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398,174 results on '"Mueller, A."'

1. Multimodal Misinformation Detection using Large Vision-Language Models

Author: Tahmasebi, Sahar, Müller-Budack, Eric, and Ewerth, Ralph
Subjects: Computer Science - Computation and Language, Computer Science - Information Retrieval, Computer Science - Multimedia
Abstract: The increasing proliferation of misinformation and its alarming impact have motivated both industry and academia to develop approaches for misinformation detection and fact checking. Recent advances on large language models (LLMs) have shown remarkable performance in various tasks, but whether and how LLMs could help with misinformation detection remains relatively underexplored. Most of existing state-of-the-art approaches either do not consider evidence and solely focus on claim related features or assume the evidence to be provided. Few approaches consider evidence retrieval as part of the misinformation detection but rely on fine-tuning models. In this paper, we investigate the potential of LLMs for misinformation detection in a zero-shot setting. We incorporate an evidence retrieval component into the process as it is crucial to gather pertinent information from various sources to detect the veracity of claims. To this end, we propose a novel re-ranking approach for multimodal evidence retrieval using both LLMs and large vision-language models (LVLM). The retrieved evidence samples (images and texts) serve as the input for an LVLM-based approach for multimodal fact verification (LVLM4FV). To enable a fair evaluation, we address the issue of incomplete ground truth for evidence samples in an existing evidence retrieval dataset by annotating a more complete set of evidence samples for both image and text retrieval. Our experimental results on two datasets demonstrate the superiority of the proposed approach in both evidence retrieval and fact verification tasks and also better generalization capability across dataset compared to the supervised baseline., Comment: Accepted for publication in: Conference on Information and Knowledge Management (CIKM) 2024
Published: 2024

2. Observation of exotic $J/\psi\phi$ resonances in diffractive processes in proton-proton collisions

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., Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Baldini, W., Leite, J. Baptista de Souza, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Baryshnikov, F., Basels, J. M., Bassi, G., Batsukh, B., Battig, A., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Beiter, 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, Bertella, C., 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., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bowcock, T. J. V., Boyer, A., Bozzi, C., Bradley, M. J., 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., Bursche, A., Butkevich, A., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Calabrese, R., Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, 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., Cerasoli, J., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Barajas, C. A. Chavez, Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., 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., 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, D., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., 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., Dolmatov, A., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Downes, A. G., 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., Ek-In, S., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Epple, E., Escher, S., 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., Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Sole, S. Ferreres, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Fischer, K. M., Fitzgerald, D. S., Fitzpatrick, C., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Fuehring, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. Gallas, Galli, D., Gambetta, S., Gandelman, M., Gandini, P., Gao, H., Gao, R., Gao, Y., Garau, M., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., 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., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Hajheidari, M., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Harrison, T., Hartmann, M., He, J., Heijhoff, K., 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, Hill, D., Hollitt, S. E., 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., 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., Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kang, Y., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., 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., Kretzschmar, S., Krokovny, P., Krupa, W., Krzemien, W., Kubat, J., Kubis, S., Kucewicz, W., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Leverington, B., Li, A., Li, H., Li, K., Li, L., Li, P., Li, P. -R., Li, S., Li, T., Li, Y., Li, Z., Lian, Z., Liang, X., Libralon, S., Lin, C., Lin, T., Lindner, R., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, Q., Liu, S., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Castro, J. Lomba, Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lovell, G. H., Lucarelli, C., Lucchesi, D., Luchuk, S., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. M., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malecki, B., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Marshall, P. J., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, Massafferri, A., Materok, M., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., Mazurek, M., McCann, M., Mcconnell, L., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Meadows, B., Meier, G., Melnychuk, D., 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., Mödden, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., 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., Nogga, P., Nolte, N. S., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Pawley, C. J., Pellegrino, A., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Castro, A. Pereiro, Perret, P., Perro, A., Petridis, K., Petrolini, A., Petrucci, S., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Pugatch, V., Punzi, G., Qian, W., Qin, N., Qu, S., Quagliani, R., Raab, N. V., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, 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., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Lamas, M. Romero, Vidal, A. Romero, Romolini, G., Ronchetti, F., Rotondo, M., Roy, S. R., Rudolph, M. S., Ruf, T., 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., Gras, C. Sanchez, Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarpis, G., Sarpis, M., Sarti, A., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schertz, A. M., 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., 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., Shields, E. B., 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., 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., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sun, Y., Sutcliffe, W., Swallow, P. N., Swystun, F., Szabelski, A., Szumlak, T., Tan, Y., Taneja, S., 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., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Valassi, A., Valenti, G., Canudas, N. Valls, Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Laak, R., van Veghel, M., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Velthuis, J. J., Veltri, M., Venkateswaran, A., Vesterinen, M., Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Vorobyev, V., Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Westhenry, B. D. C., White, D. J., Whitehead, M., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. R. J., Williams, R., Wilson, F. F., Wislicki, W., Witek, M., Witola, L., Wong, C. P., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, Y., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xu, A., Xu, J., Xu, L., Xu, M., Xu, Z., Yang, D., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yu, C. Y., Yu, J., Yuan, X., Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhao, Y., Zharkova, A., Zhelezov, A., 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 study of $J/\psi\phi$ production in diffractive processes in proton-proton collisions is presented. The study is based on an LHCb dataset recorded at centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 5 fb$^{-1}$. The data disfavour a nonresonant $J/\psi\phi$ production but are consistent with a resonant model including several resonant states observed previously only in $B^+ \to J/\psi\phi K^+$ decays. The $\chi_{c0}(4500)$ state is observed with a significance over $5\sigma$ and the $\chi_{c1}(4274)$ is confirmed with a significance of more than $4\sigma$., Comment: All figures and tables, along with any supplementary material and additional information, are available at: https://lhcbproject.web.cern.ch/Publications/LHCbProjectPublic/LHCb-PAPER-2023-043.html (LHCb public pages)
Published: 2024

3. Study of charmonium production via the decay to $p\bar{p}$ at $\sqrt{s} = 13 TeV$

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., Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Baldini, W., Bao, H., Leite, J. Baptista de Souza, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Baryshnikov, F., Basels, J. M., Bassi, G., Batsukh, B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., 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., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bowcock, T. J. V., Boyer, A., Bozzi, C., Bradley, M. J., 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., Butkevich, A., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., 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., Barajas, C. A. Chavez, Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., 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., 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., 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., 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. M., Fitzgerald, D. S., Fitzpatrick, C., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Fuehring, 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, Y., Garau, M., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., 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., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Hajheidari, M., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Hartmann, M., 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, Hill, D., Hollitt, S. E., 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., 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., Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., 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. K., Kubat, J., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Leverington, B., Li, A., Li, H., Li, K., Li, L., 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., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, S., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Castro, J. Lomba, Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lucarelli, C., Lucchesi, D., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. M., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, Massafferri, A., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., Mazurek, M., McCann, M., Mcconnell, L., 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., Mödden, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., 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., Nogarolli, P., Nogga, P., Nolte, N. S., 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., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., 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., Castro, A. Pereiro, Perret, P., Perro, A., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Pugatch, V., Punzi, G., Qasim, S., Qian, W., Qin, N., Qu, S., Quagliani, R., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, 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., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Lamas, M. Romero, Vidal, A. Romero, Romolini, G., Ronchetti, F., Rotondo, M., Roy, S. R., Rudolph, M. S., Ruf, T., 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., Gras, C. Sanchez, Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., 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., 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., Shields, E. B., 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., 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., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sun, Y., Sundfeld, D., Sutcliffe, W., Swallow, P. N., Swystun, F., Szabelski, A., Szumlak, T., Tan, 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., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Valassi, A., Valenti, G., Canudas, N. Valls, 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., Vesterinen, M., Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, D. J., Whitehead, M., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. R. J., Williams, R., Wilson, F. F., Wislicki, W., Witek, M., Witola, L., Wong, C. P., 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, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yu, C. Y., Yu, J., Yuan, X., Zaffaroni, E., Zavertyaev, M., Zdybal, M., 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, 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: Charmonium production cross-section in proton-proton collisions is measured at the centre-of-mass energy $\sqrt{s}=13\,TeV$ using decays to $p\bar{p}$ final state. The study is performed using a data sample corresponding to an integrated luminosity of $2.2\,{fb}^{-1}$ collected in 2018 with the $LHCb$ detector. The production cross-section of the $\eta_c$ meson is measured in a rapidity range of $2.0 < y < 4.0$ and in a transverse momentum range of $5.0 < p_{T} < 20.0\,{GeV/\it{c}}$, which is extended compared with previous $LHCb$ analyses. The differential cross-section is measured in bins of $p_{T}$ and, for the first time, of $y$. Upper limits, at 90% and 95% confidence levels, on the $\eta_c(2S)$ and $h_c(1P)$ prompt production cross-sections are determined for the first time., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-004.html (LHCb public pages)
Published: 2024

4. Temporal Evolution of Defects and Related Electric Properties in He-Irradiated YBa$_{2}$Cu$_{3}$O$_{7-\delta}$ Thin Films

Author: Keppert, Sandra, Aichner, Bernd, Rohringer, Philip, Bodea, Marius-Aurel, Müller, Benedikt, Karrer, Max, Kleiner, Reinhold, Goldobin, Edward, Koelle, Dieter, Pedarnig, Johannes D., and Lang, Wolfgang
Subjects: Condensed Matter - Superconductivity, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract: Thin films of the superconductor YBa$_2$Cu$_3$O$_{7-\delta}$ (YBCO) were modified by low-energy light-ion irradiation employing collimated or focused He$^+$ beams, and the long-term stability of irradiation-induced defects was investigated. For films irradiated with collimated beams, the resistance was measured in situ during and after irradiation and analyzed using a phenomenological model. The formation and stability of irradiation-induced defects are highly influenced by temperature. Thermal annealing experiments conducted in an Ar atmosphere at various temperatures demonstrated a decrease in resistivity and allowed us to determine diffusion coefficients and the activation energy $\Delta E = (0.31 \pm 0.03)$ eV for diffusive oxygen rearrangement within the YBCO unit cell basal plane. Additionally, thin YBCO films, nanostructured by focused He$^+$-beam irradiation into vortex pinning arrays, displayed significant commensurability effects in magnetic fields. Despite the strong modulation of defect densities in these pinning arrays, oxygen diffusion during room-temperature annealing over almost six years did not compromise the signatures of vortex matching, which remained precisely at their magnetic fields predicted by the pattern geometry. Moreover, the critical current increased substantially within the entire magnetic field range after long-term storage in dry air. These findings underscore the potential of ion irradiation in tailoring the superconducting properties of thin YBCO films., Comment: 16 pages, 8 figures
Published: 2024
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5. Current-Crowding-Free Superconducting Nanowire Single-Photon Detectors

Author: Strohauer, Stefan, Wietschorke, Fabian, Schmid, Christian, Grotowski, Stefanie, Zugliani, Lucio, Jonas, Björn, Müller, Kai, and Finley, Jonathan J.
Subjects: Quantum Physics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Superconductivity, Physics - Instrumentation and Detectors, Physics - Optics
Abstract: Detecting single photons is essential for applications such as dark matter detection, quantum science and technology, and biomedical imaging. Superconducting nanowire single-photon detectors (SNSPDs) excel in this task due to their near-unity detection efficiency, sub-Hz dark count rates, and picosecond timing jitter. However, a local increase of current density (current crowding) in the bends of meander-shaped SNSPDs limits these performance metrics. By locally irradiating the straight segments of SNSPDs with helium ions while leaving the bends unirradiated, we realize current-crowding-free SNSPDs with simultaneously enhanced sensitivity: after irradiation with 800 ions/nm$\unicode{xB2}$, locally irradiated SNSPDs showed a relative saturation plateau width of 37% while fully irradiated SNSPDs reached only 10%. This larger relative plateau width allows operation at lower relative bias currents, thereby reducing the dark count rate while still detecting single photons efficiently. We achieve an internal detection efficiency of 94% for a wavelength of 780 nm with a dark count rate of 7 mHz near the onset of saturating detection efficiency., Comment: 11 pages, 7 figures
Published: 2024

6. Amplitude analysis of $B^+ \to \psi(2S) K^+ \pi^+ \pi^-$ 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. Ataide, 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. B., Belin, S., Bellee, V., Belous, K., Belov, 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., 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., Butkevich, A., 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., Barajas, C. A. Chavez, 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. C., 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., 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. M., Fitzgerald, D. S., Fitzpatrick, C., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Fuehring, 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, Y., Garau, M., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Girardey, L., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., 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., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Hajheidari, M., Hallett, G. H., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., 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, Hill, D., Hollitt, S. E., 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., 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., 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. K., Kubat, J., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., 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., Leverington, B., Li, A., Li, C., Li, H., Li, K., Li, L., 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., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, S., Liu, W., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Castro, J. Lomba, Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lucarelli, C., Lucchesi, D., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. M., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martel, L., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, 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., Mcconnell, L., 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., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., 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., Nogarolli, P., Nogga, P., Nolte, N. S., 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., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., 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., Perro, A., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Pietrzyk, B., Pietrzyk, G., 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., 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., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Lamas, M. Romero, 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., Gras, C. Sanchez, Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A. S., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., 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., Sellam, S., Semennikov, A., Senger, T., Soares, M. 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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., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Valenti, G., Canudas, N. Valls, 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., Vesterinen, M., Benet, D. Vico, Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., 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., Wong, C. P., 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., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., 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: The first full amplitude analysis of $B^+ \to \psi(2S) K^+ \pi^+ \pi^-$ decays is performed using proton-proton collision data corresponding to an integrated luminosity of $9\,\text{fb}^{-1}$ recorded with the LHCb detector. The rich $K^+ \pi^+ \pi^-$ spectrum is studied and the branching fractions of the resonant substructure associated with the prominent $K_1(1270)^+$ contribution are measured. The data cannot be described by conventional strange and charmonium resonances only. An amplitude model with 53 components is developed comprising 11 hidden-charm exotic hadrons. New production mechanisms for charged charmonium-like states are observed. Significant resonant activity with spin-parity $J^P = 1^+$ in the $\psi(2S) \pi^+$ system is confirmed and a multi-pole structure is demonstrated. The spectral decomposition of the $\psi(2S) \pi^+ \pi^-$ invariant-mass structure, dominated by $X^0 \to \psi(2S) \rho(770)^0$ decays, broadly resembles the $J/\psi \phi$ spectrum observed in $B^+ \to J/\psi \phi K^+$ decays. Exotic $\psi(2S) K^+ \pi^-$ resonances are observed for the first time., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-014.html (LHCb public pages)
Published: 2024

7. A two-sorted theory of nilpotent Lie algebras

Author: d'Elbée, Christian, Müller, Isabel, Ramsey, Nicholas, and Siniora, Daoud
Subjects: Mathematics - Logic
Abstract: We prove the existence of a model companion of the two-sorted theory of $c$-nilpotent Lie algebras over a field satisfying a given theory of fields. We describe a language in which it admits relative quantifier elimination up to the field sort. Using a new criterion which does not rely on a stationary independence relation, we prove that if the field is NSOP$_1$, then the model companion is NSOP$_4$. We also prove that if the field is algebraically closed, then the model companion is $c$-NIP.
Published: 2024

8. Angular dependent measurement of electron-ion recombination in liquid argon for ionization calorimetry in the ICARUS liquid argon time projection chamber

Author: ICARUS collaboration, Abratenko, P., Abrego-Martinez, N., Aduszkiewicz, A., Akbar, F., Soplin, L. Aliaga, Pons, M. Artero, Asaadi, J., Badgett, W. F., Baibussinov, B., Behera, B., Bellini, V., Benocci, R., Berkman, S., Bertolucci, S., Betancourt, M., Bonesini, M., Boone, T., Bottino, B., Braggiotti, A., Brailsford, D., Brice, S. J., Brio, V., Brizzolari, C., Campani, H. S. Budd A., Campos, A., Carber, D., Carneiro, M., Terrazas, I. Caro, Carranza, H., Fernandez, F. Castillo, Castro, A., Centro, S., Cerati, G., Chatterjee, A., Cherdack, D., Cherubini, S., Chitirasreemadam, N., Cicerchia, M., Coan, T., Cocco, A., Convery, M. R., Cooper-Troendle, L., Copello, S., Dange, A. A., De Roeck, A., Di Noto, L., Di Stefano, C., DiFerdinando, D., Diwan, M., Dolan, S., Domine, L., Donati, S., Drielsma, F., Dyer, J., Dytman, S., Falcone, A., Farnese, C., Fava, A., Ferrari, A., Gallice, N., Garcia, F. G., Gatto, C., Gibin, D., Gioiosa, A., Gu, W., Guglielmi, A., Gurung, G., Hausner, H., Heggestuen, A., Howard, B., Howell, R., Ingratta, I., James, C., Jang, W., Jwa, Y. -J., Kashur, L., Ketchum, W., Kim, J. S., Koh, D. -H., Larkin, J., Li, Y., Mariani, C., Marshall, C. M., Martynenko, S., Mauri, N., McFarland, K. S., Méndez, D. P., Menegolli, A., Meng, G., Miranda, O. G., Mogan, A., Moggi, N., Montagna, E., Montanari, C., Montanari, A., Mooney, M., Moreno-Granados, G., Mueller, J., Murphy, M., Naples, D., Nguyen, V. C. L., Palestini, S., Pallavicini, M., Paolone, V., Papaleo, R., Pasqualini, L., Patrizii, L., Paudel, L., Petrillo, G., Petta, C., Pia, V., Pietropaolo, F., Poppi, F., Pozzato, M., Putnam, G., Qian, X., Rappoldi, A., Raselli, G. L., Repetto, S., Resnati, F., Ricci, A. M., Riccobene, G., Richards, E., Rosenberg, M., Rossella, M., Roy, P., Rubbia, C., Saad, M., Saha, S., Sala, P., Samanta, S., Sapienza, P., Scaramelli, A., Scarpelli, A., Schmitz, D., Schukraft, A., Senadheera, D., Seo, S-H., Sergiampietri, F., Sirri, G., Smedley, J. S., Smith, J., Stanco, L., Stewart, J., Tanaka, H. A., Tapia, F., Tenti, M., Terao, K., Terranova, F., Togo, V., Torretta, D., Torti, M., Tortorici, F., Triozzi, R., Tsai, Y. -T., Tufanli, S., Usher, T., Varanini, F., Ventura, S., Vicenzi, M., Vignoli, C., Viren, B., Williams, Z., Wilson, R. J., Wilson, P., Wolfs, J., Wongjirad, T., Wood, A., Worcester, E., Worcester, M., Wospakrik, M., Yu, H., Yu, J., Zani, A., Zennamo, J., Zettlemoyer, J. C., Zhang, C., and Zucchelli, S.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: This paper reports on a measurement of electron-ion recombination in liquid argon in the ICARUS liquid argon time projection chamber (LArTPC). A clear dependence of recombination on the angle of the ionizing particle track relative to the drift electric field is observed. An ellipsoid modified box (EMB) model of recombination describes the data across all measured angles. These measurements are used for the calorimetric energy scale calibration of the ICARUS TPC, which is also presented. The impact of the EMB model is studied on calorimetric particle identification, as well as muon and proton energy measurements. Accounting for the angular dependence in EMB recombination improves the accuracy and precision of these measurements.
Published: 2024

9. A SageMath Package for Elementary and Sign Vectors with Applications to Chemical Reaction Networks

Author: Aichmayr, Marcus S., Müller, Stefan, and Regensburger, Georg
Subjects: Computer Science - Symbolic Computation, Mathematics - Dynamical Systems
Abstract: We present our SageMath package elementary_vectors for computing elementary and sign vectors of real subspaces. In this setting, elementary vectors are support-minimal vectors that can be determined from maximal minors of a real matrix representing a subspace. By applying the sign function, we obtain the cocircuits of the corresponding oriented matroid, which in turn allow the computation of all sign vectors of a real subspace. As an application, we discuss sign vector conditions for existence and uniqueness of complex-balanced equilibria of chemical reaction networks with generalized mass-action kinetics. The conditions are formulated in terms of sign vectors of two subspaces arising from the stoichiometric coefficients and the kinetic orders of the reactions. We discuss how these conditions can be checked algorithmically, and we demonstrate the functionality of our package sign_vector_conditions in several examples., Comment: 10 pages, ICMS 2024
Published: 2024
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10. MBE-grown virtual substrates for quantum dots emitting in the telecom O- and C-bands

Author: Scaparra, Bianca, Sirotti, Elise, Ajay, Akhil, Jonas, Bjoern, Costa, Beatrice, Riedl, Hubert, Avdienko, Pavel, Sharp, Ian D., Koblmueller, Gregor, Zallo, Eugenio, Finley, Jonathan J., and Mueller, Kai
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics
Abstract: InAs semiconductor quantum dots (QDs) emitting in the near infrared are promising platforms for on-demand single-photon sources and spin-photon interfaces. However, the realization of quantum-photonic nanodevices emitting in the second and third telecom windows with similar performance remains an open challenge. Here, we report an optimized heterostructure design for QDs emitting in the O- and C-bands grown by means of molecular beam epitaxy. The InAs QDs are grown on compositionally graded InGaAs buffers, which act as virtual substrates, and are embedded in mostly relaxed active regions. Reciprocal space maps of the indium profiles and optical absorption spectra are used to optimize In0.22Ga0.78As and In0.30Ga0.70As active regions, accounting for the chosen indium grading profile. This approach results in a tunable QD photoluminescence (PL) emission from 1200 up to 1600 nm. Power and polarization dependent micro-PL measurements performed at 4 K reveal exciton-biexciton complexes from quantum dots emitting in the telecom O- and C-bands. The presented study establishes a flexible platform that can be an essential component for advanced photonic devices based on InAs/GaAs that serve as building blocks for future quantum networks., Comment: The following article has been submitted to APL Materials
Published: 2024

11. Search for the rare $\Lambda_c^+ \to p \mu^+ \mu^-$ decay

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., Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Baldini, W., Bao, H., Leite, J. Baptista de Souza, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Baryshnikov, F., Basels, J. M., Bassi, G., Batsukh, B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., 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., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bowcock, T. J. V., Boyer, A., Bozzi, C., Bradley, M. J., 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., Butkevich, A., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., 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., Barajas, C. A. Chavez, Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., 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., 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., 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. 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G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., 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., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Hajheidari, M., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Hartmann, M., 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, Hill, D., Hollitt, S. E., 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., 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., Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., 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. K., Kubat, J., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Leverington, B., Li, A., Li, H., Li, K., Li, L., 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., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, S., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Castro, J. Lomba, Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lucarelli, C., Lucchesi, D., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. M., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, Massafferri, A., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., Mazurek, M., McCann, M., Mcconnell, L., 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., Mödden, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., 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., Nogarolli, P., Nogga, P., Nolte, N. S., 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. 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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., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Lamas, M. Romero, Vidal, A. Romero, Romolini, G., Ronchetti, F., Rotondo, M., Roy, S. R., Rudolph, M. S., Ruf, T., 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., Gras, C. Sanchez, Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., 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., 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., Shields, E. B., 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., 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., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sun, Y., Lima, D. S. Sundfeld, Sutcliffe, W., Swallow, P. N., Swystun, F., Szabelski, A., Szumlak, T., Tan, 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., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Valassi, A., Valenti, G., Canudas, N. Valls, 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., Vesterinen, M., Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, D. J., Whitehead, M., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. R. J., Williams, R., Wilson, F. F., Wislicki, W., Witek, M., Witola, L., Wong, C. P., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, Y., 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., Yu, C. Y., Yu, J., Yuan, X., Zaffaroni, E., Zavertyaev, M., Zdybal, M., 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, 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 the nonresonant $\Lambda_c^+ \to p \mu^+ \mu^-$ decay is performed using proton-proton collision data recorded at a centre-of-mass energy of 13 TeV by the LHCb experiment, corresponding to an integrated luminosity of 5.4 fb$^{-1}$. No evidence for the decay is found in the dimuon invariant-mass regions where the expected contributions of resonances is subdominant. The upper limit on the branching fraction of the $\Lambda_c^+ \to p \mu^+ \mu^-$ decay is determined to be $2.9~(3.2) \times 10^{-8}$ at 90% (95%) confidence level. The branching fractions in the dimuon invariant-mass regions dominated by the $\eta$, $\rho$ and $\omega$ resonances are also determined., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-005.html (LHCb public pages)
Published: 2024

12. Estimate of water and hydroxyl abundance on asteroid (16) Psyche from JWST data

Author: Jarmak, Stephanie G., Becker, Tracy M., Woodward, Charles E., Honniball, Casey I., Rivkin, Andrew S., McAdam, Margaret M., Landsman, Zoe A., Cambioni, Saverio, Müller, Thomas G., Takir, Driss, Retherford, Kurt D., Arredondo, Anicia, and Elkins-Tanton, Linda T.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: Our understanding of Solar System evolution is closely tied to interpretations of asteroid composition, particularly the M-class asteroids. These asteroids were initially thought to be the exposed cores of differentiated planetesimals, a hypothesis based on their spectral similarity to iron meteorites. However, recent astronomical observations have revealed hydration on their surface through the detection of 3-$\mu$m absorption features associated with OH and potentially H2O. We present evidence of hydration due mainly to OH on asteroid (16) Psyche, the largest M-class asteroid, using data from the James Webb Space Telescope (JWST) spanning 1.1 - 6.63 $\mu$m. Our observations include two detections of the full 3-$\mu$m feature associated with OH and H2O resembling those found in CY-, CH-, and CB-type carbonaceous chondrites, and no 6-$\mu$m feature uniquely associated with H2O across two observations. We observe 3-$\mu$m depths of between 4.3 and 6% across two observations, values consistent with hydrogen abundance estimates on other airless bodies of 250 - 400 ppm. We place an upper limit of 39 ppm on the water abundance from the standard deviation around the 6-$\mu$m feature region. The presence of hydrated minerals suggests a complex history for Psyche. Exogenous sources of OH-bearing minerals could come from hydrated impactors. Endogenous OH-bearing minerals would indicate a composition more similar to E-or P-class asteroids. If the hydration is endogenous, it supports the theory that Psyche originated beyond the snow line and later migrated to the outer main belt.
Published: 2024

13. Multigrid Monte Carlo Revisited: Theory and Bayesian Inference

Author: Kazashi, Yoshihito, Müller, Eike H., and Scheichl, Robert
Subjects: Mathematics - Numerical Analysis, Mathematics - Statistics Theory, 60J22, 60G60, 62F15, 65C05, 65N55, F.2.1, G.1, G.3
Abstract: Gaussian random fields play an important role in many areas of science and engineering. In practice, they are often simulated by sampling from a high-dimensional multivariate normal distribution which arises from the discretisation of a suitable precision operator on a finite grid. Existing methods such as Cholesky factorisation and Gibbs-sampling become prohibitively expensive on fine meshes due to their high computational cost or the fact that they do not explore the probability space efficiently. In this work we revisit the Multigrid Monte Carlo algorithm of Goodman & Sokal (Physical Review D 40.6, 1989), which can overcome these issues. The novelty of our work consists in the application of the method to linear Bayesian settings where the prior is constrained by a finite set of observations. For this, we develop a bespoke random smoother which takes care of the low-rank updates that arise in Bayesian inference. We provide a rigorous analysis of the method based on the link between linear solvers and samplers for multivariate normal distributions, drawing on standard multigrid convergence theory in a finite element setting. In particular, we prove that Multigrid Monte Carlo is algorithmically near-optimal in the limit of the grid-size going to zero. These theoretical results are confirmed by numerical experiments which demonstrate that Multigrid Monte Carlo can be significantly more efficient than alternative methods when applied in a Bayesian setting., Comment: 58 pages, 4 figures, 1 table
Published: 2024

14. Entanglement Structure of Non-Gaussian States and How to Measure It

Author: Froland, Henry, Zache, Torsten V., Ott, Robert, and Mueller, Niklas
Subjects: Quantum Physics, Condensed Matter - Quantum Gases, High Energy Physics - Lattice
Abstract: Rapidly growing capabilities of quantum simulators to probe quantum many-body phenomena require new methods to characterize increasingly complex states. We present a protocol that constrains quantum states by experimentally measured correlation functions which only scales polynomially with system size. This method enables measurement of a quantum state's entanglement structure, opening a new route to study entanglement-related phenomena. Our approach extends Gaussian state parameterizations by systematically incorporating higher-order correlations. We show the protocol's usefulness in conjunction with current and forthcoming experimental capabilities, focusing on weakly interacting fermions as a proof of concept. Here, the lowest non-trivial expansion quantitatively predicts early time thermalization dynamics, including signaling the on-set of quantum chaos indicated by the entanglement Hamiltonian., Comment: 15 pages, 10 figures
Published: 2024

15. Calibration and simulation of ionization signal and electronics noise in the ICARUS liquid argon time projection chamber

Author: ICARUS collaboration, Abratenko, P., Abrego-Martinez, N., Aduszkiewicz, A., Akbar, F., Soplin, L. Aliaga, Pons, M. Artero, Asaadi, J., Badgett, W. F., Baibussinov, B., Behera, B., Bellini, V., Benocci, R., Berkman, S., Bertolucci, S., Betancourt, M., Bonesini, M., Boone, T., Bottino, B., Braggiotti, A., Brailsford, D., Brice, S. J., Brio, V., Brizzolari, C., Campani, H. S. Budd A., Campos, A., Carber, D., Carneiro, M., Terrazas, I. Caro, Carranza, H., Fernandez, F. Castillo, Castro, A., Centro, S., Cerati, G., Chatterjee, A., Cherdack, D., Cherubini, S., Chitirasreemadam, N., Cicerchia, M., Coan, T., Cocco, A., Convery, M. R., Cooper-Troendle, L., Copello, S., Dange, A. A., De Roeck, A., Di Noto, L., Di Stefano, C., DiFerdinando, D., Diwan, M., Dolan, S., Domine, L., Donati, S., Drielsma, F., Dyer, J., Dytman, S., Falcone, A., Farnese, C., Fava, A., Ferrari, A., Gallice, N., Garcia, F. G., Gatto, C., Gibin, D., Gioiosa, A., Gu, W., Guglielmi, A., Gurung, G., Hausner, H., Heggestuen, A., Howard, B., Howell, R., Ingratta, I., James, C., Jang, W., Jwa, Y. -J., Kashur, L., Ketchum, W., Kim, J. S., Koh, D. -H., Larkin, J., Li, Y., Mariani, C., Marshall, C. M., Martynenko, S., Mauri, N., McFarland, K. S., Menegolli, D. P. Méndez1 A., Meng, G., Miranda, O. G., Mogan, A., Moggi, N., Montagna, E., Montanari, C., Montanari, A., Mooney, M., Moreno-Granados, G., Mueller, J., Murphy, M., Naples, D., Nguyen, V. C. L., Palestini, S., Pallavicini, M., Paolone, V., Papaleo, R., Pasqualini, L., Patrizii, L., Paudel, L., Petrillo, G., Petta, C., Pia, V., Pietropaolo, F., Poppi, F., Pozzato, M., Putnam, G., Qian, X., Rappoldi, A., Raselli, G. L., Repetto, S., Resnati, F., Ricci, A. M., Riccobene, G., Richards, E., Rosenberg, M., Rossella, M., Roy, P., Rubbia, C., Saad, M., Saha, S., Sala, P., Samanta, S., Sapienza, P., Scaramelli, A., Scarpelli, A., Schmitz, D., Schukraft, A., Senadheera, D., Seo, S-H., Sergiampietri, F., Sirri, G., Smedley, J. S., Smith, J., Stanco, L., Stewart, J., Tanaka, H. A., Tapia, F., Tenti, M., Terao, K., Terranova, F., Togo, V., Torretta, D., Torti, M., Tortorici, F., Triozzi, R., Tsai, Y. -T., Tufanli, S., Usher, T., Varanini, F., Ventura, S., Vicenzi, M., Vignoli, C., Viren, B., Williams, Z., Wilson, R. J., Wilson, P., Wolfs, J., Wongjirad, T., Wood, A., Worcester, E., Worcester, M., Wospakrik, M., Yu, H., Yu, J., Zani, A., Zennamo, J., Zettlemoyer, J. C., Zhang, C., and Zucchelli, S.
Subjects: High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract: The ICARUS liquid argon time projection chamber (LArTPC) neutrino detector has been taking physics data since 2022 as part of the Short-Baseline Neutrino (SBN) Program. This paper details the equalization of the response to charge in the ICARUS time projection chamber (TPC), as well as data-driven tuning of the simulation of ionization charge signals and electronics noise. The equalization procedure removes non-uniformities in the ICARUS TPC response to charge in space and time. This work leverages the copious number of cosmic ray muons available to ICARUS at the surface. The ionization signal shape simulation applies a novel procedure that tunes the simulation to match what is measured in data. The end result of the equalization procedure and simulation tuning allows for a comparison of charge measurements in ICARUS between Monte Carlo simulation and data, showing good performance with minimal residual bias between the two.
Published: 2024

16. InsertDiffusion: Identity Preserving Visualization of Objects through a Training-Free Diffusion Architecture

Author: Mueller, Phillip, Wiese, Jannik, Craciun, Ioan, and Mikelsons, Lars
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Recent advancements in image synthesis are fueled by the advent of large-scale diffusion models. Yet, integrating realistic object visualizations seamlessly into new or existing backgrounds without extensive training remains a challenge. This paper introduces InsertDiffusion, a novel, training-free diffusion architecture that efficiently embeds objects into images while preserving their structural and identity characteristics. Our approach utilizes off-the-shelf generative models and eliminates the need for fine-tuning, making it ideal for rapid and adaptable visualizations in product design and marketing. We demonstrate superior performance over existing methods in terms of image realism and alignment with input conditions. By decomposing the generation task into independent steps, InsertDiffusion offers a scalable solution that extends the capabilities of diffusion models for practical applications, achieving high-quality visualizations that maintain the authenticity of the original objects.
Published: 2024

17. The evolution of Jupiter and Saturn with helium rain

Author: Howard, Saburo, Müller, Simon, and Helled, Ravit
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: Phase separation between hydrogen and helium at high pressures and temperatures leads to the rainout of helium in the deep interiors of Jupiter and Saturn. This process, also known as "helium rain", affects their long-term evolution. Therefore, modelling the evolution and internal structure of Jupiter and Saturn (and giant exoplanets) relies on the phase diagram of hydrogen and helium. In this work, we simulate the evolution of Jupiter and Saturn with helium rain by applying different phase diagrams of hydrogen and helium. We find that consistency between Jupiter s evolution and the Galileo measurement of its atmospheric helium abundance is achieved only if a shift in temperature in the existing phase diagrams is applied (-1250 K, +350 K or -3850 K depending on the used phase diagram). We next use the shifted phase diagrams to model Saturn s evolution and find consistent solutions for both planets. We confirm that demixing in Jupiter is modest while in Saturn, the process of helium rain is significant. We find that Saturn has a large helium gradient and a helium ocean. Saturn s atmospheric helium mass fraction is estimated to be between 0.13 and 0.16. We also investigate how the used hydrogen-helium equation of state and atmospheric model affect the planetary evolution and find that the predicted cooling times can change by several hundred million years. Constraining the level of super-adiabaticity in the helium gradient formed in Jupiter and Saturn remains challenging and should be investigated in detail in future research. We conclude that further explorations of the immiscibility between hydrogen and helium are valuable as this knowledge directly affects the evolution and current-state structure of Jupiter and Saturn. Finally, we argue that measuring Saturn s atmospheric helium content is crucial for constraining Saturn s evolution as well as the hydrogen-helium phase diagram., Comment: Accepted for publication in A&A
Published: 2024

18. Exploring the Potentials and Challenges of Deep Generative Models in Product Design Conception

Author: Mueller, Phillip and Mikelsons, Lars
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: The synthesis of product design concepts stands at the crux of early-phase development processes for technical products, traditionally posing an intricate interdisciplinary challenge. The application of deep learning methods, particularly Deep Generative Models (DGMs), holds the promise of automating and streamlining manual iterations and therefore introducing heightened levels of innovation and efficiency. However, DGMs have yet to be widely adopted into the synthesis of product design concepts. This paper aims to explore the reasons behind this limited application and derive the requirements for successful integration of these technologies. We systematically analyze DGM-families (VAE, GAN, Diffusion, Transformer, Radiance Field), assessing their strengths, weaknesses, and general applicability for product design conception. Our objective is to provide insights that simplify the decision-making process for engineers, helping them determine which method might be most effective for their specific challenges. Recognizing the rapid evolution of this field, we hope that our analysis contributes to a fundamental understanding and guides practitioners towards the most promising approaches. This work seeks not only to illuminate current challenges but also to propose potential solutions, thereby offering a clear roadmap for leveraging DGMs in the realm of product design conception.
Published: 2024

19. Supernova Pointing Capabilities of DUNE

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M, Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. 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O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Wenzel, H., Westerdale, S., Wetstein, M., Whalen, K., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: High Energy Physics - Experiment, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Nuclear Experiment, Physics - Instrumentation and Detectors
Abstract: The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on $^{40}$Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage., Comment: 25 pages, 16 figures
Published: 2024

20. Weak Chaos, Anomalous Diffusion, and Weak Ergodicity Breaking in Systems with Delay

Author: Albers, Tony, Hille, Lukas, Müller-Bender, David, and Radons, Günter
Subjects: Nonlinear Sciences - Chaotic Dynamics
Abstract: We demonstrate that standard delay systems with a linear instantaneous and a delayed nonlinear term show weak chaos, asymptotically subdiffusive behavior, and weak ergodicity breaking if the nonlinearity is chosen from a specific class of functions. In the limit of large constant delay times, anomalous behavior may not be observable due to exponentially large crossover times. A periodic modulation of the delay causes a strong reduction of the effective dimension of the chaotic phases, leads to hitherto unknown types of solutions, and the occurrence of anomalous diffusion already at short times. The observed anomalous behavior is caused by non-hyperbolic fixed points in function space., Comment: 7 pages, 5 figures
Published: 2024

21. Mitigating Catastrophic Forgetting in Language Transfer via Model Merging

Author: Alexandrov, Anton, Raychev, Veselin, Müller, Mark Niklas, Zhang, Ce, Vechev, Martin, and Toutanova, Kristina
Subjects: Computer Science - Machine Learning
Abstract: As open-weight large language models (LLMs) achieve ever more impressive performances across a wide range of tasks in English, practitioners aim to adapt these models to different languages. However, such language adaptation is often accompanied by catastrophic forgetting of the base model's capabilities, severely limiting the usefulness of the resulting model. We address this issue by proposing Branch-and-Merge (BaM), a new adaptation method based on iteratively merging multiple models, fine-tuned on a subset of the available training data. BaM is based on the insight that this yields lower magnitude but higher quality weight changes, reducing forgetting of the source domain while maintaining learning on the target domain. We demonstrate in an extensive empirical study on Bulgarian and German that BaM can significantly reduce forgetting while matching or even improving target domain performance compared to both standard continued pretraining and instruction finetuning across different model architectures.
Published: 2024

22. The XYZ ruby code: Making a case for a three-colored graphical calculus for quantum error correction in spacetime

Author: de la Fuente, Julio C. Magdalena, Old, Josias, Townsend-Teague, Alex, Rispler, Manuel, Eisert, Jens, and Müller, Markus
Subjects: Quantum Physics, Condensed Matter - Strongly Correlated Electrons, Mathematical Physics
Abstract: Analyzing and developing new quantum error-correcting schemes is one of the most prominent tasks in quantum computing research. In such efforts, introducing time dynamics explicitly in both analysis and design of error-correcting protocols constitutes an important cornerstone. In this work, we present a graphical formalism based on tensor networks to capture the logical action and error-correcting capabilities of any Clifford circuit with Pauli measurements. We showcase the formalism on new Floquet codes derived from topological subsystem codes, which we call XYZ ruby codes. Based on the projective symmetries of the building blocks of the tensor network we develop a framework of Pauli flows. Pauli flows allow for a graphical understanding of all quantities entering an error correction analysis of a circuit, including different types of QEC experiments, such as memory and stability experiments. We lay out how to derive a well-defined decoding problem from the tensor network representation of a protocol and its Pauli flows alone, independent of any stabilizer code or fixed circuit. Importantly, this framework applies to all Clifford protocols and encompasses both measurement- and circuit-based approaches to fault tolerance. We apply our method to our new family of dynamical codes which are in the same topological phase as the 2+1d color code, making them a promising candidate for low-overhead logical gates. In contrast to its static counterpart, the dynamical protocol applies a Z3 automorphism to the logical Pauli group every three timesteps. We highlight some of its topological properties and comment on the anyon physics behind a planar layout. Lastly, we benchmark the performance of the XYZ ruby code on a torus by performing both memory and stability experiments and find competitive circuit-level noise thresholds of 0.18%, comparable with other Floquet codes and 2+1d color codes., Comment: 59 pages, 26 figures
Published: 2024

23. On the cohomology of plus/minus Selmer groups of supersingular elliptic curves in weakly ramified base fields

Author: Forrás, Ben and Müller, Katharina
Subjects: Mathematics - Number Theory, 11G05, 11R23
Abstract: Let $E/\mathbb{Q}$ be an elliptic curve and let $p\ge 5$ be a prime of good supersingular reduction. We generalize results due to Meng Fai Lim proving Kida's formula and integrality results for characteristic elements of signed Selmer groups along the cyclotomic $\mathbb{Z}_p$-extension of weakly ramified base fields $K/\mathbb{Q}_p$., Comment: 29 pages
Published: 2024

24. Specialist vision-language models for clinical ophthalmology

Author: Holland, Robbie, Taylor, Thomas R. P., Holmes, Christopher, Riedl, Sophie, Mai, Julia, Patsiamanidi, Maria, Mitsopoulou, Dimitra, Hager, Paul, Müller, Philip, Scholl, Hendrik P. N., Bogunović, Hrvoje, Schmidt-Erfurth, Ursula, Rueckert, Daniel, Sivaprasad, Sobha, Lotery, Andrew J., and Menten, Martin J.
Subjects: Computer Science - Artificial Intelligence
Abstract: Clinicians spend a significant amount of time reviewing medical images and transcribing their findings regarding patient diagnosis, referral and treatment in text form. Vision-language models (VLMs), which automatically interpret images and summarize their findings as text, have enormous potential to alleviate clinical workloads and increase patient access to high-quality medical care. While foundational models have stirred considerable interest in the medical community, it is unclear whether their general capabilities translate to real-world clinical utility. In this work, we show that foundation VLMs markedly underperform compared to practicing ophthalmologists on specialist tasks crucial to the care of patients with age-related macular degeneration (AMD). To address this, we initially identified the essential capabilities required for image-based clinical decision-making, and then developed a curriculum to selectively train VLMs in these skills. The resulting model, RetinaVLM, can be instructed to write reports that significantly outperform those written by leading foundation medical VLMs in disease staging (F1 score of 0.63 vs. 0.11) and patient referral (0.67 vs. 0.39), and approaches the diagnostic performance of junior ophthalmologists (who achieve 0.77 and 0.78 on the respective tasks). Furthermore, in a reader study involving two senior ophthalmologists with up to 32 years of experience, RetinaVLM's reports were found to be similarly correct (78.6% vs. 82.1%) and complete (both 78.6%) as reports written by junior ophthalmologists with up to 10 years of experience. These results demonstrate that our curriculum-based approach provides a blueprint for specializing generalist foundation medical VLMs to handle real-world clinical tasks., Comment: Submitted to Nature Medicine
Published: 2024

25. The minimum neutron star mass in neutrino-driven supernova explosions

Author: Müller, Bernhard, Heger, Alexander, and Powell, Jade
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics, General Relativity and Quantum Cosmology
Abstract: Supernova theory has struggled to explain the lightest known neutron star candidate with an accurate mass determination, the $1.174\mathrm{M}_\odot$ companion in the eccentric compact binary system J0453+1559. To improve the theoretical lower limit for neutron star birth masses, we perform 3D supernova simulations for five stellar models close to the minimum mass for iron core collapse. We obtain a record-low neutron star mass of $1.192\mathrm{M}_\odot$ and a substantial kick of $\mathord{\sim} 100\,\mathrm{km}\,\mathrm{s}^{-1}$. Given residual uncertainties in stellar evolution, a neutron star origin for the $1.174\mathrm{M}_\odot$ object remains plausible., Comment: 6 pages, 3 figures. Submitted to Physical Review Letters
Published: 2024

26. Dynamical Measure Transport and Neural PDE Solvers for Sampling

Author: Sun, Jingtong, Berner, Julius, Richter, Lorenz, Zeinhofer, Marius, Müller, Johannes, Azizzadenesheli, Kamyar, and Anandkumar, Anima
Subjects: Computer Science - Machine Learning, Mathematics - Dynamical Systems, Mathematics - Optimization and Control, Mathematics - Probability, Statistics - Machine Learning
Abstract: The task of sampling from a probability density can be approached as transporting a tractable density function to the target, known as dynamical measure transport. In this work, we tackle it through a principled unified framework using deterministic or stochastic evolutions described by partial differential equations (PDEs). This framework incorporates prior trajectory-based sampling methods, such as diffusion models or Schr\"odinger bridges, without relying on the concept of time-reversals. Moreover, it allows us to propose novel numerical methods for solving the transport task and thus sampling from complicated targets without the need for the normalization constant or data samples. We employ physics-informed neural networks (PINNs) to approximate the respective PDE solutions, implying both conceptional and computational advantages. In particular, PINNs allow for simulation- and discretization-free optimization and can be trained very efficiently, leading to significantly better mode coverage in the sampling task compared to alternative methods. Moreover, they can readily be fine-tuned with Gauss-Newton methods to achieve high accuracy in sampling.
Published: 2024

27. Early Explorations of Lightweight Models for Wound Segmentation on Mobile Devices

Author: Borst, Vanessa, Dittus, Timo, Müller, Konstantin, and Kounev, Samuel
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract: The aging population poses numerous challenges to healthcare, including the increase in chronic wounds in the elderly. The current approach to wound assessment by therapists based on photographic documentation is subjective, highlighting the need for computer-aided wound recognition from smartphone photos. This offers objective and convenient therapy monitoring, while being accessible to patients from their home at any time. However, despite research in mobile image segmentation, there is a lack of focus on mobile wound segmentation. To address this gap, we conduct initial research on three lightweight architectures to investigate their suitability for smartphone-based wound segmentation. Using public datasets and UNet as a baseline, our results are promising, with both ENet and TopFormer, as well as the larger UNeXt variant, showing comparable performance to UNet. Furthermore, we deploy the models into a smartphone app for visual assessment of live segmentation, where results demonstrate the effectiveness of TopFormer in distinguishing wounds from wound-coloured objects. While our study highlights the potential of transformer models for mobile wound segmentation, future work should aim to further improve the mask contours., Comment: To be published in the "47th German Conference on Artificial Intelligence (KI 2024)"
Published: 2024

28. A survey on isothermal and isentropic Baer-Nunziato-type models

Author: Hantke, Maren, Müller, Siegfried, Sikstel, Aleksey, and Thein, Ferdinand
Subjects: Physics - Fluid Dynamics, Mathematical Physics, 76T30, 76T10, 74A15, 35L60, 82C26
Abstract: Multi-component Baer-Nunziato-type models for isothermal and isentropic fluids are investigated. These are given by balance equations for volume fractions, density and momentum for each component accounting for the relaxation to equilibrium by means of relaxation terms. Mathematical properties of the models are derived such as hyperbolicity and symmetrization. The fields are characterized and corresponding Riemann invariants are determined. Appropriate entropy-entropy flux pairs are derived taking into account the phasic energy equations including the heat flux. Physically meaningful constraints are presented that ensure the entropy inequality to hold. Instantaneous relaxation to equilibrium is investigated and appropriate algorithms are presented. Numerical results for the isothermal Baer-Nunziato model are compared to an isothermal Euler model and to an isothermal phase-field model., Comment: 44 pages, 3 figures
Published: 2024

29. The 2023/24 VIEWS Prediction Challenge: Predicting the Number of Fatalities in Armed Conflict, with Uncertainty

Author: Hegre, Håvard, Vesco, Paola, Colaresi, Michael, Vestby, Jonas, Timlick, Alexa, Kazmi, Noorain Syed, Becker, Friederike, Binetti, Marco, Bodentien, Tobias, Bohne, Tobias, Brandt, Patrick T., Chadefaux, Thomas, Drauz, Simon, Dworschak, Christoph, D'Orazio, Vito, Fritz, Cornelius, Frank, Hannah, Gleditsch, Kristian Skrede, Häffner, Sonja, Hofer, Martin, Klebe, Finn L., Macis, Luca, Malaga, Alexandra, Mehrl, Marius, Metternich, Nils W., Mittermaier, Daniel, Muchlinski, David, Mueller, Hannes, Oswald, Christian, Pisano, Paola, Randahl, David, Rauh, Christopher, Rüter, Lotta, Schincariol, Thomas, Seimon, Benjamin, Siletti, Elena, Tagliapietra, Marco, Thornhill, Chandler, Vegelius, Johan, and Walterskirchen, Julian
Subjects: Statistics - Applications, Computer Science - Machine Learning, Statistics - Computation, J.4, I.6.3, I.6.4, I.6.5
Abstract: This draft article outlines a prediction challenge where the target is to forecast the number of fatalities in armed conflicts, in the form of the UCDP `best' estimates, aggregated to the VIEWS units of analysis. It presents the format of the contributions, the evaluation metric, and the procedures, and a brief summary of the contributions. The article serves a function analogous to a pre-analysis plan: a statement of the forecasting models made publicly available before the true future prediction window commences. More information on the challenge, and all data referred to in this document, can be found at https://viewsforecasting.org/research/prediction-challenge-2023., Comment: Forecasting competition, conflict forecasting, forecasting with uncertainty
Published: 2024

30. Contrastive Learning of Preferences with a Contextual InfoNCE Loss

Author: Bertram, Timo, Fürnkranz, Johannes, and Müller, Martin
Subjects: Computer Science - Artificial Intelligence
Abstract: A common problem in contextual preference ranking is that a single preferred action is compared against several choices, thereby blowing up the complexity and skewing the preference distribution. In this work, we show how one can solve this problem via a suitable adaptation of the CLIP framework.This adaptation is not entirely straight-forward, because although the InfoNCE loss used by CLIP has achieved great success in computer vision and multi-modal domains, its batch-construction technique requires the ability to compare arbitrary items, and is not well-defined if one item has multiple positive associations in the same batch. We empirically demonstrate the utility of our adapted version of the InfoNCE loss in the domain of collectable card games, where we aim to learn an embedding space that captures the associations between single cards and whole card pools based on human selections. Such selection data only exists for restricted choices, thus generating concrete preferences of one item over a set of other items rather than a perfect fit between the card and the pool. Our results show that vanilla CLIP does not perform well due to the aforementioned intuitive issues. However, by adapting CLIP to the problem, we receive a model outperforming previous work trained with the triplet loss, while also alleviating problems associated with mining triplets.
Published: 2024

31. Learning With Generalised Card Representations for 'Magic: The Gathering'

Author: Bertram, Timo, Fürnkranz, Johannes, and Müller, Martin
Subjects: Computer Science - Artificial Intelligence
Abstract: A defining feature of collectable card games is the deck building process prior to actual gameplay, in which players form their decks according to some restrictions. Learning to build decks is difficult for players and models alike due to the large card variety and highly complex semantics, as well as requiring meaningful card and deck representations when aiming to utilise AI. In addition, regular releases of new card sets lead to unforeseeable fluctuations in the available card pool, thus affecting possible deck configurations and requiring continuous updates. Previous Game AI approaches to building decks have often been limited to fixed sets of possible cards, which greatly limits their utility in practice. In this work, we explore possible card representations that generalise to unseen cards, thus greatly extending the real-world utility of AI-based deck building for the game "Magic: The Gathering".We study such representations based on numerical, nominal, and text-based features of cards, card images, and meta information about card usage from third-party services. Our results show that while the particular choice of generalised input representation has little effect on learning to predict human card selections among known cards, the performance on new, unseen cards can be greatly improved. Our generalised model is able to predict 55\% of human choices on completely unseen cards, thus showing a deep understanding of card quality and strategy., Comment: Best paper award nominee at IEEE Conference on Games 2024
Published: 2024

32. Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets

Author: Bertram, Timo, Fürnkranz, Johannes, and Müller, Martin
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computer Science and Game Theory, Computer Science - Machine Learning
Abstract: In imperfect information games, the evaluation of a game state not only depends on the observable world but also relies on hidden parts of the environment. As accessing the obstructed information trivialises state evaluations, one approach to tackle such problems is to estimate the value of the imperfect state as a combination of all states in the information set, i.e., all possible states that are consistent with the current imperfect information. In this work, the goal is to learn a function that maps from the imperfect game information state to its expected value. However, constructing a perfect training set, i.e. an enumeration of the whole information set for numerous imperfect states, is often infeasible. To compute the expected values for an imperfect information game like \textit{Reconnaissance Blind Chess}, one would need to evaluate thousands of chess positions just to obtain the training target for a single state. Still, the expected value of a state can already be approximated with appropriate accuracy from a much smaller set of evaluations. Thus, in this paper, we empirically investigate how a budget of perfect information game evaluations should be distributed among training samples to maximise the return. Our results show that sampling a small number of states, in our experiments roughly 3, for a larger number of separate positions is preferable over repeatedly sampling a smaller quantity of states. Thus, we find that in our case, the quantity of different samples seems to be more important than higher target quality., Comment: KI 2024 - 47th German Conference on Artificial Intelligence
Published: 2024

33. Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess

Author: Bertram, Timo, Fürnkranz, Johannes, and Müller, Martin
Subjects: Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: In imperfect information games, the game state is generally not fully observable to players. Therefore, good gameplay requires policies that deal with the different information that is hidden from each player. To combat this, effective algorithms often reason about information sets; the sets of all possible game states that are consistent with a player's observations. While there is no way to distinguish between the states within an information set, this property does not imply that all states are equally likely to occur in play. We extend previous research on assigning weights to the states in an information set in order to facilitate better gameplay in the imperfect information game of Reconnaissance Blind Chess. For this, we train two different neural networks which estimate the likelihood of each state in an information set from historical game data. Experimentally, we find that a Siamese neural network is able to achieve higher accuracy and is more efficient than a classical convolutional neural network for the given domain. Finally, we evaluate an RBC-playing agent that is based on the generated weightings and compare different parameter settings that influence how strongly it should rely on them. The resulting best player is ranked 5th on the public leaderboard., Comment: Extended version of IEEE Conference on Games 2023 paper
Published: 2024
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34. Simulation of the impact of an additional corrugated structure impedance on the bursting dynamics in an electron storage ring

Author: Maier, Sebastian, Brosi, Miriam, Mochihashi, Akira, Nasse, Michael J., Schwarz, Markus, and Müller, Anke-Susanne
Subjects: Physics - Accelerator Physics
Abstract: In the case of single-digit picosecond bunch length, synchrotron light sources produce intense coherent radiation up to the THz range. The reduction of the bunch length by lowering the momentum compaction factor (low-$\alpha$) gives rise to the micro-bunching instability, which is on one hand a crucial roadblock in the X-ray range during to the resulting effective bunch lengthening but on the other hand also an opportunity for the generation of intense THz radiation if it can be controlled appropriately. In the KIT storage ring KARA (Karlsruhe Research Accelerator), two parallel plates with periodic rectangular corrugations are planned to be installed in an electron storage ring. These plates create an additional longitudinal impedance based on their geometry, which can affect the beam dynamics. The resulting impedance manipulation will be used to study and control the longitudinal electron beam dynamics and the emitted coherent synchrotron radiation (CSR). This paper presents the results of systematic studies in simulation of the impact of additional corrugated plate impedances on the longitudinal beam dynamics using the example of the KARA storage ring. If the periodicity of the wake function of the corrugated plates matches the size of the substructures in the longitudinal bunch profile, the instability threshold can be effectively manipulated. This extends intense THz radiation to different beam current regimes., Comment: 11 pages, 13 figures, to be published in Physical Review Accelerators and Beams
Published: 2024

35. Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis

Author: Molchanova, Nataliia, Cagol, Alessandro, Gordaliza, Pedro M., Ocampo-Pineda, Mario, Lu, Po-Jui, Weigel, Matthias, Chen, Xinjie, Depeursinge, Adrien, Granziera, Cristina, Müller, Henning, and Cuadra, Meritxell Bach
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: Uncertainty quantification (UQ) has become critical for evaluating the reliability of artificial intelligence systems, especially in medical image segmentation. This study addresses the interpretability of instance-wise uncertainty values in deep learning models for focal lesion segmentation in magnetic resonance imaging, specifically cortical lesion (CL) segmentation in multiple sclerosis. CL segmentation presents several challenges, including the complexity of manual segmentation, high variability in annotation, data scarcity, and class imbalance, all of which contribute to aleatoric and epistemic uncertainty. We explore how UQ can be used not only to assess prediction reliability but also to provide insights into model behavior, detect biases, and verify the accuracy of UQ methods. Our research demonstrates the potential of instance-wise uncertainty values to offer post hoc global model explanations, serving as a sanity check for the model. The implementation is available at https://github.com/NataliiaMolch/interpret-lesion-unc.
Published: 2024

36. Geospatial Trajectory Generation via Efficient Abduction: Deployment for Independent Testing

Author: Bavikadi, Divyagna, Aditya, Dyuman, Parkar, Devendra, Shakarian, Paulo, Mueller, Graham, Parvis, Chad, and Simari, Gerardo I.
Subjects: Computer Science - Logic in Computer Science, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract: The ability to generate artificial human movement patterns while meeting location and time constraints is an important problem in the security community, particularly as it enables the study of the analog problem of detecting such patterns while maintaining privacy. We frame this problem as an instance of abduction guided by a novel parsimony function represented as an aggregate truth value over an annotated logic program. This approach has the added benefit of affording explainability to an analyst user. By showing that any subset of such a program can provide a lower bound on this parsimony requirement, we are able to abduce movement trajectories efficiently through an informed (i.e., A*) search. We describe how our implementation was enhanced with the application of multiple techniques in order to be scaled and integrated with a cloud-based software stack that included bottom-up rule learning, geolocated knowledge graph retrieval/management, and interfaces with government systems for independently conducted government-run tests for which we provide results. We also report on our own experiments showing that we not only provide exact results but also scale to very large scenarios and provide realistic agent trajectories that can go undetected by machine learning anomaly detectors., Comment: Accepted at ICLP 2024
Published: 2024

37. Missed Causes and Ambiguous Effects: Counterfactuals Pose Challenges for Interpreting Neural Networks

Author: Mueller, Aaron
Subjects: Computer Science - Machine Learning, Computer Science - Computation and Language
Abstract: Interpretability research takes counterfactual theories of causality for granted. Most causal methods rely on counterfactual interventions to inputs or the activations of particular model components, followed by observations of the change in models' output logits or behaviors. While this yields more faithful evidence than correlational methods, counterfactuals nonetheless have key problems that bias our findings in specific and predictable ways. Specifically, (i) counterfactual theories do not effectively capture multiple independently sufficient causes of the same effect, which leads us to miss certain causes entirely; and (ii) counterfactual dependencies in neural networks are generally not transitive, which complicates methods for extracting and interpreting causal graphs from neural networks. We discuss the implications of these challenges for interpretability researchers and propose concrete suggestions for future work.
Published: 2024

38. Peering inside the black box: Learning the relevance of many-body functions in Neural Network potentials

Author: Bonneau, Klara, Lederer, Jonas, Templeton, Clark, Rosenberger, David, Müller, Klaus-Robert, and Clementi, Cecilia
Subjects: Physics - Computational Physics
Abstract: Machine learned potentials are becoming a popular tool to define an effective energy model for complex systems, either incorporating electronic structure effects at the atomistic resolution, or effectively renormalizing part of the atomistic degrees of freedom at a coarse-grained resolution. One of the main criticisms to machine learned potentials is that the energy inferred by the network is not as interpretable as in more traditional approaches where a simpler functional form is used. Here we address this problem by extending tools recently proposed in the nascent field of Explainable Artificial Intelligence (XAI) to coarse-grained potentials based on graph neural networks (GNN). We demonstrate the approach on three different coarse-grained systems including two fluids (methane and water) and the protein NTL9. On these examples, we show that the neural network potentials can be in practice decomposed in relevance contributions to different orders, that can be directly interpreted and provide physical insights on the systems of interest.
Published: 2024

39. Mapping Cardinality-based Feature Models to Weighted Automata over Featured Multiset Semirings (Extended Version)

Author: Müller, Robert, Weiß, Mathis, and Lochau, Malte
Subjects: Computer Science - Software Engineering
Abstract: Cardinality-based feature models permit to select multiple copies of the same feature, thus generalizing the notion of product configurations from subsets of Boolean features to multisets of feature instances. This increased expressiveness shapes a-priori infinite and non-convex configuration spaces, which renders established solution-space mappings based on Boolean presence conditions insufficient for cardinality-based feature models. To address this issue, we propose weighted automata over featured multiset semirings as a novel behavioral variability modeling formalism for cardinality-based feature models. The formalism uses multisets over features as a predefined semantic domain for transition weights. It permits to use any algebraic structure forming a proper semiring on multisets to aggregate the weights traversed along paths to map accepted words to multiset configurations. In particular, tropical semirings constitute a promising sub-class with a reasonable trade-off between expressiveness and computational tractability of canonical analysis problems. The formalism is strictly more expressive than featured transition systems, as it enables upper-bound multiplicity constraints depending on the length of words. We provide a tool implementation of the behavioral variability model and present preliminary experimental results showing applicability and computational feasibility of the proposed approach., Comment: This is the author's version of the work. The definitive version will be published in Proceedings of 28th ACM International Systems and Software Product Lines Conference (SPLC'24)
Published: 2024
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40. Designing Value-Centered Consent Interfaces: A Mixed-Methods Approach to Support Patient Values in Data-Sharing Decisions

Author: Leimstädtner, David, Sörries, Peter, and Müller-Birn, Claudia
Subjects: Computer Science - Human-Computer Interaction
Abstract: In the digital health domain, ethical data collection practices are crucial for ensuring the availability of quality datasets that drive medical advancement. Data donation, allowing patients to share their clinical data for secondary research use, presents a promising resource for such datasets. Yet, current consent interfaces mediating data-sharing decisions are found to favor data-collectors' values by leveraging cognitive biases in data-subjects towards higher data-sharing rates. This raises ethical concerns about the use of data collected, as well as concerning the quality of the resulting datasets. Seeking to establish patient-centered data collection practices in digital health, we investigate the design of consent interfaces that support end-users in making value-congruent health data-sharing decisions. Focusing our research efforts on the situated context of health data donation at the psychosomatic unit of a German university hospital, we demonstrate how a human-centered design can ground technology within the perspective of a vulnerable group. We employed an exploratory sequential mixed-method approach consisting of five phases: Participatory workshops explore patient values, informing the design of a proposed Value-Centered Consent Interface. An online experiment demonstrates our interface element's effect, increasing value-congruence in data-sharing decisions. Our proposed consent interface design is then adapted to the research context through a co-creation workshop with subject experts and a user evaluation with patients. Our work contributes to recent discourse in CSCW concerning ethical implications of new data practices within their socio-technological context by exploring patient values on medical data sharing, introducing a novel consent interface to support value-congruent decision-making, and providing a situated evaluation of the proposed interface with patients., Comment: 26 pages, 8 figures
Published: 2024

41. Spectroscopic Performance of Detectors for Athena's WFI: Measurements and Simulation

Author: Müller-Seidlitz, Johannes, Andritschke, Robert, Emberger, Valentin, Bonholzer, Michael, Hauser, Günter, Lechner, Peter, Mayr, Astrid, Reiffers, Jonas, Schweingruber, Anna, and Treberspurg, Wolfgang
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors
Abstract: The depleted p-channel field effect transistor is the chosen sensor type for the Wide Field Imager of the Athena mission. It will be used in two types of cameras. One will enable observations of a field of view of 40' x 40' by using an array of four 512 x 512 pixel sensors in a 2 x 2 configuration. A second, small one is designed to investigate bright, point-like sources with a time resolution of up to 40 microseconds. Sensors of final size, layout, and technology were fabricated, assembled and characterised. Also, first results from the flight production are available and confirm the excellent performance. In order to be able to estimate the future performance of degraded detectors, a simulation was developed that takes into account the non-analytical threshold effects on the basis of measurement results. We present the measurement analysis and the comparison of simulated and measured values as well as first attempts to use the Monte Carlo simulation to predict performance results based on noise measurements., Comment: SPIE Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray
Published: 2024

42. Predicting solvation free energies for neutral molecules in any solvent with openCOSMO-RS

Author: Müller, Simon, Nevolianis, Thomas, Garcia-Ratés, Miquel, Riplinger, Christoph, Leonhard, Kai, and Smirnova, Irina
Subjects: Physics - Chemical Physics, Condensed Matter - Soft Condensed Matter, Physics - Computational Physics
Abstract: The accurate prediction of solvation free energies is critical for understanding various phenomena in the liquid phase, including reaction rates, equilibrium constants, activity coefficients, and partition coefficients. Despite extensive research, precise prediction of solvation free energies remains challenging. In this study, we introduce openCOSMO-RS 24a, an improved version of the open-source COSMO-RS model, capable of predicting solvation free energies alongside other liquid-phase properties. We parameterize openCOSMO-RS 24a using quantum chemical calculations from ORCA 6.0, leveraging a comprehensive dataset that includes solvation free energies, partition coefficients, and infinite dilution activity coefficients for various solutes and solvents at 25 {\deg}C. Additionally, we develop a Quantitative Structure-Property Relationships model to predict molar volumes of the solvents, an essential requirement for predicting solvation free energies from structure alone. Our results show that openCOSMO-RS 24a achieves an average absolute deviation of 0.45 kcal/mol for solvation free energies, 0.76 for partition coefficients, and 0.51 for infinite dilution activity coefficients, demonstrating improvements over the previous openCOSMO-RS 22 parameterization and comparable results to COSMOtherm 24 TZVP. A new command line interface for openCOSMO-RS 24a was developed which allows easy acces to the solvation energy model directly from within ORCA 6.0. This represents a significant advancement in the predictive modeling of solvation free energies and other solution-phase properties, providing researchers with a robust tool for applications in chemical and materials science.
Published: 2024

43. Simulations of cluster ultra-diffuse galaxies in MOND

Author: Nagesh, Srikanth T., Freundlich, Jonathan, Famaey, Benoit, Bílek, Michal, Candlish, Graeme, Ibata, Rodrigo, and Müller, Oliver
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Ultra-diffuse galaxies (UDGs) in the Coma cluster have velocity dispersion profiles that are in full agreement with the predictions of Modified Newtonian Dynamics (MOND) in isolation. However, the external field effect (EFE) from the cluster seriously deteriorates this agreement. It has been suggested that this could be related to the fact that UDGs are out-of-equilibrium objects whose stars have been heated by the cluster tides or that they recently fell onto the cluster on radial orbits, such that their velocity dispersion may not reflect the EFE at their instantaneous distance from the cluster center. Here, we simulate UDGs within the Coma cluster in MOND, using the Phantom of Ramses (\textsc{por}) code, and show that if UDGs are initially at equilibrium within the cluster, tides are not sufficient to increase their velocity dispersions to values as high as the observed ones. On the other hand, if they are on a first radial infall onto the cluster, they can keep high velocity dispersions without being destroyed until their first pericentric passage. We conclude that, without alterations such as a screening of the EFE in galaxy clusters or much higher baryonic masses than currently estimated, in the MOND context UDGs must be out-of-equilibrium objects on their first infall onto the cluster., Comment: 10 Pages, 9 Figures, accepted by A&A
Published: 2024

44. Millimeter-millimeter-wave double-modulation double-resonance spectroscopy

Author: Zingsheim, Oliver, Bonah, Luis, Lewen, Frank, Thorwirth, Sven, Müller, Holger S. P., and Schlemmer, Stephan
Subjects: Physics - Chemical Physics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: A new millimeter- to millimeter-wave double-modulation double-resonance (MMW-MMW DM-DR) scheme has been applied to record spectra of two astronomically relevant complex organic molecules (COMs), propanal (C2H5CHO) and ethyl cyanide (C2H5CN), to demonstrate advantages of the DM-DR experimental technique. The DR technique helps to identify target transitions in a forest of lines and the implementation of a DM procedure (modulation of the pump and probe source) allows for confusion- and baseline-free spectra containing only the line(s) of interest. In particular the unambiguous assignment of weak and blended transitions in very dense MMW spectra is highlighted. Details of the observed Autler-Townes line splitting and possible future applications, such as automated analyses and adaptions of DM-DR methods to other experimental setups, are discussed.
Published: 2024
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45. SignCLIP: Connecting Text and Sign Language by Contrastive Learning

Author: Jiang, Zifan, Sant, Gerard, Moryossef, Amit, Müller, Mathias, Sennrich, Rico, and Ebling, Sarah
Subjects: Computer Science - Computation and Language
Abstract: We present SignCLIP, which re-purposes CLIP (Contrastive Language-Image Pretraining) to project spoken language text and sign language videos, two classes of natural languages of distinct modalities, into the same space. SignCLIP is an efficient method of learning useful visual representations for sign language processing from large-scale, multilingual video-text pairs, without directly optimizing for a specific task or sign language which is often of limited size. We pretrain SignCLIP on Spreadthesign, a prominent sign language dictionary consisting of ~500 thousand video clips in up to 44 sign languages, and evaluate it with various downstream datasets. SignCLIP discerns in-domain signing with notable text-to-video/video-to-text retrieval accuracy. It also performs competitively for out-of-domain downstream tasks such as isolated sign language recognition upon essential few-shot prompting or fine-tuning. We analyze the latent space formed by the spoken language text and sign language poses, which provides additional linguistic insights. Our code and models are openly available.
Published: 2024

46. The basis problem for modular forms for the Weil representation

Author: Müller, Manuel K. -H.
Subjects: Mathematics - Number Theory
Abstract: The vector valued theta series of a positive-definite even lattice is a modular form for the Weil representation of $\mathrm{SL}_2(\mathbb{Z})$. We show that the space of cusp forms for the Weil representation is generated by such functions. This gives a positive answer to Eichler's basis problem in this case. As applications we derive Waldspurger's result on the basis problem for scalar valued modular forms and give a new proof of the surjectivity of the Borcherds lift based on the analysis of local Picard groups., Comment: 42 pages
Published: 2024

47. Investigation of the rotational spectrum of CH$_3$$^{17}$OH and its tentative detection toward Sagittarius B2(N)

Author: Müller, Holger S. P., Ilyushin, Vadim V., Belloche, Arnaud, Lewen, Frank, and Schlemmer, Stephan
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics, Physics - Chemical Physics
Abstract: Methanol is an abundant molecule in space. The column density of CH$_3^{18}$OH is in some star-forming regions so high that the search for CH$_3^{17}$OH is promising. But only very few transition frequencies of CH$_3^{17}$OH with a microwave accuracy have been published thus far. We recorded the rotational spectrum of CH$_3^{17}$OH between 38 and 1095 GHz employing a methanol sample enriched in $^{17}$O to 20\%. A torsion-rotation Hamiltonian model based on the rho-axis method was employed to fit the data, as in our previous studies. We searched for rotational transitions of CH$_3^{17}$OH in the imaging spectral line survey ReMoCA obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) toward the high-mass star-forming region Sgr B2(N). The observed spectra were modeled under the assumption of local thermodynamic equilibrium (LTE). The assignments cover $0 \le J \le 45$, $K_a \le 16$, and mainly the $v_ t = 0$ and 1 torsional states. The Hamiltonian model describes our data well. The model was applied to derive a line list for radio-astronomical observations. We report a tentative detection of CH$_3^{17}$OH along with secure detections of the more abundant isotopologs of methanol toward Sgr B2(N2b). The derived column densities yield isotopic ratios $^{12}$C/$^{13}$C = 25, $^{16}$O/$^{18}$O = 240, and $^{18}$O/$^{17}$O = 3.3, which are consistent with values found earlier for other molecules in Sgr B2. The agreement between the $^{18}$O/$^{17}$O isotopic ratio that we obtained for methanol and the $^{18}$O/$^{17}$O ratios reported in the past for other molecules in Sgr B2(N) strongly supports our tentative interstellar identification of CH$_3^{17}$OH. The accuracy of the derived line list is sufficient for further radio astronomical searches for this methanol isotopolog toward other star-forming regions., Comment: 16 pages, including tables, figures, references and appendices. Abstract slightly shortened. Astronomy and Astrophysics, accepted for publication
Published: 2024

48. Low temperature proton irradiation with DEPFETs for Athena's Wide Field Imager

Author: Emberger, Valentin, Andritschke, Robert, Azhdarzadeh, Parviz, Hauser, Günter, Mayr, Astrid, Müller-Seidlitz, Johannes, Rezaei, Abbas, and Treberer-Treberspurg, Wolfgang
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors
Abstract: The Wide Field Imager (WFI), one of two instruments on ESA's next large X-ray mission Athena, is designed for imaging spectroscopy of X-rays in the range of 0.2 to 15 keV with a large field of view and high count rate capability. The focal plane consists of back-illuminated DEPFET (Depleted p-channel field effect transistor) sensors that have a high radiation tolerance and provide a near Fano-limited energy resolution. To achieve this, a very low noise readout is required, about 3 electrons ENC at beginning of life is foreseen. This makes the device very susceptible to any radiation induced worsening of the readout noise. The main mechanism of degradation will be the increase of dark current due to displacement damage caused primarily by high energy protons. To study the expected performance degradation, a prototype detector module with fully representative pixel layout and fabrication technology was irradiated with 62.4 MeV protons at the accelerator facility MedAustron in Wiener Neustadt. A total dose equivalent to 3.3 $\textstyle{10^{9}}$ 10-MeV protons/$\mathrm{cm^{2}}$ was applied in two steps. During, in-between and after the irradiations the detector remained at the operating temperature of 213 K and was fully biased and operated. Data was recorded to analyze the signal of all incident particles. We report on the increase of dark current after the irradiation and present the current related damage rate at 213 K. The effect of low temperature annealing at 213 K , 236 K, 253 K, 273 K, and 289 K is presented., Comment: to be published in SPIE Proceeding of Astronomical Telescopes + Instrumentation, 2024
Published: 2024

49. GAP9Shield: A 150GOPS AI-capable Ultra-low Power Module for Vision and Ranging Applications on Nano-drones

Author: Müller, Hanna, Kartsch, Victor, and Benini, Luca
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Signal Processing
Abstract: The evolution of AI and digital signal processing technologies, combined with affordable energy-efficient processors, has propelled the development of both hardware and software for drone applications. Nano-drones, which fit into the palm of the hand, are suitable for indoor environments and safe for human interaction; however, they often fail to deliver the required performance for complex tasks due to the lack of hardware providing sufficient sensing and computing performance. Addressing this gap, we present the GAP9Shield, a nano-drone-compatible module powered by the GAP9, a 150GOPS-capable SoC. The system also includes a 5MP OV5647 camera for high-definition imaging, a WiFi-BLE NINA module, and a 5D VL53L1-based ranging subsystem, which enhances obstacle avoidance capabilities. In comparison with similarly targeted state-of-the-art systems, GAP9Shield provides a 20% higher sample rate (RGB images) while offering a 20% weight reduction. In this paper, we also highlight the energy efficiency and processing power capabilities of GAP9 for object detection (YOLO), localization, and mapping, which can run within a power envelope of below 100 mW and at low latency (as 17 ms for object detection), highlighting the transformative potential of GAP9 for the new generation of nano-drone applications., Comment: This work has been accepted for publication at the European Robotics Forum 2024
Published: 2024

50. 1D $Z_2$ lattice gauge theory in periodic Gauss law sectors

Author: Sharma, Vaibhav and Mueller, Erich J
Subjects: Condensed Matter - Quantum Gases, Quantum Physics
Abstract: We calculate the properties of a 1D $Z_2$ lattice gauge theory in different Gauss law sectors, corresponding to different configurations of static charges set by the orientations of the gauge spins. Importantly, in quantum simulator experiments these sectors can be accessed without adding any additional physical particles or changing the Hamiltonian: The Gauss law sectors are simply set by the initial conditions. We study the interplay between conservation laws and interactions when the static charges are chosen to form periodic patterns. We classify the different Gauss law sectors and use the density matrix renormalization group to calculate the ground state compressibility, density profiles, charge density wave order parameters, and single particle correlation functions as a function of matter density. We find confined and deconfined phases, charge density waves, correlated insulators, and supersolids., Comment: 11 pages, 11 figures
Published: 2024

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