweiller, Catherine Vollgraff, Waltman, Steven, Wang, Shannon X., White, Theodore, Wong, Kristi, Woo, Bryan W., Xing, Cheng, Yao, Z. Jamie, Yeh, Ping, Ying, Bicheng, Yoo, Juhwan, Yosri, Noureldin, Young, Grayson, Zalcman, Adam, Zhu, Ningfeng, Zobrist, Nicholas, Neven, Hartmut, Babbush, Ryan, Boixo, Sergio, Hilton, Jeremy, Lucero, Erik, Megrant, Anthony, Kelly, Julian, Chen, Yu, Smelyanskiy, Vadim, Vidal, Guifre, Roushan, Pedram, Lauchli, Andreas M., Abanin, Dmitry A., and Mi, Xiao

Subjects
Quantum Physics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Strongly Correlated Electrons
Abstract

Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators. Unlocking the full potential of such systems toward this goal requires flexible initial state preparation, precise time evolution, and extensive probes for final state characterization. We present a quantum simulator comprising 69 superconducting qubits which supports both universal quantum gates and high-fidelity analog evolution, with performance beyond the reach of classical simulation in cross-entropy benchmarking experiments. Emulating a two-dimensional (2D) XY quantum magnet, we leverage a wide range of measurement techniques to study quantum states after ramps from an antiferromagnetic initial state. We observe signatures of the classical Kosterlitz-Thouless phase transition, as well as strong deviations from Kibble-Zurek scaling predictions attributed to the interplay between quantum and classical coarsening of the correlated domains. This interpretation is corroborated by injecting variable energy density into the initial state, which enables studying the effects of the eigenstate thermalization hypothesis (ETH) in targeted parts of the eigenspectrum. Finally, we digitally prepare the system in pairwise-entangled dimer states and image the transport of energy and vorticity during thermalization. These results establish the efficacy of superconducting analog-digital quantum processors for preparing states across many-body spectra and unveiling their thermalization dynamics.

Published
2024

78. Euclid. I. Overview of the Euclid mission

Author

Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. 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R., Granvik, M., Grazian, A., Gregorio, A., Grenet, C., Grillo, C., Grupp, F., Gruppioni, C., Gruppuso, A., Guerbuez, C., Guerrini, S., Guidi, M., Guillard, P., Gutierrez, C. M., Guttridge, P., Guzzo, L., Gwyn, S., Haapala, J., Haase, J., Haddow, C. R., Hailey, M., Hall, A., Hall, D., Hamaus, N., Haridasu, B. S., Harnois-Déraps, J., Harper, C., Hartley, W. G., Hasinger, G., Hassani, F., Hatch, N. A., Haugan, S. V. H., Häußler, B., Heavens, A., Heisenberg, L., Helmi, A., Helou, G., Hemmati, S., Henares, K., Herent, O., Hernández-Monteagudo, C., Heuberger, T., Hewett, P. C., Heydenreich, S., Hildebrandt, H., Hirschmann, M., Hjorth, J., Hoar, J., Hoekstra, H., Holland, A. D., Holliman, M. S., Holmes, W., Hook, I., Horeau, B., Hormuth, F., Hornstrup, A., Hosseini, S., Hu, D., Hudelot, P., Hudson, M. J., Huertas-Company, M., Huff, E. M., Hughes, A. C. N., Humphrey, A., Hunt, L. K., Huynh, D. D., Ibata, R., Ichikawa, K., Iglesias-Groth, S., Ilbert, O., Ilić, S., Ingoglia, L., Iodice, E., Israel, H., Israelsson, U. E., Izzo, L., Jablonka, P., Jackson, N., Jacobson, J., Jafariyazani, M., Jahnke, K., Jain, B., Jansen, H., Jarvis, M. J., Jasche, J., Jauzac, M., Jeffrey, N., Jhabvala, M., Jimenez-Teja, Y., Muñoz, A. Jimenez, Joachimi, B., Johansson, P. H., Joudaki, S., Jullo, E., Kajava, J. J. E., Kang, Y., Kannawadi, A., Kansal, V., Karagiannis, D., Kärcher, M., Kashlinsky, A., Kazandjian, M. V., Keck, F., Keihänen, E., Kerins, E., Kermiche, S., Khalil, A., Kiessling, A., Kiiveri, K., Kilbinger, M., Kim, J., King, R., Kirkpatrick, C. C., Kitching, T., Kluge, M., Knabenhans, M., Knapen, J. H., Knebe, A., Kneib, J. -P., Kohley, R., Koopmans, L. V. E., Koskinen, H., Koulouridis, E., Kou, R., Kovács, A., Kovačić, I., Kowalczyk, A., Koyama, K., Kraljic, K., Krause, O., Kruk, S., Kubik, B., Kuchner, U., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lacey, C. G., La Franca, F., Lagarde, N., Lahav, O., Laigle, C., La Marca, A., La Marle, O., Lamine, B., Lam, M. C., Lançon, A., Landt, H., Langer, M., Lapi, A., Larcheveque, C., Larsen, S. S., Lattanzi, M., Laudisio, F., Laugier, D., Laureijs, R., Laurent, V., Lavaux, G., Lawrenson, A., Lazanu, A., Lazeyras, T., Boulc'h, Q. Le, Brun, A. M. C. Le, Brun, V. Le, Leclercq, F., Lee, S., Graet, J. Le, Legrand, L., Leirvik, K. N., Jeune, M. Le, Lembo, M., Mignant, D. Le, Lepinzan, M. D., Lepori, F., Reun, A. Le, Leroy, G., Lesci, G. F., Lesgourgues, J., Leuzzi, L., Levi, M. E., Liaudat, T. I., Libet, G., Liebing, P., Ligori, S., Lilje, P. B., Lin, C. -C., Linde, D., Linder, E., Lindholm, V., Linke, L., Li, S. -S., Liu, S. J., Lloro, I., Lobo, F. S. N., Lodieu, N., Lombardi, M., Lombriser, L., Lonare, P., Longo, G., López-Caniego, M., Lopez, X. Lopez, Alvarez, J. Lorenzo, Loureiro, A., Loveday, J., Lusso, E., Macias-Perez, J., Maciaszek, T., Maggio, G., Magliocchetti, M., Magnard, F., Magnier, E. 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W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

Published
2024

79. Orbital angular momentum enhanced laser absorption and neutron generation

Author

Peskosky, Nicholas, Ernst, Nicholas, Burger, Miloš, Murphy, Jon, Nees, John A., Jovanovic, Igor, Thomas, Alec G. R., and Krushelnick, Karl

Subjects
Physics - Plasma Physics
Abstract

We experimentally demonstrate enhanced absorption of near relativistic optical vortex beams in $\mathrm{D_2O}$ plasmas to generate a record fast-neutron yield of $1.45 \times 10^6$ n/s/sr. Beams with a topological charge of 5 were shown to deliver up to a 3.3 times enhancement of fast-neutron yield over a Gaussian focused beam of the same energy but having two orders of magnitude higher intensity. This result was achieved with laser energies of 16 mJ and a pulse duration of 67 fs. The Orbital Angular Momentum (OAM) beam-target interactions in our experiment were also investigated through Particle-in-Cell (PIC) simulations. Electron density rippling resulting in enhanced plasma wave excitation on the critical surface and significantly enhanced resonance absorption is observed., Comment: 7 pages, 4 figures

Published
2024

80. KiDS-1000 and DES-Y1 combined: Cosmology from peak count statistics

Author

Harnois-Deraps, Joachim, Heydenreich, Sven, Giblin, Benjamin, Martinet, Nicolas, Troester, Tilman, Asgari, Marika, Burger, Pierre, Castro, Tiago, Dolag, Klaus, Heymans, Catherine, Hildebrandt, Hendrik, Joachimi, Benjamin, and Wright, Angus H.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We analyse the fourth data release of the Kilo Degree Survey (KiDS-1000) and extract cosmological parameter constraints based on the cosmic shear peak count statistics. Peaks are identified in aperture mass maps in which the filter is maximally sensitive to angular scales in the range 2-4arcmin, probing deep into the non-linear regime of structure formation. We interpret our results with a simulation-based inference pipeline, sampling over a broad $w$CDM prior volume and marginalising over uncertainties on shape calibration, photometric redshift distribution, intrinsic alignment and baryonic feedback. Our measurements constrain the structure growth parameter and the amplitude of the non-linear intrinsic alignment model to $\Sigma_8 \equiv \sigma_8\left[\Omega_{\rm m}/0.3\right]^{0.60}=0.765^{+0.030}_{-0.030}$ and $A_{\rm IA}= 0.71^{+0.42}_{-0.42}$, respectively, in agreement with previous KiDS-1000 results based on two-point shear statistics. These results are robust against modelling of the non-linear physics, different scale cuts and selections of tomographic bins. The posterior is also consistent with that from the Dark Energy Survey Year-1 peak count analysis presented in Harnois-D\'eraps et al (2021), and hence we jointly analyse both surveys. We obtain $\Sigma_8^{\rm joint} \equiv \sigma_8\left[\Omega_{\rm m}/0.3\right]^{0.57}=0.759^{+0.020}_{-0.017}$, in agreement with the Planck $w$CDM results. The shear-CMB tension on this parameter increases to $3.1\sigma$ when forcing $w=-1.0$, and to $4.1\sigma$ if comparing instead with $S_{8,\Lambda{\rm CDM}}^{\rm joint} = 0.736^{+0.016}_{-0.018}$, one of the tightest constraints to date on this quantity. (abridged), Comment: 26 pages, 20 figures. MNRAS Accepted version

Published
2024

81. A Gauss-Newton Method for ODE Optimal Tracking Control

Author

Holfeld, Vicky, Burger, Michael, and Schillings, Claudia

Subjects
Mathematics - Optimization and Control
Abstract

This paper introduces and analyses a continuous optimization approach to solve optimal control problems involving ordinary differential equations (ODEs) and tracking type objectives. Our aim is to determine control or input functions, and potentially uncertain model parameters, for a dynamical system described by an ODE. We establish the mathematical framework and define the optimal control problem with a tracking functional, incorporating regularization terms and box-constraints for model parameters and input functions. Treating the problem as an infinite-dimensional optimization problem, we employ a Gauss-Newton method within a suitable function space framework. This leads to an iterative process where, at each step, we solve a linearization of the problem by considering a linear surrogate model around the current solution estimate. The resulting linear auxiliary problem resembles a linear-quadratic ODE optimal tracking control problem, which we tackle using either a gradient descent method in function spaces or a Riccati-based approach. Finally, we present and analyze the efficacy of our method through numerical experiments.

Published
2024

82. Hypergraph $p$-Laplacian regularization on point clouds for data interpolation

Author

Shi, Kehan and Burger, Martin

Subjects
Mathematics - Numerical Analysis, Computer Science - Machine Learning, Mathematics - Analysis of PDEs, 49J55, 35J20, 65N12
Abstract

As a generalization of graphs, hypergraphs are widely used to model higher-order relations in data. This paper explores the benefit of the hypergraph structure for the interpolation of point cloud data that contain no explicit structural information. We define the $\varepsilon_n$-ball hypergraph and the $k_n$-nearest neighbor hypergraph on a point cloud and study the $p$-Laplacian regularization on the hypergraphs. We prove the variational consistency between the hypergraph $p$-Laplacian regularization and the continuum $p$-Laplacian regularization in a semisupervised setting when the number of points $n$ goes to infinity while the number of labeled points remains fixed. A key improvement compared to the graph case is that the results rely on weaker assumptions on the upper bound of $\varepsilon_n$ and $k_n$. To solve the convex but non-differentiable large-scale optimization problem, we utilize the stochastic primal-dual hybrid gradient algorithm. Numerical experiments on data interpolation verify that the hypergraph $p$-Laplacian regularization outperforms the graph $p$-Laplacian regularization in preventing the development of spikes at the labeled points., Comment: 33 pages

Published
2024

83. Optimal transport on gas networks

Author

Fazeny, Ariane, Burger, Martin, and Pietschmann, Jan-Frederik

Subjects
Mathematics - Analysis of PDEs, Mathematics - Optimization and Control, 49Q22, 35R02, 76N25 (Primary) 35Q35, 60B05 (Secondary)
Abstract

This paper models gas networks as metric graphs, with isothermal Euler equations at the edges, Kirchhoff's law at interior vertices and time-(in)dependent boundary conditions at boundary vertices. For this setup, a generalized $p$-Wasserstein metric in a dynamic formulation is introduced and utilized to derive $p$-Wasserstein gradient flows, specifically focusing on the non-standard case $p = 3$., Comment: 43 pages, 5 figures, submitted to EJAM (Evolution Equations on Graphs: Analysis and Applications)

Published
2024

84. Continuum limit of $p$-biharmonic equations on graphs

Author

Shi, Kehan and Burger, Martin

Subjects
Mathematics - Analysis of PDEs, Computer Science - Machine Learning, Mathematics - Numerical Analysis, 35R02, 35J30, 65N12
Abstract

This paper studies the $p$-biharmonic equation on graphs, which arises in point cloud processing and can be interpreted as a natural extension of the graph $p$-Laplacian from the perspective of hypergraph. The asymptotic behavior of the solution is investigated when the random geometric graph is considered and the number of data points goes to infinity. We show that the continuum limit is an appropriately weighted $p$-biharmonic equation with homogeneous Neumann boundary conditions. The result relies on the uniform $L^p$ estimates for solutions and gradients of nonlocal and graph Poisson equations. The $L^\infty$ estimates of solutions are also obtained as a byproduct., Comment: 20 pages

Published
2024

85. Bayesian optimization for state engineering of quantum gases

Author

Müller, Gabriel, Martínez-Lahuerta, V. J., Sekulic, Ivan, Burger, Sven, Schneider, Philipp-Immanuel, and Gaaloul, Naceur

Subjects
Quantum Physics, Physics - Computational Physics
Abstract

State engineering of quantum objects is a central requirement in most implementations. In the cases where the quantum dynamics can be described by analytical solutions or simple approximation models, optimal state preparation protocols have been theoretically proposed and experimentally realized. For more complex systems, however, such as multi-component quantum gases, simplifying assumptions do not apply anymore and the optimization techniques become computationally impractical. Here, we propose Bayesian optimization based on multi-output Gaussian processes to learn the quantum state's physical properties from few simulations only. We evaluate its performance on an optimization study case of diabatically transporting a Bose-Einstein condensate while keeping it in its ground state, and show that within only few hundreds of executions of the underlying physics simulation, we reach a competitive performance with other protocols. While restricting this benchmarking to well known approximations for straightforward comparisons, we expect a similar performance when employing more involving models, which are computationally more challenging. This paves the way to efficient state engineering of complex quantum systems., Comment: 12 pages, 5 figures

Published
2024
Full Text
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86. Broadband Multi-wavelength Properties of M87 during the 2018 EHT Campaign including a Very High Energy Flaring Episode

Author

Algaba, J. C., Balokovic, M., Chandra, S., Cheong, W. Y., Cui, Y. Z., D'Ammando, F., Falcone, A. D., Ford, N. M., Giroletti, M., Goddi, C., Gurwell, M. A., Hada, K., Haggard, D., Jorstad, S., Kaur, A., Kawashima, T., Kerby, S., Kim, J. Y., Kino, M., Kravchenko, E. V., Lee, S. S., Lu, R. S., Markoff, S., Michail, J., Neilsen, J., Nowak, M. A., Principe, G., Ramakrishnan, V., Ripperda, B., Sasada, M., Savchenko, S. S., Sheridan, C., Akiyama, K., Alberdi, A., Alef, W., Anantua, R., Asada, K., Azulay, R., Bach, U., Baczko, A. -K., Ball, D., Bandyopadhyay, B., Barrett, J., Bauböck, M., Benson, B. A., Bintley, D., Blackburn, L., Blundell, R., Bouman, K. L., Bower, G. C., Boyce, H., Bremer, M., Brissenden, R., Britzen, S., Broderick, A. E., Broguiere, D., Bronzwaer, T., Bustamante, S., Carlstrom, J. E., Chael, A., Chan, C. -K., Chang, D. O., Chatterjee, K., Chatterjee, S., Chen, M. -T., Chen, Y., Cheng, X., Cho, I., Christian, P., Conroy, N. S., Conway, J. E., Crawford, T. M., Crew, G. B., Cruz-Osorio, A., Dahale, R., Davelaar, J., De Laurentis, M., Deane, R., Dempsey, J., Desvignes, G., Dexter, J., Dhruv, V., Dihingia, I. K., Doeleman, S. S., Dzib, S. A., Eatough, R. P., Emami, R., Falcke, H., Farah, J., Fish, V. L., Fomalont, E., Ford, H. A., Foschi, M., Fraga-Encinas, R., Freeman, W. T., Friberg, P., Fromm, C. M., Fuentes, A., Galison, P., Gammie, C. F., García, R., Gentaz, O., Georgiev, B., Gold, R., Gómez-Ruiz, A. I., Gómez, J. L., Gu, M., Hesper, R., Heumann, D., Ho, L. C., Ho, P., Honma, M., Huang, C. -W. L., Huang, L., Hughes, D. H., Ikeda, S., Impellizzeri, C. M. V., Inoue, M., Issaoun, S., James, D. J., Jannuzi, B. T., Janssen, M., Jeter, B., Jiang, W., Jiménez-Rosales, A., Johnson, M. D., Jones, A. C., Joshi, A. V., Jung, T., Karuppusamy, R., Keating, G. K., Kettenis, M., Kim, D. -J., Kim, J., Koay, J. Y., Kocherlakota, P., Kofuji, Y., Koch, P. M., Koyama, S., Kramer, C., Kramer, J. A., Kramer, M., Krichbaum, T. P., Kuo, C. -Y., La Bella, N., Levis, A., Li, Z., Lico, R., Lindahl, G., Lindqvist, M., Lisakov, M., Liu, J., Liu, K., Liuzzo, E., Lo, W. -P., Lobanov, A. P., Loinard, L., Lonsdale, C. J., Lowitz, A. E., MacDonald, N. R., Mao, J., Marchili, N., Marrone, D. P., Marscher, A. P., Martí-Vidal, I., Matsushita, S., Matthews, L. D., Medeiros, L., Menten, K. M., Mizuno, I., Mizuno, Y., Montgomery, J., Moran, J. M., Moriyama, K., Moscibrodzka, M., Mulaudzi, W., Müller, C., Müller, H., Mus, A., Musoke, G., Myserlis, I., Nagai, H., Nagar, N. M., Nair, D. G., Nakamura, M., Narayanan, G., Natarajan, I., Nathanail, A., Fuentes, S. Navarro, Ni, C., Oh, J., Okino, H., Olivares, H., Oyama, T., Özel, F., Palumbo, D. C. M., Paraschos, G. Filippos, Park, J., Parsons, H., Patel, N., Pen, U. -L., Pesce, D. W., Piétu, V., PopStefanija, A., Porth, O., Prather, B., Psaltis, D., Pu, H. -Y., Rao, R., Rawlings, M. G., Raymond, A. W., Rezzolla, L., Ricarte, A., Roelofs, F., Romero-Cañizales, C., Ros, E., Roshanineshat, A., Rottmann, H., Roy, A. L., Ruiz, I., Ruszczyk, C., Rygl, K. L. J., Sánchez, S., Sánchez-Argüelles, D., Sánchez-Portal, M., Satapathy, K., Savolainen, T., Schloerb, F. P., Schonfeld, J., Schuster, K. -F., Shao, L., Shen, Z., Small, D., Sohn, B. W., SooHoo, J., Salas, L. D. Sosapanta, Souccar, K., Stanway, J. S., Sun, H., Tazaki, F., Tetarenko, A. J., Tiede, P., Tilanus, R. P. J., Titus, M., Toma, K., Torne, P., Toscano, T., Traianou, E., Trent, T., Trippe, S., Turk, M., van Bemmel, I., van Langevelde, H. J., van Rossum, D. R., Vos, J., Wagner, J., Ward-Thompson, D., Wardle, J., Washington, J. E., Weintroub, J., Wharton, R., Wielgus, M., Wiik, K., Witzel, G., Wondrak, M. F., Wong, G. N., Wu, Q., Yadlapalli, N., Yamaguchi, P., Yfantis, A., Yoon, D., Young, A., Younsi, Z., Yu, W., Yuan, F., Yuan, Y. -F., Zensus, J. A., Zhang, S., Zhao, G. -Y., Zhao, S. -S., Bellazzini, R., Berenji, B., Bissaldi, E., Blandford, R. D., Bonino, R., Bruel, P., Cameron, R. A., Caraveo, P. A., Cavazzuti, E., Cheung, C. C., Ciprini, S., Orestano, P. Cristarella, Cutini, S., Di Lalla, N., Dinesh, A., Di Venere, L., Domínguez, A., Fegan, S. J., Franckowiak, A., Fukazawa, Y., Fusco, P., Gargano, F., Gasbarra, C., Germani, S., Giliberti, M., Grenier, I. A., Hays, E., Horan, D., Kuss, M., Larsson, S., Liodakis, I., Longo, F., Loparco, F., Lovellette, M. N., Maldera, S., Mazziotta, M. N., Mereu, I., Michelson, P. F., Mirabal, N., Mizuno, T., Monzani, M. E., Morselli, A., Negro, M., Omodei, N., Orlando, E., Persic, M., Rainò, S., Rani, B., Reimer, A., Reimer, O., Sánchez-Conde, M., Parkinson, P. M. Saz, Sgrò, C., Siskind, E. J., Spinelli, P., Suson, D. J., Tajima, H., Torres, D. F., Zaharijas, G., Aharonian, F., Benkhali, F. Ait, Aschersleben, J., Ashkar, H., Backes, M., Martins, V. Barbosa, Batzofin, R., Becherini, Y., Berge, D., Böttcher, M., Boisson, C., Bolmont, J., de Lavergne, M. de Bony, Borowska, J., Bouyahiaoui, M., Bradascio, F., Brose, R., Brown, A., Bruno, B., Bulik, T., Burger-Scheidlin, C., Casanova, S., Cecil, R., Celic, J., Cerruti, M., Chand, T., Chen, A., Chibueze, J., Chibueze, O., Czerny, T., Dainotti, M., Dubus, F., Dumm, J., D'Urso, G., Drouhin, A., Durouchoux, P., Fabbian, D., Franczak, D., Funk, M., Gabanyi, J., Gaggero, G., Garcia, N., Geiger, A., Giorgi, M. G., Gleeson, S., Gonzalez, S., Gauthier, G. T., Grasso, P., Hovatta, T., Hyman, J., Kaaret, C., Kirk, D., Lal, S., Lesch, T. M., Lohmann, K., Massaro, C., Mayer, M., Meintjes, P. J., Miral, E., Mirra, A., Neronov, J., Padovani, E., Paccagnella, F., Parisi, E., Piotrowska, A., Pohl, S., Puga, G., Ramirez, L. R., Reville, S., Rowell, D. S., Rudge, M., Rybka, G., Schlenstedt, M. S., Seo, E. S., Svirski, J., Taylor, J. R., Torres, F., Tsujimoto, K., Tosti, F., Volpi, S., Walraven, N. A., Welker, L., Zietkiewicz, M., Abdalla, G., Aleva, C., Benkhali, H. A. Ait, Aldous, M., Amin, M., Aschieri, M. A., de Deus, E., Santos, J. de Los, Fontanot, D., Jorfi, S., Levens, P., Zwart, A. E. E., Oliviero, S., Puglisi, D., Thiel, M., Zaharijas, C., Amaral, F., Boella, L., Holincheck, L., Queiroz, R., Sofue, H., Tellis, G., Wagner, G., Wierzcholska, A., Zacharias, M., Zdziarski, A. A., Zech, A., Zywucka, N., Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Babic, A., de Almeida, U. Barres, Barrio, J. A., Batkovic, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bosnjak, Z., Bronzini, E., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Elsaesser, D., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Laínez, M., Lamastra, A., Leone, F., Lindfors, E., Lombardi, S., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolic, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Priyadarshi, C., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Spolon, A., Stamerra, A., Strišković, J., Strom, D., Strzys, M., Suda, Y., Suutarinen, S., Takahashi, M., Takeishi, R., Tavecchio, F., Temnikov, P., Terauchi, K., Terzic, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Verna, G., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Will, M., Wunderlich, C., Yamamoto, T., Acharyya, A., Adams, C. B., Bangale, P., Bartkoske, J. T., Benbow, W., Christiansen, J. L., Duerr, A., Errando, M., Feng, Q., Foote, G. M., Fortson, L., Furniss, A., Hanlon, W., Hervet, O., Hinrichs, C. E., Holder, J., Humensky, T. B., Jin, W., Johnson, M. N., Kaaret, P., Kertzman, M., Kieda, D., Kleiner, T. K., Korzoun, N., Krennrich, F., Kumar, S., Lang, M. J., Lundy, M., Maier, G., McGrath, C. E., Millard, M. J., Mooney, C. L., Moriarty, P., Mukherjee, R., Ning, W., O'Brien, S., Ong, R. A., Pohl, M., Pueschel, E., Quinn, J., Ragan, K., Reynolds, P. T., Ribeiro, D., Roache, E., Ryan, J. L., Sadeh, I., Saha, L., Santander, M., Sembroski, G. H., Shang, R., Splettstoesser, M., Talluri, A. K., Tucci, J. V., Valverde, J., Vassiliev, V. V., Williams, D. A., Wong, S. L., Chen, Z., Cui, L., Hirota, T., Li, B., Li, G., Liu, Q., Liu, X., Liu, Z., Ma, J., Niinuma, K., Ro, H., Sakai, N., Sawada-Satoh, S., Wajima, K., Wang, J., Wang, N., Xia, B., Yan, H., Yonekura, Y., Zhang, H., Zhao, R., Zhong, W., group, The Event Horizon Telescope - Multi-wavelength science working, Collaboration, The Event Horizon Telescope, Collaboration, The Fermi Large Area Telescope, Collaboration, H. E. S. S., Collaboration, MAGIC, Collaboration, VERITAS, and Collaboration, EAVN

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies
Abstract

The nearby elliptical galaxy M87 contains one of the only two supermassive black holes whose emission surrounding the event horizon has been imaged by the Event Horizon Telescope (EHT). In 2018, more than two dozen multi-wavelength (MWL) facilities (from radio to gamma-ray energies) took part in the second M87 EHT campaign. The goal of this extensive MWL campaign was to better understand the physics of the accreting black hole M87*, the relationship between the inflow and inner jets, and the high-energy particle acceleration. Understanding the complex astrophysics is also a necessary first step towards performing further tests of general relativity. The MWL campaign took place in April 2018, overlapping with the EHT M87* observations. We present a new, contemporaneous spectral energy distribution (SED) ranging from radio to very high energy (VHE) gamma-rays, as well as details of the individual observations and light curves. We also conduct phenomenological modelling to investigate the basic source properties. We present the first VHE gamma-ray flare from M87 detected since 2010. The flux above 350 GeV has more than doubled within a period of about 36 hours. We find that the X-ray flux is enhanced by about a factor of two compared to 2017, while the radio and millimetre core fluxes are consistent between 2017 and 2018. We detect evidence for a monotonically increasing jet position angle that corresponds to variations in the bright spot of the EHT image. Our results show the value of continued MWL monitoring together with precision imaging for addressing the origins of high-energy particle acceleration. While we cannot currently pinpoint the precise location where such acceleration takes place, the new VHE gamma-ray flare already presents a challenge to simple one-zone leptonic emission model approaches, and emphasises the need for combined image and spectral modelling., Comment: 46 pages, 23 figures, accepted by Astronomy & Astrophysics on August. 29, 2024

Published
2024
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87. Risk of Harm in VR Dating from the Perspective of Women and LGBTQIA+ Stakeholders

Author

Tebbe, Devin, Barkallah, Meryem, Burger, Braeden, and Zytko, Douglas

Subjects
Computer Science - Human-Computer Interaction
Abstract

Virtual reality (VR) dating introduces novel opportunities for romantic interactions, but it also raises concerns about new harms that typically occur separately in traditional dating apps and general-purpose social VR environments. Given the subjectivity in which VR dating experiences can be considered harmful it is imperative to involve user stakeholders in anticipating harms and formulating preventative designs. Towards this goal with conducted participatory design workshops with 17 stakeholders identified as women and/or LGBTQIA+; demographics that are at elevated risk of harm in online dating and social VR. Findings reveal that participants are concerned with two categories of harm in VR dating: those that occur through the transition of interaction across virtual and physical modalities, and harms stemming from expectations of sexual interaction in VR., Comment: First three listed authors had equal contributions. This is an accepted position statement of CHI 2024 Workshop (Novel Approaches for Understanding and Mitigating Emerging New Harms in Immersive and Embodied Virtual Spaces: A Workshop at CHI 2024)

Published
2024

88. Efficient rational approximation of optical response functions with the AAA algorithm

Author

Betz, Fridtjof, Hammerschmidt, Martin, Zschiedrich, Lin, Burger, Sven, and Binkowski, Felix

Subjects
Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Computational Physics
Abstract

We introduce a theoretical framework for the rational approximation of optical response functions in resonant photonic systems. The framework is based on the AAA algorithm and further allows to solve the underlying nonlinear eigenproblems and to efficiently model sensitivities. An adaptive sampling strategy exploits the predominance of resonances in the physical response. We investigate a chiral metasurface and show that the chiroptical response on parameter variations can be accurately modeled in the vicinity of the relevant resonance frequencies.

Published
2024
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89. Multi-Modal Contrastive Learning for Online Clinical Time-Series Applications

Author

Baldenweg, Fabian, Burger, Manuel, Rätsch, Gunnar, and Kuznetsova, Rita

Subjects
Computer Science - Machine Learning
Abstract

Electronic Health Record (EHR) datasets from Intensive Care Units (ICU) contain a diverse set of data modalities. While prior works have successfully leveraged multiple modalities in supervised settings, we apply advanced self-supervised multi-modal contrastive learning techniques to ICU data, specifically focusing on clinical notes and time-series for clinically relevant online prediction tasks. We introduce a loss function Multi-Modal Neighborhood Contrastive Loss (MM-NCL), a soft neighborhood function, and showcase the excellent linear probe and zero-shot performance of our approach., Comment: Accepted as a Workshop Paper at TS4H@ICLR2024

Published
2024

90. Unveiling extended gamma-ray emission around HESS J1813-178

Author

Aharonian, F., Benkhali, F. Ait, Aschersleben, J., Ashkar, H., Backes, M., Baktash, A., Martins, V. Barbosa, Barnard, J., Batzofin, R., Becherini, Y., Berge, D., Bernlöhr, K., Bi, B., Böttcher, M., Boisson, C., Bolmont, J., de Lavergne, M. de Bony, Borowska, J., Bouyahiaoui, M., Breuhaus, M., Brose, R., Brun, F., Bruno, B., Bulik, T., Burger-Scheidlin, C., Caroff, S., Casanova, S., Cecil, R., Celic, J., Cerruti, M., Chambery, P., Chand, T., Chen, A., Chibueze, J., Chibueze, O., Cotter, G., Mbarubucyeye, J. Damascene, Djannati-Ataï, A., Dmytriiev, A., Doroshenko, V., Einecke, S., Ernenwein, J. -P., Feijen, K., Filipovic, M., Fontaine, G., Füßling, M., Funk, S., Gabici, S., Gallant, Y. A., Ghafourizadeh, S., Giavitt, G., Glawion, D., Glicenstein, J. F., Goswami, P., Grolleron, G., Grondin, M. -H., Hinton, J. A., Hofmann, W., Holch, T. L., Holler, M., Jamrozy, M., Jankowsky, F., Joshi, V., Jung-Richardt, I., Katarzyński, K., Khatoon, R., Khélifi, B., Klepser, S., Kluźniak, W., Komin, Nu., Kosack, K., Kostunin, D., Kundu, A., Lang, R. G., Stum, S. Le, Leitl, F., Lemière, A., Lemoine-Goumard, M., Lenain, J. -P., Leuschner, F., Mackey, J., Malyshev, D., Marandon, V., Marinos, P., Martí-Devesa, G., Marx, R., Mehta, A., Mitchell, A., Moderski, R., Mohrmann, L., Montanari, A., Moulin, E., Murach, T., de Naurois, M., Niemiec, J., Noel, A. Priyana, O'Brien, P., Ohm, S., Olivera-Nieto, L., Wilhelmi, E. de Ona, Ostrowski, M., Panny, S., Panter, M., Parsons, R. D., Prokhorov, D. A., Pühlhofer, G., Punch, M., Quirrenbach, A., Regeard, M., Reichherzer, P., Reimer, A., Reimer, O., Ren, H., Renaud, M., Reville, B., Rieger, F., Roellinghoff, G., Rudak, B., Sahakian, V., Salzmann, H., Sasaki, M., Schüssler, F., Schutte, H. M., Shapopi, J. N. S., Specovius, A., Spencer, S., Steenkamp, R., Steinmassl, S., Steppa, C., Sushch, I., Suzuki, H., Takahashi, T., Tanaka, T., Terrier, R., Tluczykont, M., Tsuji, N., Unbehaun, T., van Eldik, C., Vecchi, M., Veh, J., Venter, C., Vink, J., Wach, T., Wagner, S. J., Wierzcholska, A., Zacharias, M., Zargaryan, D., Zdziarski, A. A., Zouari, S., and Żywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

HESS J1813$-$178 is a very-high-energy $\gamma$-ray source spatially coincident with the young and energetic pulsar PSR J1813$-$1749 and thought to be associated with its pulsar wind nebula (PWN). Recently, evidence for extended high-energy emission in the vicinity of the pulsar has been revealed in the Fermi Large Area Telescope (LAT) data. This motivates revisiting the HESS J1813$-$178 region, taking advantage of improved analysis methods and an extended data set. Using data taken by the High Energy Stereoscopic System (H.E.S.S.) experiment and the Fermi-LAT, we aim to describe the $\gamma$-ray emission in the region with a consistent model, to provide insights into its origin. We performed a likelihood-based analysis on 32 hours of H.E.S.S. data and 12 years of Fermi-LAT data and fit a spectro-morphological model to the combined datasets. These results allowed us to develop a physical model for the origin of the observed $\gamma$-ray emission in the region. In addition to the compact very-high-energy $\gamma$-ray emission centered on the pulsar, we find a significant yet previously undetected component along the Galactic plane. With Fermi-LAT data, we confirm extended high-energy emission consistent with the position and elongation of the extended emission observed with H.E.S.S. These results establish a consistent description of the emission in the region from GeV energies to several tens of TeV. This study suggests that HESS J1813$-$178 is associated with a $\gamma$-ray PWN powered by PSR J1813$-$1749. A possible origin of the extended emission component is inverse Compton emission from electrons and positrons that have escaped the confines of the pulsar and form a halo around the PWN., Comment: 13+5 pages, 13+11 figures. Accepted for publication in A&A. Corresponding authors: T.Wach, A.Mitchell, V.Joshi, P.Chamb\'ery

Published
2024
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91. Exosense: A Vision-Based Scene Understanding System For Exoskeletons

Author

Wang, Jianeng, Mattamala, Matias, Kassab, Christina, Burger, Guillaume, Elnecave, Fabio, Zhang, Lintong, Petriaux, Marine, and Fallon, Maurice

Subjects
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract

Self-balancing exoskeletons are a key enabling technology for individuals with mobility impairments. While the current challenges focus on human-compliant hardware and control, unlocking their use for daily activities requires a scene perception system. In this work, we present Exosense, a vision-centric scene understanding system for self-balancing exoskeletons. We introduce a multi-sensor visual-inertial mapping device as well as a navigation stack for state estimation, terrain mapping and long-term operation. We tested Exosense attached to both a human leg and Wandercraft's Personal Exoskeleton in real-world indoor scenarios. This enabled us to test the system during typical periodic walking gaits, as well as future uses in multi-story environments. We demonstrate that Exosense can achieve an odometry drift of about 4 cm per meter traveled, and construct terrain maps under 1 cm average reconstruction error. It can also work in a visual localization mode in a previously mapped environment, providing a step towards long-term operation of exoskeletons., Comment: 8 pages, 9 figures

Published
2024

92. Dynamic Survival Analysis for Early Event Prediction

Author

Yèche, Hugo, Burger, Manuel, Veshchezerova, Dinara, and Rätsch, Gunnar

Subjects
Computer Science - Machine Learning
Abstract

This study advances Early Event Prediction (EEP) in healthcare through Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk localization into alarm policies to enhance clinical event metrics. By adapting and evaluating DSA models against traditional EEP benchmarks, our research demonstrates their ability to match EEP models on a time-step level and significantly improve event-level metrics through a new alarm prioritization scheme (up to 11% AuPRC difference). This approach represents a significant step forward in predictive healthcare, providing a more nuanced and actionable framework for early event prediction and management.

Published
2024

93. Spectrum and extension of the inverse-Compton emission of the Crab Nebula from a combined Fermi-LAT and H.E.S.S. analysis

Author

Aharonian, F., Benkhali, F. Ait, Aschersleben, J., Ashkar, H., Backes, M., Baktash, A., Martins, V. Barbosa, Batzofin, R., Becherini, Y., Berge, D., Bernlöhr, K., Bi, B., Böttcher, M., Boisson, C., Bolmont, J., de Lavergne, M. de Bony, Borowska, J., Bradascio, F., Breuhaus, M., Brose, R., Brown, A., Brun, F., Bruno, B., Bulik, T., Burger-Scheidlin, C., Bylund, T., Caroff, S., Casanova, S., Cecil, R., Celic, J., Cerruti, M., Chambery, P., Chand, T., Chandra, S., Chen, A., Chibueze, J., Chibueze, O., Cotter, G., Cristofari, P., Devin, J., Djannati-Ataï, A., Djuvsland, J., Dmytriiev, A., Einecke, S., Ernenwein, J. -P., Fegan, S., Feijen, K., Filipović, M., Fontaine, G., Füßling, M., Funk, S., Gabici, S., Gallant, Y. A., Giavitto, G., Glawion, D., Glicenstein, J. F., Glombitza, J., Goswami, P., Grolleron, G., Grondin, M. -H., Haerer, L., Hinton, J. A., Hofmann, W., Holch, T. L., Holler, M., Horns, D., Jamrozy, M., Jankowsky, F., Joshi, V., Kasai, E., Katarzyński, K., Khatoon, R., Khélifi, B., Kluźniak, W., Komin, Nu., Kosack, K., Kostunin, D., Kundu, A., Lang, R. G., Stum, S. Le, Leitl, F., Lemière, A., Lemoine-Goumard, M., Lenain, J. -P., Leuschner, F., Luashvili, A., Mackey, J., Malyshev, D., Marandon, V., Marinos, P., Martí-Devesa, G., Marx, R., Mehta, A., Meyer, M., Mitchell, A., Moderski, R., Mohrmann, L., Montanari, A., Moulin, E., Murach, T., de Naurois, M., Niemiec, J., O'Brien, P., Ohm, S., Olivera-Nieto, L., Wilhelmi, E. de Ona, Ostrowski, M., Panny, S., Panter, M., Parsons, R. D., Peron, G., Prokhorov, D. A., Pühlhofer, G., Punch, M., Quirrenbach, A., Regeard, M., Reichherzer, P., Reimer, A., Reimer, O., Ren, H., Renaud, M., Reville, B., Rieger, F., Roellinghoff, G., Rudak, B., Sahakian, V., Salzmann, H., Sasaki, M., Schüssler, F., Schutte, H. M., Shapopi, J. N. S., Specovius, A., Spencer, S., Stawarz, Ł., Steenkamp, R., Steinmassl, S., Steppa, C., Streil, K., Sushch, I., Suzuki, H., Takahashi, T., Tanaka, T., Terrier, R., Tluczykont, M., Tsuji, N., Unbehaun, T., van Eldik, C., Vecchi, M., Veh, J., Venter, C., Vink, J., Wach, T., Wagner, S. J., Wierzcholska, A., Zacharias, M., Zargaryan, D., Zdziarski, A. A., Zech, A., Zouari, S., Żywucka, N., and Harding, A.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Crab Nebula is a unique laboratory for studying the acceleration of electrons and positrons through their non-thermal radiation. Observations of very-high-energy $\gamma$ rays from the Crab Nebula have provided important constraints for modelling its broadband emission. We present the first fully self-consistent analysis of the Crab Nebula's $\gamma$-ray emission between 1 GeV and $\sim$100 TeV, that is, over five orders of magnitude in energy. Using the open-source software package Gammapy, we combined 11.4 yr of data from the Fermi Large Area Telescope and 80 h of High Energy Stereoscopic System (H.E.S.S.) data at the event level and provide a measurement of the spatial extension of the nebula and its energy spectrum. We find evidence for a shrinking of the nebula with increasing $\gamma$-ray energy. Furthermore, we fitted several phenomenological models to the measured data, finding that none of them can fully describe the spatial extension and the spectral energy distribution at the same time. Especially the extension measured at TeV energies appears too large when compared to the X-ray emission. Our measurements probe the structure of the magnetic field between the pulsar wind termination shock and the dust torus, and we conclude that the magnetic field strength decreases with increasing distance from the pulsar. We complement our study with a careful assessment of systematic uncertainties., Comment: 18+6 pages, 15+2 figures. Accepted for publication in A&A. Corresponding authors: M. Meyer, L. Mohrmann, T. Unbehaun. v2: after A&A language editing

Published
2024
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94. First Measurement of the $\nu_e$ and $\nu_\mu$ Interaction Cross Sections at the LHC with FASER's Emulsion Detector

Author

FASER Collaboration, Abraham, Roshan Mammen, Anders, John, Antel, Claire, Ariga, Akitaka, Ariga, Tomoko, Atkinson, Jeremy, Bernlochner, Florian U., Boeckh, Tobias, Boyd, Jamie, Brenner, Lydia, Burger, Angela, Cadoux, Franck, Cardella, Roberto, Casper, David W., Cavanagh, Charlotte, Chen, Xin, Coccaro, Andrea, Debieux, Stephane, D'Onofrio, Monica, Desai, Ansh, Dmitrievsky, Sergey, Eley, Sinead, Favre, Yannick, Fellers, Deion, Feng, Jonathan L., Fenoglio, Carlo Alberto, Ferrere, Didier, Fieg, Max, Filali, Wissal, Fujimori, Haruhi, Garabaglu, Ali, Gibson, Stephen, Gonzalez-Sevilla, Sergio, Gornushkin, Yuri, Gwilliam, Carl, Hayakawa, Daiki, Hsu, Shih-Chieh, Hu, Zhen, Iacobucci, Giuseppe, Inada, Tomohiro, Iodice, Luca, Jakobsen, Sune, Joos, Hans, Kajomovitz, Enrique, Kanai, Takumi, Kawahara, Hiroaki, Keyken, Alex, Kling, Felix, Kock, Daniela, Kontaxakis, Pantelis, Kose, Umut, Kotitsa, Rafaella, Kuehn, Susanne, Kugathasan, Thanushan, Lefebvre, Helena, Levinson, Lorne, Li, Ke, Liu, Jinfeng, Lutz, Margaret S., MacDonald, Jack, Magliocca, Chiara, Martinelli, Fulvio, McCoy, Lawson, McFayden, Josh, Medina, Andrea Pizarro, Milanesio, Matteo, Moretti, Theo, Munker, Magdalena, Nakamura, Mitsuhiro, Nakano, Toshiyuki, Neuhaus, Friedemann, Nevay, Laurie, Nonaka, Motoya, Okui, Kazuaki, Ohashi, Ken, Otono, Hidetoshi, Pang, Hao, Paolozzi, Lorenzo, Petersen, Brian, Prim, Markus, Queitsch-Maitland, Michaela, Rokujo, Hiroki, Ruiz-Choliz, Elisa, Rubbia, André, Sabater-Iglesias, Jorge, Sato, Osamu, Scampoli, Paola, Schmieden, Kristof, Schott, Matthias, Sfyrla, Anna, Shamim, Mansoora, Shively, Savannah, Takubo, Yosuke, Tarannum, Noshin, Theiner, Ondrej, Torrence, Eric, Vasina, Svetlana, Vormwald, Benedikt, Wang, Di, Wang, Yuxiao, Welch, Eli, Zahorec, Samuel, Zambito, Stefano, and Zhang, Shunliang

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract

This paper presents the first results of the study of high-energy electron and muon neutrino charged-current interactions in the FASER$\nu$ emulsion/tungsten detector of the FASER experiment at the LHC. A subset of the FASER$\nu$ volume, which corresponds to a target mass of 128.6~kg, was exposed to neutrinos from the LHC $pp$ collisions with a centre-of-mass energy of 13.6~TeV and an integrated luminosity of 9.5 fb$^{-1}$. Applying stringent selections requiring electrons with reconstructed energy above 200~GeV, four electron neutrino interaction candidate events are observed with an expected background of $0.025^{+0.015}_{-0.010}$, leading to a statistical significance of 5.2$\sigma$. This is the first direct observation of electron neutrino interactions at a particle collider. Eight muon neutrino interaction candidate events are also detected, with an expected background of $0.22^{+0.09}_{-0.07}$, leading to a statistical significance of 5.7$\sigma$. The signal events include neutrinos with energies in the TeV range, the highest-energy electron and muon neutrinos ever detected from an artificial source. The energy-independent part of the interaction cross section per nucleon is measured over an energy range of 560--1740 GeV (520--1760 GeV) for $\nu_e$ ($\nu_{\mu}$) to be $(1.2_{-0.7}^{+0.8}) \times 10^{-38}~\mathrm{cm}^{2}\,\mathrm{GeV}^{-1}$ ($(0.5\pm0.2) \times 10^{-38}~\mathrm{cm}^{2}\,\mathrm{GeV}^{-1}$), consistent with Standard Model predictions. These are the first measurements of neutrino interaction cross sections in those energy ranges.

Published
2024
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95. The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Author

Li, Nathaniel, Pan, Alexander, Gopal, Anjali, Yue, Summer, Berrios, Daniel, Gatti, Alice, Li, Justin D., Dombrowski, Ann-Kathrin, Goel, Shashwat, Phan, Long, Mukobi, Gabriel, Helm-Burger, Nathan, Lababidi, Rassin, Justen, Lennart, Liu, Andrew B., Chen, Michael, Barrass, Isabelle, Zhang, Oliver, Zhu, Xiaoyuan, Tamirisa, Rishub, Bharathi, Bhrugu, Khoja, Adam, Zhao, Zhenqi, Herbert-Voss, Ariel, Breuer, Cort B., Marks, Samuel, Patel, Oam, Zou, Andy, Mazeika, Mantas, Wang, Zifan, Oswal, Palash, Lin, Weiran, Hunt, Adam A., Tienken-Harder, Justin, Shih, Kevin Y., Talley, Kemper, Guan, John, Kaplan, Russell, Steneker, Ian, Campbell, David, Jokubaitis, Brad, Levinson, Alex, Wang, Jean, Qian, William, Karmakar, Kallol Krishna, Basart, Steven, Fitz, Stephen, Levine, Mindy, Kumaraguru, Ponnurangam, Tupakula, Uday, Varadharajan, Vijay, Wang, Ruoyu, Shoshitaishvili, Yan, Ba, Jimmy, Esvelt, Kevin M., Wang, Alexandr, and Hendrycks, Dan

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society
Abstract

The White House Executive Order on Artificial Intelligence highlights the risks of large language models (LLMs) empowering malicious actors in developing biological, cyber, and chemical weapons. To measure these risks of malicious use, government institutions and major AI labs are developing evaluations for hazardous capabilities in LLMs. However, current evaluations are private, preventing further research into mitigating risk. Furthermore, they focus on only a few, highly specific pathways for malicious use. To fill these gaps, we publicly release the Weapons of Mass Destruction Proxy (WMDP) benchmark, a dataset of 3,668 multiple-choice questions that serve as a proxy measurement of hazardous knowledge in biosecurity, cybersecurity, and chemical security. WMDP was developed by a consortium of academics and technical consultants, and was stringently filtered to eliminate sensitive information prior to public release. WMDP serves two roles: first, as an evaluation for hazardous knowledge in LLMs, and second, as a benchmark for unlearning methods to remove such hazardous knowledge. To guide progress on unlearning, we develop RMU, a state-of-the-art unlearning method based on controlling model representations. RMU reduces model performance on WMDP while maintaining general capabilities in areas such as biology and computer science, suggesting that unlearning may be a concrete path towards reducing malicious use from LLMs. We release our benchmark and code publicly at https://wmdp.ai, Comment: See the project page at https://wmdp.ai

Published
2024

97. CLARITY: A Call for Transparency in Marine Diamond Mining

Author

Burger, Morgan

Subjects
Marine Diamond Mining, Seafloor Mining, Seabed Mining, Namibia, Greenland, Orange River, Maniitsoq, Economic Development, Ecosystem Preservation, Fisheries, Climate Change, Seafloor Extraction, Arctic Ecosystems, Sociopolitical Conflict, Environmental Ethics, Marine Conservation, Inuit Communities, Sustainability, Marine Science, Deep-Sea Mining, Economic Trade-offs, Environmental Justice, Documentary Film, Science Communication
Abstract

This capstone project tells the untold story of marine diamond mining, tracing its origins from the shores of Namibia to the fjords of Greenland. Despite the stark differences between these two locales, they share striking similarities in diamond potential. In Namibia, marine diamond mining flourished prior to the country's independence and the establishment of international mining laws, setting a precedent for potential challenges in Greenland's current political landscape. Through in-depth research, stakeholder interviews, and media production, this project fosters an informed storyline for a full-length documentary film. The capstone deliverables encompass a film treatment, budget, film plan, concise trailer, and transcribed interviews, strategically crafted towards securing future support of the project. The outcome of such seeking to advocate for greater transparency in the diamond industry and policies that prioritize both economic development and environmental integrity. The final film will engage audiences worldwide in considering the implications of marine diamond mining for Greenland's evolving climate and economy.CLARITY film treatment can be found here: https://tinyurl.com/ClarityTreatment CLARITY interview transcriptions can be found here: https://tinyurl.com/ClarityTranscriptions

Published
2024

98. Cortical plasticity is associated with blood-brain barrier modulation.

Author

Swissa, Evyatar, Monsonego, Uri, Yang, Lynn, Schori, Lior, Kamintsky, Lyna, Mirloo, Sheida, Burger, Itamar, Uzzan, Sarit, Patel, Rishi, Sudmant, Peter, Prager, Ofer, Kaufer, Daniela, and Friedman, Alon

Subjects
albumin, blood–brain barrier, caveolae-mediated transcytosis, human, magnetic resonance imaging, neuroscience, rat, synaptic plasticity, transforming growth factor β, Animals, Blood-Brain Barrier, Neuronal Plasticity, Rats, Humans, Male, Magnetic Resonance Imaging, Somatosensory Cortex, Capillary Permeability, Adult
Abstract

Brain microvessels possess the unique properties of a blood-brain barrier (BBB), tightly regulating the passage of molecules from the blood to the brain neuropil and vice versa. In models of brain injury, BBB dysfunction and the associated leakage of serum albumin to the neuropil have been shown to induce pathological plasticity, neuronal hyper-excitability, and seizures. The effect of neuronal activity on BBB function and whether it plays a role in plasticity in the healthy brain remain unclear. Here we show that neuronal activity induces modulation of microvascular permeability in the healthy brain and that it has a role in local network reorganization. Combining simultaneous electrophysiological recording and vascular imaging with transcriptomic analysis in rats, and functional and BBB-mapping MRI in human subjects, we show that prolonged stimulation of the limb induces a focal increase in BBB permeability in the corresponding somatosensory cortex that is associated with long-term synaptic plasticity. We further show that the increased microvascular permeability depends on neuronal activity and involves caveolae-mediated transcytosis and transforming growth factor β signaling. Our results reveal a role of BBB modulation in cortical plasticity in the healthy brain, highlighting the importance of neurovascular interactions for sensory experience and learning.

Published
2024

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