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1. Strategic Conceptual Theories and Sustainable Cooperation Among Stakeholders in E-government, E-participation, and Social Media

Author: Quintana Alba Garrote, Urquía-Grande Elena, and Jalón María Luisa Delgado
Subjects: e-government, e-participation, social media, conceptual theories, performance analysis, bibliometric análisis, science mapping, cooperation, researchers, o3 innovation, research and development, technological change, intellectual property rights: o33 technological change: choices and consequences, diffusion processes r5 regional government analysis: r50 general, Political science
Abstract: The objective of this study is twofold: on one hand, to analyze the current conceptual theories about e-government, e-participation, and social media. On the other hand, to analyze the cooperation among the most influential authors and its organizations where they belong. We will use different bibliometric software such as CitNetExplorer and SciMAT. Conceptual theories and cooperation among the most influential authors and its organizations will help us understand how the last trends in e-government and social media and the dynamics of the academic community work in the area. As interesting results, we can highlight that the technology acceptance model and the unified model of electronic government adoption are motor themes. Additionally, the analysis of the most influential authors and organizations shows that researchers such as Dwivedi from the University of Maryland and Jaeger from the Arizona State University in social media and e-government are the most significant authors. Furthermore, countries such as USA and Spain are leading the research on three topics, where Spanish researchers are growing considerably especially in social media related to e-government.
Published: 2022
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2. gSeaGen code by KM3NeT: an efficient tool to propagate muons simulated with CORSIKA

Author: Aiello, S., Albert, A., Alhebsi, A. R., Alshamsi, M., Garre, S. Alves, Ambrosone, A., Ameli, F., Andre, M., Androutsou, E., Aphecetche, L., Ardid, M., Ardid, S., Atmani, H., Aublin, J., Badaracco, F., Bailly-Salins, L., Bardačová, Z., Baret, B., Bariego-Quintana, A., Becherini, Y., Bendahman, M., Benfenati, F., Benhassi, M., Bennani, M., Benoit, D. M., Berbee, E., Bertin, V., Beyer, C., Biagi, S., Boettcher, M., Bonanno, D., Bouasla, A. B., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Bozza, R. M., Brânzaş, H., Bretaudeau, F., Breuhaus, M., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carenini, F., Carretero, V., Cartraud, T., Castaldi, P., Cecchini, V., Celli, S., Cerisy, L., Chabab, M., Chadolias, M., Chen, A., Cherubini, S., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Condorelli, A., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., Darras, Y., De Benedittis, A., De Martino, B., De Wasseige, G., Decoene, V., Del Rosso, I., Di Mauro, L. S., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Drakopoulou, E., Drouhin, D., Ducoin, J. -G., Dvornický, R., Eberl, T., Eckerová, E., Eddymaoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Ellajosyula, V., Enzenhöfer, A., Ferrara, G., Filipović, M. D., Filippini, F., Franciotti, D., Fusco, L. A., Gagliardini, S., Gal, T., Méndez, J. García, Soto, A. Garcia, Oliver, C. Gatius, Geißelbrecht, N., Genton, E., Ghaddari, H., Gialanella, L., Gibson, B. K., Giorgio, E., Goos, I., Goswami, P., Gozzini, S. R., Gracia, R., Guidi, C., Guillon, B., Gutiérrez, M., Haack, C., van Haren, H., Hassieiev, V., Heijboer, A., Hennig, L., Hernández-Rey, J. J., Ibnsalih, W. Idrissi, Illuminati, G., Joly, D., de Jong, M., de Jong, P., Jung, B. J., Kalaczyński, P., Kistauri, G., Kopper, C., Kouchner, A., Kueviakoe, V., Kulikovskiy, V., Kvatadze, R., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Stum, S. Le, Lehaut, G., Lemaître, V., Leonora, E., Lessing, N., Levi, G., Clark, M. Lindsey, Longhitano, F., Magnani, F., Majumdar, J., Malerba, L., Mamedov, F., Manfreda, A., Marconi, M., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Mastrodicasa, M., Mastroianni, S., Mauro, J., Miele, G., Migliozzi, P., Migneco, E., Mitsou, M. L., Mollo, C. M., Morales-Gallegos, L., Moretti, G., Moussa, A., Mateo, I. Mozun, Muller, R., Musone, M. R., Musumeci, M., Navas, S., Nayerhoda, A., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, Oliviero, V., Orlando, A., Oukacha, E., Paesani, D., González, J. Palacios, Papalashvili, G., Parisi, V., Gomez, E. J. Pastor, Păun, A. M., Păvălaş, G. E., Pelegris, I., Martínez, S. Peña, Perrin-Terrin, M., Pestel, V., Pestes, R., Piattelli, P., Poirè, C., Popa, V., Pradier, T., Prado, J., Pulvirenti, S., Quiroz-Rangel, C. A., Rahaman, U., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Riccobene, G., Robinson, J., Romanov, A., Šaina, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanfilippo, S., Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Schutte, H. M., Seneca, J., Sennan, N., Setter, B., Sgura, I., Shanidze, R., Sharma, A., Shitov, Y., Šimkovic, F., Simonelli, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Štekl, I., Taiuti, M., Tayalati, Y., Thiersen, H., Thoudam, S., de la Torre, P., Melo, I. Tosta e, Tragia, E., Trocmé, B., Tsourapis, V., Tudorache, A., Tzamariudaki, E., Ukleja, A., Vacheret, A., Valsecchi, V., Van Elewyck, V., Vannoye, G., Vasileiadis, G., de Sola, F. Vazquez, Veutro, A., Viola, S., Vivolo, D., van Vliet, A., Warnhofer, H., Weissbrod, S., de Wolf, E., Lhenry-Yvon, I., Zarpapis, G., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.
Subjects: High Energy Physics - Experiment, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Computational Physics
Abstract: The KM3NeT Collaboration has tackled a common challenge faced by the astroparticle physics community, namely adapting the experiment-specific simulation software to work with the CORSIKA air shower simulation output. The proposed solution is an extension of the open-source code gSeaGen, allowing for the transport of muons generated by CORSIKA to a detector of any size at an arbitrary depth. The gSeaGen code was not only extended in terms of functionalities but also underwent a thorough redesign of the muon propagation routine, resulting in a more accurate and efficient simulation. This paper presents the capabilities of the new gSeaGen code as well as prospects for further developments., Comment: 27 pages, 13 figures
Published: 2024

3. Observation of disorder-free localization and efficient disorder averaging on a quantum processor

Author: Gyawali, Gaurav, Cochran, Tyler, Lensky, Yuri, Rosenberg, Eliott, Karamlou, Amir H., Kechedzhi, Kostyantyn, Berndtsson, Julia, Westerhout, Tom, Asfaw, Abraham, Abanin, Dmitry, Acharya, Rajeev, Beni, Laleh Aghababaie, Andersen, Trond I., Ansmann, Markus, Arute, Frank, Arya, Kunal, Astrakhantsev, Nikita, Atalaya, Juan, Babbush, Ryan, Ballard, Brian, Bardin, Joseph C., Bengtsson, Andreas, Bilmes, Alexander, Bortoli, Gina, Bourassa, Alexandre, Bovaird, Jenna, Brill, Leon, Broughton, Michael, Browne, David A., Buchea, Brett, Buckley, Bob B., Buell, David A., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Cabrera, Anthony, Campero, Juan, Chang, Hung-Shen, Chen, Zijun, Chiaro, Ben, Claes, Jahan, Cleland, Agnetta Y., Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Das, Sayan, Debroy, Dripto M., De Lorenzo, Laura, Barba, Alexander Del Toro, Demura, Sean, Di Paolo, Agustin, Donohoe, Paul, Drozdov, Ilya, Dunsworth, Andrew, Earle, Clint, Eickbusch, Alec, Elbag, Aviv Moshe, Elzouka, Mahmoud, Erickson, Catherine, Faoro, Lara, Fatemi, Reza, Ferreira, Vinicius S., Burgos, Leslie Flores, Forati, Ebrahim, Fowler, Austin G., Foxen, Brooks, Ganjam, Suhas, Gasca, Robert, Giang, William, Gidney, Craig, Gilboa, Dar, Gosula, Raja, Dau, Alejandro Grajales, Graumann, Dietrich, Greene, Alex, Gross, Jonathan A., Habegger, Steve, Hamilton, Michael C., Hansen, Monica, Harrigan, Matthew P., Harrington, Sean D., Heslin, Stephen, Heu, Paula, Hill, Gordon, Hilton, Jeremy, Hoffmann, Markus R., Huang, Hsin-Yuan, Huff, Ashley, Huggins, William J., Ioffe, Lev B., Isakov, Sergei V., Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Jordan, Stephen, Joshi, Chaitali, Juhas, Pavol, Kafri, Dvir, Kang, Hui, Khaire, Trupti, Khattar, Tanuj, Khezri, Mostafa, Kieferová, Mária, Kim, Seon, Klimov, Paul V., Klots, Andrey R., Kobrin, Bryce, Korotkov, Alexander N., Kostritsa, Fedor, Kreikebaum, John Mark, Kurilovich, Vladislav D., Landhuis, David, Lange-Dei, Tiano, Langley, Brandon W., Laptev, Pavel, Lau, Kim-Ming, Guevel, Loïck Le, Ledford, Justin, Lee, Joonho, Lee, Kenny, Lester, Brian J., Li, Wing Yan, Lill, Alexander T., Liu, Wayne, Livingston, William P., Locharla, Aditya, Lundahl, Daniel, Lunt, Aaron, Madhuk, Sid, Maloney, Ashley, Mandrà, Salvatore, Martin, Leigh S., Martin, Steven, Martin, Orion, Maxfield, Cameron, McClean, Jarrod R., McEwen, Matt, Meeks, Seneca, Megrant, Anthony, Mi, Xiao, Miao, Kevin C., Mieszala, Amanda, Molina, Sebastian, Montazeri, Shirin, Morvan, Alexis, Movassagh, Ramis, Neill, Charles, Nersisyan, Ani, Newman, Michael, Nguyen, Anthony, Nguyen, Murray, Ni, Chia-Hung, Niu, Murphy Yuezhen, Oliver, William D., Ottosson, Kristoffer, Pizzuto, Alex, Potter, Rebecca, Pritchard, Orion, Pryadko, Leonid P., Quintana, Chris, Reagor, Matthew J., Rhodes, David M., Roberts, Gabrielle, Rocque, Charles, Rubin, Nicholas C., Saei, Negar, Sankaragomathi, Kannan, Satzinger, Kevin J., Schurkus, Henry F., Schuster, Christopher, Shearn, Michael J., Shorter, Aaron, Shutty, Noah, Shvarts, Vladimir, Sivak, Volodymyr, Skruzny, Jindra, Small, Spencer, Smith, W. Clarke, Springer, Sofia, Sterling, George, Suchard, Jordan, Szalay, Marco, Szasz, Aaron, Sztein, Alex, Thor, Douglas, Torunbalci, M. Mert, Vaishnav, Abeer, Vdovichev, Sergey, Vidal, Guifré, Heidweiller, Catherine Vollgraff, Waltman, Steven, Wang, Shannon X., White, Theodore, Wong, Kristi, Woo, Bryan W. K., Xing, Cheng, Yao, Z. Jamie, Yeh, Ping, Ying, Bicheng, Yoo, Juhwan, Yosri, Noureldin, Young, Grayson, Zalcman, Adam, Zhang, Yaxing, Zhu, Ningfeng, Zobrist, Nicholas, Boixo, Sergio, Kelly, Julian, Lucero, Erik, Chen, Yu, Smelyanskiy, Vadim, Neven, Hartmut, Kovrizhin, Dmitry, Knolle, Johannes, Halimeh, Jad C., Aleiner, Igor, Moessner, Roderich, and Roushan, Pedram
Subjects: Quantum Physics, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Strongly Correlated Electrons, High Energy Physics - Lattice
Abstract: One of the most challenging problems in the computational study of localization in quantum manybody systems is to capture the effects of rare events, which requires sampling over exponentially many disorder realizations. We implement an efficient procedure on a quantum processor, leveraging quantum parallelism, to efficiently sample over all disorder realizations. We observe localization without disorder in quantum many-body dynamics in one and two dimensions: perturbations do not diffuse even though both the generator of evolution and the initial states are fully translationally invariant. The disorder strength as well as its density can be readily tuned using the initial state. Furthermore, we demonstrate the versatility of our platform by measuring Renyi entropies. Our method could also be extended to higher moments of the physical observables and disorder learning.
Published: 2024

4. BN-SCAFFOLD: controlling the drift of Batch Normalization statistics in Federated Learning

Author: Quintana, Gonzalo Iñaki, Vancamberg, Laurence, Jugnon, Vincent, Mougeot, Mathilde, and Desolneux, Agnès
Subjects: Computer Science - Machine Learning
Abstract: Federated Learning (FL) is gaining traction as a learning paradigm for training Machine Learning (ML) models in a decentralized way. Batch Normalization (BN) is ubiquitous in Deep Neural Networks (DNN), as it improves convergence and generalization. However, BN has been reported to hinder performance of DNNs in heterogeneous FL. Recently, the FedTAN algorithm has been proposed to mitigate the effect of heterogeneity on BN, by aggregating BN statistics and gradients from all the clients. However, it has a high communication cost, that increases linearly with the depth of the DNN. SCAFFOLD is a variance reduction algorithm, that estimates and corrects the client drift in a communication-efficient manner. Despite its promising results in heterogeneous FL settings, it has been reported to underperform for models with BN. In this work, we seek to revive SCAFFOLD, and more generally variance reduction, as an efficient way of training DNN with BN in heterogeneous FL. We introduce a unified theoretical framework for analyzing the convergence of variance reduction algorithms in the BN-DNN setting, inspired of by the work of Wang et al. 2023, and show that SCAFFOLD is unable to remove the bias introduced by BN. We thus propose the BN-SCAFFOLD algorithm, which extends the client drift correction of SCAFFOLD to BN statistics. We prove convergence using the aforementioned framework and validate the theoretical results with experiments on MNIST and CIFAR-10. BN-SCAFFOLD equals the performance of FedTAN, without its high communication cost, outperforming Federated Averaging (FedAvg), SCAFFOLD, and other FL algorithms designed to mitigate BN heterogeneity.
Published: 2024

5. Search for quantum decoherence in neutrino oscillations with six detection units of KM3NeT/ORCA

Author: Aiello, S., Albert, A., Alhebsi, A. R., Alshamsi, M., Garre, S. Alves, Ambrosone, A., Ameli, F., Andre, M., Aphecetche, L., Ardid, M., Ardid, S., Atmani, H., Aublin, J., Badaracco, F., Bailly-Salins, L., Bardacova, Z., Baret, B., Bariego-Quintana, A., Becherini, Y., Bendahman, M., Benfenati, F., Benhassi, M., Bennani, M., Benoit, D. M., Berbee, E., Bertin, V., Biagi, S., Boettcher, M., Bonanno, D., Bouasla, A. B., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Bozza, R. M., Branzas, H., Bretaudeau, F., Breuhaus, M., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carenini, F., Carretero, V., Cartraud, T., Castaldi, P., Cecchini, V., Celli, S., Cerisy, L., Chabab, M., Chen, A., Cherubini, S., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Condorelli, A., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., De Benedittis, A., De Martino, B., De Wasseige, G., Decoene, V., Del Rosso, I., Di Mauro, L. S., Di Palma, I., Diaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Drakopoulou, E., Drouhin, D., Ducoin, J. -G., Dvornicky, R., Eberl, T., Eckerova, E., Eddymaoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Ellajosyula, V., Enzenhoefer, A., Ferrara, G., Filipovic, M. D., Filippini, F., Franciotti, D., Fusco, L. A., Gagliardini, S., Gal, T., Mendez, J. Garcia, Soto, A. Garcia, Oliver, C. Gatius, Geißelbrecht, N., Genton, E., Ghaddari, H., Gialanella, L., Gibson, B. K., Giorgio, E., Goos, I., Goswami, P., Gozzini, S. R., Gracia, R., Guidi, C., Guillon, B., Gutierrez, M., Haack, C., van Haren, H., Heijboer, A., Hennig, L., Hernandez-Rey, J. J., Ibnsalih, W. Idrissi, Illuminati, G., Joly, D., de Jong, M., de Jong, P., Jung, B. J., Kistauri, G., Kopper, C., Kouchner, A., Kovalev, Y. Y., Kueviakoe, V., Kulikovskiy, V., Kvatadze, R., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Stum, S. Le, Lehaut, G., Lemaitre, V., Leonora, E., Lessing, N., Levi, G., Clark, M. Lindsey, Longhitano, F., Magnani, F., Majumdar, J., Malerba, L., Mamedov, F., Manczak, J., Manfreda, A., Marconi, M., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Mastrodicasa, M., Mastroianni, S., Mauro, J., Miele, G., Migliozzi, P., Migneco, E., Mitsou, M. L., Mollo, C. M., Morales-Gallegos, L., Moussa, A., Mateo, I. Mozun, Muller, R., Musone, M. R., Musumeci, M., Navas, S., Nayerhoda, A., Nicolau, C. A., Nkosi, B., Fearraigh, B. O., Oliviero, V., Orlando, A., Oukacha, E., Gonzalez, D. Paesaniy J. Palacios, Papalashvili, G., Parisi, V., Gomez, E. J. Pastor, Pastore, C., Paun, A. M., Pavala, G. E., Martinez, S. Pena, Perrin-Terrin, M., Pestel, V., Pestes, R., Piattelli, P., Plavin, A., Poire, C., Popa, V., Pradier, T., Prado, J., Pulvirenti, S., Quiroz-Rangel, C. A., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Robinson, G. Riccobene. J., Romanov, A., Ros, E., Saina, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sanchez, Sanfilippo, S., Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Shitov, Y., Simkovic, F., Simonelli, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Stekl, I., Stellacci, S. M., Taiuti, M., Tayalati, Y., Thiersen, H., Thoudam, S., Tosta, I., Melo, e, Trocme, B., Tsourapis, V., Tudorache, A., Tzamariudaki, E., Ukleja, A., Vacheret, A., Valsecchi, V., Van Elewyck, V., Vannoye, G., Vasileiadis, G., de Sola, F. Vazquez, Veutro, A., Viola, S., Vivolo, D., van Vliet, A., de Wolf, E., Lhenry-Yvon, I., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zuniga, J., and Zywucka, N.
Subjects: High Energy Physics - Experiment
Abstract: Neutrinos described as an open quantum system may interact with the environment which introduces stochastic perturbations to their quantum phase. This mechanism leads to a loss of coherence along the propagation of the neutrino $-$ a phenomenon commonly referred to as decoherence $-$ and ultimately, to a modification of the oscillation probabilities. Fluctuations in space-time, as envisaged by various theories of quantum gravity, are a potential candidate for a decoherence-inducing environment. Consequently, the search for decoherence provides a rare opportunity to investigate quantum gravitational effects which are usually beyond the reach of current experiments. In this work, quantum decoherence effects are searched for in neutrino data collected by the KM3NeT/ORCA detector from January 2020 to November 2021. The analysis focuses on atmospheric neutrinos within the energy range of a few GeV to $100\,\mathrm{GeV}$. Adopting the open quantum system framework, decoherence is described in a phenomenological manner with the strength of the effect given by the parameters $\Gamma_{21}$ and $\Gamma_{31}$. Following previous studies, a dependence of the type $\Gamma_{ij} \propto (E/E_0)^n$ on the neutrino energy is assumed and the cases $n = -2,-1$ are explored. No significant deviation with respect to the standard oscillation hypothesis is observed. Therefore, $90\,\%$ CL upper limits are estimated as $\Gamma_{21} < 4.6\cdot 10^{-21}\,$GeV and $\Gamma_{31} < 8.4\cdot 10^{-21}\,$GeV for $n = -2$, and $\Gamma_{21} < 1.9\cdot 10^{-22}\,$GeV and $\Gamma_{31} < 2.7\cdot 10^{-22}\,$GeV for $n = -1$, respectively., Comment: 17 pages, 5 figures
Published: 2024

6. Visualizing Dynamics of Charges and Strings in (2+1)D Lattice Gauge Theories

Author: Cochran, Tyler A., Jobst, Bernhard, Rosenberg, Eliott, Lensky, Yuri D., Gyawali, Gaurav, Eassa, Norhan, Will, Melissa, Abanin, Dmitry, Acharya, Rajeev, Beni, Laleh Aghababaie, Andersen, Trond I., Ansmann, Markus, Arute, Frank, Arya, Kunal, Asfaw, Abraham, Atalaya, Juan, Babbush, Ryan, Ballard, Brian, Bardin, Joseph C., Bengtsson, Andreas, Bilmes, Alexander, Bourassa, Alexandre, Bovaird, Jenna, Broughton, Michael, Browne, David A., Buchea, Brett, Buckley, Bob B., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Cabrera, Anthony, Campero, Juan, Chang, Hung-Shen, Chen, Zijun, Chiaro, Ben, Claes, Jahan, Cleland, Agnetta Y., Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Curtin, Ben, Das, Sayan, Demura, Sean, De Lorenzo, Laura, Di Paolo, Agustin, Donohoe, Paul, Drozdov, Ilya, Dunsworth, Andrew, Eickbusch, Alec, Elbag, Aviv Moshe, Elzouka, Mahmoud, Erickson, Catherine, Ferreira, Vinicius S., Burgos, Leslie Flores, Forati, Ebrahim, Fowler, Austin G., Foxen, Brooks, Ganjam, Suhas, Gasca, Robert, Genois, Élie, Giang, William, Gilboa, Dar, Gosula, Raja, Dau, Alejandro Grajales, Graumann, Dietrich, Greene, Alex, Gross, Jonathan A., Habegger, Steve, Hansen, Monica, Harrigan, Matthew P., Harrington, Sean D., Heu, Paula, Higgott, Oscar, Hilton, Jeremy, Huang, Hsin-Yuan, Huff, Ashley, Huggins, William J., Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Joshi, Chaitali, Juhas, Pavol, Kafri, Dvir, Kang, Hui, Karamlou, Amir H., Kechedzhi, Kostyantyn, Khaire, Trupti, Khattar, Tanuj, Khezri, Mostafa, Kim, Seon, Klimov, Paul V., Kobrin, Bryce, Korotkov, Alexander N., Kostritsa, Fedor, Kreikebaum, John Mark, Kurilovich, Vladislav D., Landhuis, David, Lange-Dei, Tiano, Langley, Brandon W., Lau, Kim-Ming, Ledford, Justin, Lee, Kenny, Lester, Brian J., Guevel, Loïck Le, Li, Wing Yan, Lill, Alexander T., Livingston, William P., Locharla, Aditya, Lundahl, Daniel, Lunt, Aaron, Madhuk, Sid, Maloney, Ashley, Mandrà, Salvatore, Martin, Leigh S., Martin, Orion, Maxfield, Cameron, McClean, Jarrod R., McEwen, Matt, Meeks, Seneca, Megrant, Anthony, Miao, Kevin C., Molavi, Reza, Molina, Sebastian, Montazeri, Shirin, Movassagh, Ramis, Neill, Charles, Newman, Michael, Nguyen, Anthony, Nguyen, Murray, Ni, Chia-Hung, Niu, Murphy Yuezhen, Oliver, William D., Ottosson, Kristoffer, Pizzuto, Alex, Potter, Rebecca, Pritchard, Orion, Quintana, Chris, Ramachandran, Ganesh, Reagor, Matthew J., Rhodes, David M., Roberts, Gabrielle, Sankaragomathi, Kannan, Satzinger, Kevin J., Schurkus, Henry F., Shearn, Michael J., Shorter, Aaron, Shutty, Noah, Shvarts, Vladimir, Sivak, Volodymyr, Small, Spencer, Smith, W. Clarke, Springer, Sofia, Sterling, George, Suchard, Jordan, Szasz, Aaron, Sztein, Alex, Thor, Douglas, Torunbalci, M. Mert, Vaishnav, Abeer, Vargas, Justin, Vdovichev, Sergey, Vidal, Guifre, Heidweiller, Catherine Vollgraff, Waltman, Steven, Wang, Shannon X., Ware, Brayden, White, Theodore, Wong, Kristi, Woo, Bryan W. K., Xing, Cheng, Yao, Z. Jamie, Yeh, Ping, Ying, Bicheng, Yoo, Juhwan, Yosri, Noureldin, Young, Grayson, Zalcman, Adam, Zhang, Yaxing, Zhu, Ningfeng, Zobris, Nicholas, Boixo, Sergio, Kelly, Julian, Lucero, Erik, Chen, Yu, Smelyanskiy, Vadim, Neven, Hartmut, Gammon-Smith, Adam, Pollmann, Frank, Knap, Michael, and Roushan, Pedram
Subjects: Quantum Physics, Condensed Matter - Strongly Correlated Electrons, High Energy Physics - Lattice
Abstract: Lattice gauge theories (LGTs) can be employed to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-body interactions in materials. Studying dynamical properties of emergent phases can be challenging as it requires solving many-body problems that are generally beyond perturbative limits. We investigate the dynamics of local excitations in a $\mathbb{Z}_2$ LGT using a two-dimensional lattice of superconducting qubits. We first construct a simple variational circuit which prepares low-energy states that have a large overlap with the ground state; then we create particles with local gates and simulate their quantum dynamics via a discretized time evolution. As the effective magnetic field is increased, our measurements show signatures of transitioning from deconfined to confined dynamics. For confined excitations, the magnetic field induces a tension in the string connecting them. Our method allows us to experimentally image string dynamics in a (2+1)D LGT from which we uncover two distinct regimes inside the confining phase: for weak confinement the string fluctuates strongly in the transverse direction, while for strong confinement transverse fluctuations are effectively frozen. In addition, we demonstrate a resonance condition at which dynamical string breaking is facilitated. Our LGT implementation on a quantum processor presents a novel set of techniques for investigating emergent particle and string dynamics.
Published: 2024

7. Towards human-like kinematics in industrial robotic arms: a case study on a UR3 robot

Author: Wolniakowski, Adam, Miatliuk, Kanstantsin, Quintana, Jose J., Ferrer, Miguel A., and Diaz, Moises
Subjects: Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control
Abstract: Safety in industrial robotic environments is a hot research topic in the area of human-robot interaction (HRI). Up to now, a robotic arm on an assembly line interacts with other machines away from human workers. Nowadays, robotic arm manufactures are aimed to their robots could increasingly perform tasks collaborating with humans. One of the ways to improve this collaboration is by making the movement of robots more humanlike. This way, it would be easier for a human to foresee the movement of the robot and approach it without fear of contact. The main difference between the movement of a human and of a robotic arm is that the former has a bell-shaped speed profile while the latter has a uniform speed one. To generate this speed profile, the kinematic theory of rapid human movements and its Sigma-Lognormal model has been used. This model is widely used to explain most of the basic phenomena related to the control of human movements. Both human-like and robotic-like movements are transferred to the UR3 robot. In this paper we detail the how the UR3 robot was programmed to produce both kinds of movement. The dissimilarities result between the input motion and output motion to the robot confirm the possibility to develop human-like velocities in the UR3 robot., Comment: 6 pages, 5 figures
Published: 2024
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8. Energy efficiency analysis as a function of the working voltages in supercapacitors

Author: Quintana, Jose, Ramos, Alejandro, Diaz, Moises, and Nuez, Ignacio
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: Supercapacitors are increasingly used as energy storage elements. Unlike batteries, their state of charge has a considerable influence on their voltage in normal operation, allowing them to work from zero to their maximum voltage. In this work, a theoretical and practical analysis is proposed of the energy efficiency of these devices according to their working voltages. To this end, several supercapacitors were subjected to charge and discharge cycles until the measurements of current and voltage stabilized. At this point their energy efficiency was calculated. These charge-discharge cycles were carried out: i) without rest between charging and discharging; and ii) with a rest of several minutes between the two stages. Using the information obtained from the tests, the energy efficiency is shown plotted against the minimum and maximum working voltages. By consulting the data and the graphs, the ideal working voltages to optimize the energy efficiency of these devices can be obtained., Comment: 18 pages, 10 figures
Published: 2024
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9. A Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures

Author: Quintana, Fernando M., Maryada, Galindo, Pedro L., Donati, Elisa, Indiveri, Giacomo, and Perez-Peña, Fernando
Subjects: Computer Science - Neural and Evolutionary Computing, Computer Science - Hardware Architecture, Computer Science - Machine Learning
Abstract: Developing dedicated neuromorphic computing platforms optimized for embedded or edge-computing applications requires time-consuming design, fabrication, and deployment of full-custom neuromorphic processors.bTo ensure that initial prototyping efforts, exploring the properties of different network architectures and parameter settings, lead to realistic results it is important to use simulation frameworks that match as best as possible the properties of the final hardware. This is particularly challenging for neuromorphic hardware platforms made using mixed-signal analog/digital circuits, due to the variability and noise sensitivity of their components. In this paper, we address this challenge by developing a software spiking neural network simulator explicitly designed to account for the properties of mixed-signal neuromorphic circuits, including device mismatch variability. The simulator, called ARCANA (A Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures), is designed to reproduce the dynamics of mixed-signal synapse and neuron electronic circuits with autogradient differentiation for parameter optimization and GPU acceleration. We demonstrate the effectiveness of this approach by matching software simulation results with measurements made from an existing neuromorphic processor. We show how the results obtained provide a reliable estimate of the behavior of the spiking neural network trained in software, once deployed in hardware. This framework enables the development and innovation of new learning rules and processing architectures in neuromorphic embedded systems., Comment: 17 pages
Published: 2024

10. What is a Digital Twin Anyway? Deriving the Definition for the Built Environment from over 15,000 Scientific Publications

Author: Abdelrahman, Mahmoud, Macatulad, Edgardo, Lei, Binyu, Quintana, Matias, Miller, Clayton, and Biljecki, Filip
Subjects: Computer Science - Computation and Language
Abstract: The concept of digital twins has attracted significant attention across various domains, particularly within the built environment. However, there is a sheer volume of definitions and the terminological consensus remains out of reach. The lack of a universally accepted definition leads to ambiguities in their conceptualization and implementation, and may cause miscommunication for both researchers and practitioners. We employed Natural Language Processing (NLP) techniques to systematically extract and analyze definitions of digital twins from a corpus of 15,000 full-text articles spanning diverse disciplines in the built environment. The study compares these findings with insights from an expert survey that included 52 experts. The study identifies concurrence on the components that comprise a 'Digital Twin' from a practical perspective across various domains, contrasting them with those that do not, to identify deviations. We investigate the evolution of digital twin definitions over time and across different scales, including manufacturing, building, and urban/geospatial perspectives. We extracted the main components of Digital Twins using Text Frequency Analysis and N-gram analysis. Subsequently, we identified components that appeared in the literature and conducted a Chi-square test to assess the significance of each component in different domains. Our findings indicate that definitions differ based on the field of research in which they are conceived, but with many similarities across domains. One significant generalizable differentiation is related to whether a digital twin was used for High-Performance Real-Time (HPRT) or Long-Term Decision Support (LTDS) applications. We synthesized and contrasted the most representative definitions in each domain, culminating in a novel, data-driven definition specifically tailored for each context.
Published: 2024

11. Probing exotic cross-shell interactions at N=28 with single-neutron transfer on 47K

Author: Paxman, C. J., Matta, A., Catford, W. N., Lotay, G., Assié, M., Clément, E., Lemasson, A., Ramos, D., Orr, N. A., Galtarossa, F., Girard-Alcindor, V., Dudouet, J., Achouri, N. L., Ackermann, D., Barrientos, D., Beaumel, D., Bednarczyk, P., Benzoni, G., Bracco, A., Canete, L., Cederwall, B., Ciemala, M., Delahaye, P., Doherty, D. T., Domingo-Pardo, C., Fernández-Domínguez, B., Fernández, D., Flavigny, F., Fougères, C., de France, G., Franchoo, S., Gadea, A., Gibelin, J., González, V., Gottardo, A., Goyal, N., Hammache, F., Harkness-Brennan, L. J., Harrouz, D. S., Jacquot, B., Judson, D. S., Jungclaus, A., Kaşkaş, A., Korten, W., Labiche, M., Lalanne, L., Lenain, C., Leoni, S., Ljungvall, J., Lois-Fuentes, J., Lokotko, T., Lopez-Martens, A., Maj, A., Marqués, F. M., Martel, I., Menegazzo, R., Mengoni, D., Million, B., Nyberg, J., Pérez-Vidal, R. M., Plagnol, L., Podolyák, Zs., Pullia, A., Quintana, B., Regueira-Castro, D., Reiter, P., Rejmund, M., Rezynkina, K., Sanchis, E., Şenyiğit, M., de Séréville, N., Siciliano, M., Sohler, D., Stezowski, O., Thomas, J. -C., Utepov, A., Valiente-Dobón, J. J., Verney, D., and Zielińska, M.
Subjects: Nuclear Experiment
Abstract: We present the first measurement of the $^{47}$K($d,p\gamma$)$^{48}$K transfer reaction, performed in inverse kinematics using a reaccelerated beam of $^{47}$K. The level scheme of $^{48}$K has been greatly extended with nine new bound excited states identified and spectroscopic factors deduced. Detailed comparisons with SDPF-U and SDPF-MU shell-model calculations reveal a number of discrepancies with these results, and a preference for SDPF-MU is found. Intriguingly, an apparent systematic overestimation of spectroscopic factors and a poor reproduction of the energies for 1$^-$ states suggests that the mixing between the $\pi s^{\,\,\,1}_{1/2} d^{\,\,\,4}_{3/2}$ and $\pi s^{\,\,\,2}_{1/2} d^{\,\,\,3}_{3/2}$ proton configurations in $^{48}$K is not correctly described using current interactions, challenging our descriptions of light $N=28$ nuclei., Comment: 7 pages, 3 figures, 1 table
Published: 2024

12. An Adaptive Difference Method for Variable-Order Diffusion Equations

Author: Quintana-Murillo, Joaquín and Yuste, Santos Bravo
Subjects: Mathematics - Numerical Analysis, Condensed Matter - Statistical Mechanics, Physics - Computational Physics, G.1.9, G.1.4, G.1.0
Abstract: An adaptive finite difference scheme for variable-order fractional-time subdiffusion equations in the Caputo form is studied. The fractional time derivative is discretized by the L1 procedure but using nonhomogeneous timesteps. The size of these timesteps is chosen by an adaptive algorithm in order to keep the local error bounded around a preset value, a value that can be chosen at will. For some types of problems this adaptive method is much faster than the corresponding usual method with fixed timesteps while keeping the local error of the numerical solution around the preset values. These findings turns out to be similar to those found for constant-order fractional diffusion equations., Comment: 19 pages, 8 figures
Published: 2024
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13. Parallel Reduced Order Modeling for Digital Twins using High-Performance Computing Workflows

Author: de Parga, S. Ares, Bravo, J. R., Sibuet, N., Hernandez, J. A., Rossi, R., Boschert, Stefan, Quintana-Ortí, Enrique S., Tomás, Andrés E., Tatu, Cristian Cătălin, Vázquez-Novoa, Fernando, Ejarque, Jorge, and Badia, Rosa M.
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: The integration of Reduced Order Models (ROMs) with High-Performance Computing (HPC) is critical for developing digital twins, particularly for real-time monitoring and predictive maintenance of industrial systems. This paper describes a comprehensive, HPC-enabled workflow for developing and deploying projection-based ROMs (PROMs). We use PyCOMPSs' parallel framework to efficiently execute ROM training simulations, employing parallel Singular Value Decomposition (SVD) algorithms such as randomized SVD, Lanczos SVD, and full SVD based on Tall-Skinny QR. In addition, we introduce a partitioned version of the hyper-reduction scheme known as the Empirical Cubature Method. Despite the widespread use of HPC for PROMs, there is a significant lack of publications detailing comprehensive workflows for building and deploying end-to-end PROMs in HPC environments. Our workflow is validated through a case study focusing on the thermal dynamics of a motor. The PROM is designed to deliver a real-time prognosis tool that could enable rapid and safe motor restarts post-emergency shutdowns under different operating conditions for further integration into digital twins or control systems. To facilitate deployment, we use the HPC Workflow as a Service strategy and Functional Mock-Up Units to ensure compatibility and ease of integration across HPC, edge, and cloud environments. The outcomes illustrate the efficacy of combining PROMs and HPC, establishing a precedent for scalable, real-time digital twin applications across multiple industries.
Published: 2024

14. Cybersecurity Skills, Knowledge and Abilities for Criminal Justice Professionals: An Exploratory Study of Practitioners' Perspectives

Author: Kate Quintana, Caroline Sutton Chubb, Daniel Olson, and Anna E. Kosloski
Abstract: Cybersecurity has become increasingly important not only in the technology sector but in criminal justice professions as well, and significant challenges have arisen as a result. However, these challenges are not well discussed in the literature. To address this gap, and to study the cybersecurity trends impacting criminal justice professionals and the skills, knowledge and abilities criminal justice students need to succeed upon graduation, this research focuses on the role cybersecurity plays in the jobs that compose the main components of the criminal justice system and adjacent areas: law enforcement, the judicial process, corrections, social work, and military. This research utilizes semi-structured interviews with current and recently retired practitioners. Findings from this study revealed eight broad themes, many of which are complementary including changing technologies, generational gaps, over reliance on information technology professionals, and best practices for education composed of experiential learning, soft skills, specialized curriculum and interdisciplinary approaches.
Published: 2024

15. Microunidades, ejército industrial de reserva y producción mercantil simple

Author: Salas, Carlos, Quintana, Luis, and Villagra, Alberto
Published: 2024

16. Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants

Author: Matt, Georg E, Greiner, Lydia, Record, Rachael A, Wipfli, Heather, Long, Jamie, Dodder, Nathan G, Hoh, Eunha, Galvez, Nicolas Lopez, Novotny, Thomas E, Quintana, Penelope JE, Destaillats, Hugo, Tang, Xiaochen, Snijders, Antoine M, Mao, Jian-Hua, Hang, Bo, Schick, Suzaynn, Jacob, Peyton, Talbot, Prue, Mahabee-Gittens, E Melinda, Merianos, Ashley L, Northrup, Thomas F, Gundel, Lara, and Benowitz, Neal L
Subjects: Policy and Administration, Public Health, Health Sciences, Human Society, Social Determinants of Health, Tobacco Smoke and Health, Health Effects of Indoor Air Pollution, Prevention, Tobacco, 2.2 Factors relating to the physical environment, 3.2 Interventions to alter physical and biological environmental risks, Stroke, Respiratory, Good Health and Well Being, Tobacco Smoke Pollution, Humans, Smoke-Free Policy, Environmental Exposure, Air Pollution, Indoor, Health Policy, Smoking, Secondhand smoke, Carcinogens, Economics, End game, Public policy
Abstract: Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhand and thirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.
Published: 2024

17. Quantum error correction below the surface code threshold

Author: Acharya, Rajeev, Aghababaie-Beni, Laleh, Aleiner, Igor, Andersen, Trond I., Ansmann, Markus, Arute, Frank, Arya, Kunal, Asfaw, Abraham, Astrakhantsev, Nikita, Atalaya, Juan, Babbush, Ryan, Bacon, Dave, Ballard, Brian, Bardin, Joseph C., Bausch, Johannes, Bengtsson, Andreas, Bilmes, Alexander, Blackwell, Sam, Boixo, Sergio, Bortoli, Gina, Bourassa, Alexandre, Bovaird, Jenna, Brill, Leon, Broughton, Michael, Browne, David A., Buchea, Brett, Buckley, Bob B., Buell, David A., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Cabrera, Anthony, Campero, Juan, Chang, Hung-Shen, Chen, Yu, Chen, Zijun, Chiaro, Ben, Chik, Desmond, Chou, Charina, Claes, Jahan, Cleland, Agnetta Y., Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Curtin, Ben, Das, Sayan, Davies, Alex, De Lorenzo, Laura, Debroy, Dripto M., Demura, Sean, Devoret, Michel, Di Paolo, Agustin, Donohoe, Paul, Drozdov, Ilya, Dunsworth, Andrew, Earle, Clint, Edlich, Thomas, Eickbusch, Alec, Elbag, Aviv Moshe, Elzouka, Mahmoud, Erickson, Catherine, Faoro, Lara, Farhi, Edward, Ferreira, Vinicius S., Burgos, Leslie Flores, Forati, Ebrahim, Fowler, Austin G., Foxen, Brooks, Ganjam, Suhas, Garcia, Gonzalo, Gasca, Robert, Genois, Élie, Giang, William, Gidney, Craig, Gilboa, Dar, Gosula, Raja, Dau, Alejandro Grajales, Graumann, Dietrich, Greene, Alex, Gross, Jonathan A., Habegger, Steve, Hall, John, Hamilton, Michael C., Hansen, Monica, Harrigan, Matthew P., Harrington, Sean D., Heras, Francisco J. H., Heslin, Stephen, Heu, Paula, Higgott, Oscar, Hill, Gordon, Hilton, Jeremy, Holland, George, Hong, Sabrina, Huang, Hsin-Yuan, Huff, Ashley, Huggins, William J., Ioffe, Lev B., Isakov, Sergei V., Iveland, Justin, Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Jordan, Stephen, Joshi, Chaitali, Juhas, Pavol, Kafri, Dvir, Kang, Hui, Karamlou, Amir H., Kechedzhi, Kostyantyn, Kelly, Julian, Khaire, Trupti, Khattar, Tanuj, Khezri, Mostafa, Kim, Seon, Klimov, Paul V., Klots, Andrey R., Kobrin, Bryce, Kohli, Pushmeet, Korotkov, Alexander N., Kostritsa, Fedor, Kothari, Robin, Kozlovskii, Borislav, Kreikebaum, John Mark, Kurilovich, Vladislav D., Lacroix, Nathan, Landhuis, David, Lange-Dei, Tiano, Langley, Brandon W., Laptev, Pavel, Lau, Kim-Ming, Guevel, Loïck Le, Ledford, Justin, Lee, Kenny, Lensky, Yuri D., Leon, Shannon, Lester, Brian J., Li, Wing Yan, Li, Yin, Lill, Alexander T., Liu, Wayne, Livingston, William P., Locharla, Aditya, Lucero, Erik, Lundahl, Daniel, Lunt, Aaron, Madhuk, Sid, Malone, Fionn D., Maloney, Ashley, Mandrá, Salvatore, Martin, Leigh S., Martin, Steven, Martin, Orion, Maxfield, Cameron, McClean, Jarrod R., McEwen, Matt, Meeks, Seneca, Megrant, Anthony, Mi, Xiao, Miao, Kevin C., Mieszala, Amanda, Molavi, Reza, Molina, Sebastian, Montazeri, Shirin, Morvan, Alexis, Movassagh, Ramis, Mruczkiewicz, Wojciech, Naaman, Ofer, Neeley, Matthew, Neill, Charles, Nersisyan, Ani, Neven, Hartmut, Newman, Michael, Ng, Jiun How, Nguyen, Anthony, Nguyen, Murray, Ni, Chia-Hung, O'Brien, Thomas E., Oliver, William D., Opremcak, Alex, Ottosson, Kristoffer, Petukhov, Andre, Pizzuto, Alex, Platt, John, Potter, Rebecca, Pritchard, Orion, Pryadko, Leonid P., Quintana, Chris, Ramachandran, Ganesh, Reagor, Matthew J., Rhodes, David M., Roberts, Gabrielle, Rosenberg, Eliott, Rosenfeld, Emma, Roushan, Pedram, Rubin, Nicholas C., Saei, Negar, Sank, Daniel, Sankaragomathi, Kannan, Satzinger, Kevin J., Schurkus, Henry F., Schuster, Christopher, Senior, Andrew W., Shearn, Michael J., Shorter, Aaron, Shutty, Noah, Shvarts, Vladimir, Singh, Shraddha, Sivak, Volodymyr, Skruzny, Jindra, Small, Spencer, Smelyanskiy, Vadim, Smith, W. Clarke, Somma, Rolando D., Springer, Sofia, Sterling, George, Strain, Doug, Suchard, Jordan, Szasz, Aaron, Sztein, Alex, Thor, Douglas, Torres, Alfredo, Torunbalci, M. Mert, Vaishnav, Abeer, Vargas, Justin, Vdovichev, Sergey, Vidal, Guifre, Villalonga, Benjamin, Heidweiller, Catherine Vollgraff, Waltman, Steven, Wang, Shannon X., Ware, Brayden, Weber, Kate, White, Theodore, Wong, Kristi, Woo, Bryan W. K., Xing, Cheng, Yao, Z. Jamie, Yeh, Ping, Ying, Bicheng, Yoo, Juhwan, Yosri, Noureldin, Young, Grayson, Zalcman, Adam, Zhang, Yaxing, Zhu, Ningfeng, and Zobrist, Nicholas
Subjects: Quantum Physics
Abstract: Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. In this work, we present two surface code memories operating below this threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of $\Lambda$ = 2.14 $\pm$ 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% $\pm$ 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of 2.4 $\pm$ 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 $\mu$s at distance-5 up to a million cycles, with a cycle time of 1.1 $\mu$s. To probe the limits of our error-correction performance, we run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or 3 $\times$ 10$^9$ cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms., Comment: 10 pages, 4 figures, Supplementary Information
Published: 2024

18. Fast Algorithms and Implementations for Computing the Minimum Distance of Quantum Codes

Author: Hernando, Fernando, Quintana-Ortí, Gregorio, and Grassl, Markus
Subjects: Quantum Physics, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Information Theory, Computer Science - Mathematical Software, 81-04, 81-08, 94B05, 94B60, 94B99, G.4
Abstract: The distance of a stabilizer quantum code is a very important feature since it determines the number of errors that can be detected and corrected. We present three new fast algorithms and implementations for computing the symplectic distance of the associated classical code. Our new algorithms are based on the Brouwer-Zimmermann algorithm. Our experimental study shows that these new implementations are much faster than current state-of-the-art licensed implementations on single-core processors, multicore processors, and shared-memory multiprocessors. In the most computationally-demanding cases, the performance gain in the computational time can be larger than one order of magnitude. The experimental study also shows a good scalability on shared-memory parallel architectures., Comment: 14 pages, 7 figures, 1 table
Published: 2024

19. Measurement of neutrino oscillation parameters with the first six detection units of KM3NeT/ORCA

Author: KM3NeT Collaboration, Aiello, S., Albert, A., Alhebsi, A. R., Alshamsi, M., Garre, S. Alves, Ambrosone, A., Ameli, F., Andre, M., Aphecetche, L., Ardid, M., Ardid, S., Atmani, H., Aublin, J., Badaracco, F., Bailly-Salins, L., Bardačová, Z., Baret, B., Bariego-Quintana, A., Becherini, Y., Bendahman, M., Benfenati, F., Benhassi, M., Bennani, M., Benoit, D. M., Berbee, E., Bertin, V., Biagi, S., Boettcher, M., Bonanno, D., Bouasla, A. B., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Bozza, R. M., Brânzaş, H., Bretaudeau, F., Breuhaus, M., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carenini, F., Carretero, V., Cartraud, T., Castaldi, P., Cecchini, V., Celli, S., Cerisy, L., Chabab, M., Chen, A., Cherubini, S., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Condorelli, A., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., De Benedittis, A., De Martino, B., De Wasseige, G., Decoene, V., Del Rosso, I., Di Mauro, L. S., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Drakopoulou, E., Drouhin, D., Ducoin, J. -G., Dvornický, R., Eberl, T., Eckerová, E., Eddymaoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Ellajosyula, V., Enzenhöfer, A., Ferrara, G., Filipović, M. D., Filippini, F., Franciotti, D., Fusco, L. A., Gagliardini, S., Gal, T., Méndez, J. García, Soto, A. Garcia, Oliver, C. Gatius, Geißelbrecht, N., Genton, E., Ghaddari, H., Gialanella, L., Gibson, B. K., Giorgio, E., Goos, I., Goswami, P., Gozzini, S. R., Gracia, R., Guidi, C., Guillon, B., Gutiérrez, M., Haack, C., van Haren, H., Heijboer, A., Hennig, L., Hernández-Rey, J. J., Ibnsalih, W. Idrissi, Illuminati, G., Joly, D., de Jong, M., de Jong, P., Jung, B. J., Kistauri, G., Kopper, C., Kouchner, A., Kovalev, Y. Y., Kueviakoe, V., Kulikovskiy, V., Kvatadze, R., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazo, A., Stum, S. Le, Lehaut, G., Lemaítre, V., Leonora, E., Lessing, N., Levi, G., Clark, M. Lindsey, Longhitano, F., Magnani, F., Majumdar, J., Malerba, L., Mamedov, F., Mańczak, J., Manfreda, A., Marconi, M., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Mastrodicasa, M., Mastroianni, S., Mauro, J., Miele, G., Migliozzi, P., Migneco, E., Mitsou, M. L., Mollo, C. M., Morales-Gallegos, L., Moussa, A., Mateo, I. Mozun, Muller, R., Musone, M. R., Musumeci, M., Navas, S., Nayerhoda, A., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, Oliviero, V., Orlando, A., Oukacha, E., Paesani, D., González, J. Palacios, Papalashvili, G., Parisi, V., Gomez, E. J. Pastor, Păun, A. M., Păvălaş, G. E., Martínez, S. Peña, Perrin-Terrin, M., Pestel, V., Pestes, R., Piattelli, P., Plavin, A., Poirè, C., Popa, V., Pradier, T., Prado, J., Pulvirenti, S., Quiroz-Rangel, C. A., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Riccobene, G., Robinson, J., Romanov, A., Ros, E., Šaina, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanfilippo, S., Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Schutte, H. M., Seneca, J., Sgura, I., Shanidze, R., Sharma, A., Shitov, Y., Šimkovic, F., Simonelli, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Štekl, I., Stellacci, S. M., Taiuti, M., Tayalati, Y., Thiersen, H., Thoudam, S., Melo, I. Tosta e, Trocmé, B., Tsourapis, V., Tudorache, A., Tzamariudaki, E., Ukleja, A., Vacheret, A., Valsecchi, V., Van Elewyck, V., Vannoye, G., Vasileiadis, G., de Sola, F. Vazquez, Veutro, A., Viola, S., Vivolo, D., van Vliet, A., de Wolf, E., Yvon, I., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.
Subjects: High Energy Physics - Experiment
Abstract: KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on an initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photo-sensors. A high-purity neutrino sample was extracted, corresponding to an exposure of 433 kton-years. The sample of 5828 neutrino candidates is analysed following a binned log-likelihood method in the reconstructed energy and cosine of the zenith angle. The atmospheric oscillation parameters are measured to be $\sin^2\theta_{23}= 0.51^{+0.04}_{-0.05}$, and $ \Delta m^2_{31} = 2.18^{+0.25}_{-0.35}\times 10^{-3}~\mathrm{eV^2} \cup \{-2.25,-1.76\}\times 10^{-3}~\mathrm{eV^2}$ at 68\% CL. The inverted neutrino mass ordering hypothesis is disfavoured with a p-value of 0.25., Comment: 29 pages, 12 figures
Published: 2024

20. Solving Large Rank-Deficient Linear Least-Squares Problems on Shared-Memory CPU Architectures and GPU Architectures

Author: Chillarón, Mónica, Quintana-Ortí, Gregorio, Vidal, Vicente, and Martinsson, Per-Gunnar
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Performance, 68-04, 68W10, 15-04, G.1.3, G.4, C.4, D.1.3, F.2.1
Abstract: Solving very large linear systems of equations is a key computational task in science and technology. In many cases, the coefficient matrix of the linear system is rank-deficient, leading to systems that may be underdetermined, inconsistent, or both. In such cases, one generally seeks to compute the least squares solution that minimizes the residual of the problem, which can be further defined as the solution with smallest norm in cases where the coefficient matrix has a nontrivial nullspace. This work presents several new techniques for solving least squares problems involving coefficient matrices that are so large that they do not fit in main memory. The implementations include both CPU and GPU variants. All techniques rely on complete orthogonal decompositions that guarantee that both conditions of a least squares solution are met, regardless of the rank properties of the matrix. Specifically, they rely on the recently proposed "randUTV" algorithm that is particularly effective in strongly communication-constrained environments. A detailed precision and performance study reveals that the new methods, that operate on data stored on disk, are competitive with state-of-the-art methods that store all data in main memory., Comment: 26 pages, 12 figures
Published: 2024

21. Optimizing entanglement in two-qubit systems

Author: Luna-Hernandez, Salvio, Quintana, Claudia, and Rosas-Ortiz, Oscar
Subjects: Quantum Physics, Mathematical Physics
Abstract: We investigate entanglement in two-qubit systems using a geometric representation based on the minimum of essential parameters. The states are X-shaped and host pairs of identical populations while reducing the number of coherences involved. A geometric L-measure of entanglement is introduced as the distance between the points that represent entangled states and the closest point that defines separable states. Our results give a geometric meaning to the Hill-Wootters concurrence C since L coincides with C. Furthermore, unlike C, the measure L distinguishes the rank of states with maximum entanglement. We construct a time-dependent two-qubit state, traced out over the complementary components of a pure tetra-partite system, and find that its one-qubit states share the same entropy. The entanglement measure results bounded from above by the envelope of the minima of such entropy., Comment: 22 pages, 11 figures
Published: 2024

22. Analytical Emulator for the Linear Matter Power Spectrum from Physics-Informed Machine Learning

Author: Orjuela-Quintana, J. Bayron, Sapone, Domenico, and Nesseris, Savvas
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Current and future large-scale structure surveys aim to constrain cosmological parameters with unprecedented precision by analyzing vast amounts of data. This imposes a pressing need to develop fast and accurate methods for computing the matter power spectrum $P(k)$, or equivalently, the matter transfer function $T(k)$. In previous works, we introduced precise fitting formulas for these quantities within the standard cosmological model, including extensions such as the presence of massive neutrinos and modifications of gravity. However, these formulations overlooked a key characteristic imprinted in $P(k)$: the baryon acoustic oscillation signal. Here, we leverage our understanding of the well-known physics behind this oscillatory pattern to impose constraints on our genetic algorithm, a machine learning technique. By employing this ``physics-informed'' approach, we introduce an expression that accurately describes the matter transfer function with sub-percent mean accuracy. The high interpretability of the output allows for straightforward extensions of this formulation to other scenarios involving massive neutrinos and modifications of gravity. We anticipate that this formula will serve as a competitive fitting function for $P(k)$, meeting the accuracy requirements essential for cosmological analyses., Comment: 15 pages, 6 figures. Comments are very welcome!
Published: 2024

23. Para-Hermitian rational matrices

Author: Dopico, Froilán, Noferini, Vanni, Quintana, María C., and Van Dooren, Paul
Subjects: Mathematics - Numerical Analysis, 65F15, 15A18, 15A22, 15A54, 93B18, 93B20, 93B60
Abstract: In this paper we study para-Hermitian rational matrices and the associated structured rational eigenvalue problem (REP). Para-Hermitian rational matrices are square rational matrices that are Hermitian for all $z$ on the unit circle that are not poles. REPs are often solved via linearization, that is, using matrix pencils associated to the corresponding rational matrix that preserve the spectral structure. Yet, non-constant polynomial matrices cannot be para-Hermitian. Therefore, given a para-Hermitian rational matrix $R(z)$, we instead construct a $*$-palindromic linearization for $(1+z)R(z)$, whose eigenvalues that are not on the unit circle preserve the symmetries of the zeros and poles of $R(z)$. This task is achieved via M\"{o}bius transformations. We also give a constructive method that is based on an additive decomposition into the stable and anti-stable parts of $R(z)$. Analogous results are presented for para-skew-Hermitian rational matrices, i.e., rational matrices that are skew-Hermitian upon evaluation on those points of the unit circle that are not poles.
Published: 2024

24. Seasonal Changes in the Atmosphere of HD 80606b Observed with JWST's NIRSpec/G395H

Author: Sikora, James T., Rowe, Jason F., Splinter, Jared, Barat, Saugata, Dang, Lisa, Cowan, Nicolas B., Barclay, Thomas, Colón, Knicole D., Désert, Jean-Michel, Kane, Stephen R., Llama, Joe, Shivkumar, Hinna, Stassun, Keivan G., and Quintana, Elisa V.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: High-eccentricity gas giant planets serve as unique laboratories for studying the thermal and chemical properties of H/He-dominated atmospheres. One of the most extreme cases is HD 80606b -- a hot Jupiter orbiting a sun-like star with an eccentricity of $0.93$ -- which experiences an increase in incident flux of nearly three orders of magnitude as the star-planet separation decreases from $0.88\,{\rm au}$ at apoastron to $0.03\,{\rm au}$ at periastron. We observed the planet's periastron passage using \emph{JWST}'s NIRSpec/G395H instrument ($2.8-5.2\,{\rm \mu m}$) during a $21\,{\rm hr}$ window centered on the eclipse. We find that, as the planet passes through periastron, its emission spectrum transitions from a featureless blackbody to one in which CO and CH$_4$ absorption features are visible. We obtain significant detections of CH$_4$ during post-periapse phases at $3.7-4.8\sigma$ depending on the phase. Following periapse, CO and H$_2$O are also detected at $3.4\sigma$ and $3.1\sigma$, respectively. Furthermore, we rule out the presence of a strong temperature inversion near the IR photosphere -- predicted by GCMs to form temporarily during periapse passage -- based on the lack of obvious emission features throughout the observing window. Our study demonstrates the feasibility of studying hot Jupiter atmospheres using partial phase curves obtained with NIRSpec/G395H., Comment: 25 pages, 19 figures, 2 tables. Submitted to ApJ
Published: 2024

25. The VISTA Variables in the V\'ia L\'actea eXtended (VVVX) ESO public survey: Completion of the observations and legacy

Author: Saito, R. K., Hempel, M., Alonso-García, J., Lucas, P. W., Minniti, D., Alonso, S., Baravalle, L., Borissova, J., Caceres, C., Chené, A. N., Cross, N. J. G., Duplancic, F., Garro, E. R., Gómez, M., Ivanov, V. D., Kurtev, R., Luna, A., Majaess, D., Navarro, M. G., Pullen, J. B., Rejkuba, M., Sanders, J. L., Smith, L. C., Albino, P. H. C., Alonso, M. V., Amôres, E. B., Angeloni, R., Arias, J. I., Arnaboldi, M., Barbuy, B., Bayo, A., Beamin, J. C., Bedin, L. R., Bellini, A., Benjamin, R. A., Bica, E., Bonatto, C. J., Botan, E., Braga, V. F., Brown, D. A., Cabral, J. B., Camargo, D., Garatti, A. Caratti o, Carballo-Bello, J. A., Catelan, M., Chavero, C., Chijani, M. A., Clariá, J. J., Coldwell, G. V., Peña, C. Contreras, Ramos, R. Contreras, Corral-Santana, J. M., Cortés, C. C., Cortés-Contreras, M., Cruz, P., Daza-Perilla, I. V., Debattista, V. P., Dias, B., Donoso, L., D'Souza, R., Emerson, J. P., Federle, S., Fermiano, V., Fernandez, J., Fernández-Trincado, J. G., Ferreira, T., Lopes, C. E. Ferreira, Firpo, V., Flores-Quintana, C., Fraga, L., Froebrich, D., Galdeano, D., Gavignaud, I., Geisler, D., Gerhard, O. E., Gieren, W., Gonzalez, O. A., Gramajo, L. V., Gran, F., Granitto, P. M., Griggio, M., Guo, Z., Gurovich, S., Hilker, M., Jones, H. R. A., Kammers, R., Kuhn, M. A., Kumar, M. S . N., Kundu, R., Lares, M., Libralato, M., Lima, E., Maccarone, T. J., Cortés, P. Marchant, Martin, E. L., Masetti, N., Matsunaga, N., Mauro, F., McDonald, I., Mejías, A., Mesa, V., Milla-Castro, F. P., Minniti, J. H., Bidin, C. Moni, Montenegro, K., Morris, C., Motta, V., Navarete, F., Molina, C. Navarro, Nikzat, F., Castellón, J. L. Nilo, Obasi, C., Ortigoza-Urdaneta, M., Palma, T., Parisi, C., Ramírez, K. Pena, Pereyra, L., Perez, N., Petralia, I., Pichel, A., Pignata, G., Alegría, S. Ramírez, Rojas, A. F., Rojas, D., Roman-Lopes, A., Rovero, A. C., Saroon, S., Schmidt, E. O., Schröder, A. C., Schultheis, M., Sgró, M. A., Solano, E., Soto, M., Stecklum, B., Steeghs, D., Tamura, M., Tissera, P., Valcarce, A. A. R., Valotto, C. A., Vasquez, S., Villalon, C., Villanova, S., Cádiz, F. Vivanco, Bacigalupo, R. Zelada, Zijlstra, A., and Zoccali, M.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract: The ESO public survey VISTA Variables in the V\'ia L\'actea (VVV) surveyed the inner Galactic bulge and the adjacent southern Galactic disk from $2009-2015$. Upon its conclusion, the complementary VVV eXtended (VVVX) survey has expanded both the temporal as well as spatial coverage of the original VVV area, widening it from $562$ to $1700$ sq. deg., as well as providing additional epochs in $JHK_{\rm s}$ filters from $2016-2023$. With the completion of VVVX observations during the first semester of 2023, we present here the observing strategy, a description of data quality and access, and the legacy of VVVX. VVVX took $\sim 2000$ hours, covering about 4% of the sky in the bulge and southern disk. VVVX covered most of the gaps left between the VVV and the VISTA Hemisphere Survey (VHS) areas and extended the VVV time baseline in the obscured regions affected by high extinction and hence hidden from optical observations. VVVX provides a deep $JHK_{\rm s}$ catalogue of $\gtrsim 1.5\times10^9$ point sources, as well as a $K_{\rm s}$ band catalogue of $\sim 10^7$ variable sources. Within the existing VVV area, we produced a $5D$ map of the surveyed region by combining positions, distances, and proper motions of well-understood distance indicators such as red clump stars, RR Lyrae, and Cepheid variables. In March 2023 we successfully finished the VVVX survey observations that started in 2016, an accomplishment for ESO Paranal Observatory upon 4200 hours of observations for VVV+VVVX. The VVV+VVVX catalogues complement those from the Gaia mission at low Galactic latitudes and provide spectroscopic targets for the forthcoming ESO high-multiplex spectrographs MOONS and 4MOST., Comment: 17 pages, 11 figures (+ appendix). Accepted for publication in Astronomy and Astrophysics in section 14: Catalogs and data
Published: 2024
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26. Impact of Neutron Irradiation on LGADs with a Carbon-Enriched Shallow Multiplication Layer: Degradation of Timing Performance and Gain

Author: Ramos, E. Navarrete, Duarte-Campderros, J., Fernández, M., Gómez, G., González, J., Hidalgo, S., Jaramillo, R., del Árbol, P. Martínez Ruiz, Moll, M., Quintana, C., Sikdar, A. K., Vila, I., and Villegas, J.
Subjects: Physics - Instrumentation and Detectors
Abstract: In this radiation tolerance study, Low Gain Avalanche Detectors (LGADs) with a carbon-enriched broad and shallow multiplication layer were examined in comparison to identical non-carbonated LGADs. Manufactured at IMB-CNM, the sensors underwent neutron irradiation at the TRIGA reactor in Ljubljana, reaching a fluence of $1.5e^{15} {n_{eq}} cm^{-2}$. The results revealed a smaller deactivation of boron and improved resistance to radiation in carbonated LGADs. The study demonstrated the potential benefits of carbon enrichment in mitigating radiation damage effects, particularly the acceptor removal mechanism, reducing the acceptor removal constant by more than a factor of two. Additionally, time resolution and collected charge degradation due to irradiation were observed, with carbonated samples exhibiting better radiation tolerance. A noise analysis focused on baseline noise and spurious pulses showed the presence of thermal-generated dark counts attributed to a too narrow distance between the gain layer end and the p-stop implant at the periphery of the pad for the characterized LGAD design; however, without significant impact of operation performance.
Published: 2024

27. Mechanically induced topological transition of spectrin regulates its distribution in the mammalian cell cortex.

Author: Ghisleni, Andrea, Bonilla-Quintana, Mayte, Crestani, Michele, Lavagnino, Zeno, Galli, Camilla, Rangamani, Padmini, and Gauthier, Nils
Subjects: Spectrin, Animals, Fibroblasts, Actomyosin, Mice, Cytoskeleton, Stress, Mechanical, Cell Membrane, Cell Shape, Actins, Stress Fibers, Humans
Abstract: The cell cortex is a dynamic assembly formed by the plasma membrane and underlying cytoskeleton. As the main determinant of cell shape, the cortex ensures its integrity during passive and active deformations by adapting cytoskeleton topologies through yet poorly understood mechanisms. The spectrin meshwork ensures such adaptation in erythrocytes and neurons by adopting different organizations. Erythrocytes rely on triangular-like lattices of spectrin tetramers, whereas in neurons they are organized in parallel, periodic arrays. Since spectrin is ubiquitously expressed, we exploited Expansion Microscopy to discover that, in fibroblasts, distinct meshwork densities co-exist. Through biophysical measurements and computational modeling, we show that the non-polarized spectrin meshwork, with the intervention of actomyosin, can dynamically transition into polarized clusters fenced by actin stress fibers that resemble periodic arrays as found in neurons. Clusters experience lower mechanical stress and turnover, despite displaying an extension close to the tetramer contour length. Our study sheds light on the adaptive properties of spectrin, which participates in the protection of the cell cortex by varying its densities in response to key mechanical features.
Published: 2024

28. Amplitude analysis of the radiative decay $B^0_s\to K^+K^-\gamma$

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., Battig, A., 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., Ek-In, S., 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, 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., 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., 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., Quintana, B., 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., 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, 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: A search for radiative decay of $B^0_s$ mesons to orbitally excited $K^+K^-$ states is performed using proton proton collisions recorded by the \mbox{LHCb}\xspace experiment, corresponding to an integrated luminosity of 9~fb$^{-1}$. The dikaon spectrum in the mass range $m_{KK}<2400$~{\ensuremath{\,\text{Me\kern -0.1em V\!/}c^2}\xspace} is dominated by the $\phi(1020)$ resonance that accounts for almost 70$\%$ of the decay rate. Considering the possible contributions of $f_2{(1270)}$, $f'_2{(1525)}$ and $f_2{(2010)}$ meson states, the overall tensor contribution to the amplitude is measured to be \begin{equation} {\cal F}_{\{f_2\}}=16.8\pm 0.5\mathrm{~(stat.)}\pm0.7\mathrm{~(syst.)}\%,\nonumber \end{equation} mostly dominated by the $f'_2(1525)$ state. Several statistically equivalent solutions are obtained for the detailed resonant structure depending on whether the smaller amplitudes interfere destructively or constructively with the dominant amplitude. The preferred solution that corresponds to the lowest values of the fit fractions along with constructive interference leads to the relative branching ratio measurement \begin{equation} \frac{{\cal B}(B^0_s\to f'_2\gamma)}{{\cal B}(B^0_s\to\phi\gamma)}= 19.4^{+0.9}_{-0.8}\mathrm{~(stat.)}{}^{+1.4}_{-0.5}\mathrm{~(syst.)}\pm0.5\mathrm{~(\cal{B})}\%\nonumber, \end{equation} where the last uncertainty is due to the ratio of measured branching fractions to the $K^+K^-$ final state. This result represents the first observation of the radiative $B^0_s\to f'_2(1525)\gamma$ decay, which is the second radiative transition observed in the $B^0_s$ sector., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-002.html (LHCb public pages)
Published: 2024
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29. Uniform vs. Lognormal Kinematics in Robots: Perceptual Preferences for Robotic Movements

Author: Quintana, Jose J., Ferrer, Miguel A., Diaz, Moises, Feo, Jose J., Wolniakowski, Adam, and Miatliuk, Konstantsin
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract: Collaborative robots or cobots interact with humans in a common work environment. In cobots, one under investigated but important issue is related to their movement and how it is perceived by humans. This paper tries to analyze whether humans prefer a robot moving in a human or in a robotic fashion. To this end, the present work lays out what differentiates the movement performed by an industrial robotic arm from that performed by a human one. The main difference lies in the fact that the robotic movement has a trapezoidal speed profile, while for the human arm, the speed profile is bell-shaped and during complex movements, it can be considered as a sum of superimposed bell-shaped movements. Based on the lognormality principle, a procedure was developed for a robotic arm to perform human-like movements. Both speed profiles were implemented in two industrial robots, namely, an ABB IRB 120 and a Universal Robot UR3. Three tests were used to study the subjects' preference when seeing both movements and another analyzed the same when interacting with the robot by touching its ends with their fingers.
Published: 2024
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30. Thermalization and Criticality on an Analog-Digital Quantum Simulator

Author: Andersen, Trond I., Astrakhantsev, Nikita, Karamlou, Amir H., Berndtsson, Julia, Motruk, Johannes, Szasz, Aaron, Gross, Jonathan A., Schuckert, Alexander, Westerhout, Tom, Zhang, Yaxing, Forati, Ebrahim, Rossi, Dario, Kobrin, Bryce, Di Paolo, Agustin, Klots, Andrey R., Drozdov, Ilya, Kurilovich, Vladislav D., Petukhov, Andre, Ioffe, Lev B., Elben, Andreas, Rath, Aniket, Vitale, Vittorio, Vermersch, Benoit, Acharya, Rajeev, Beni, Laleh Aghababaie, Anderson, Kyle, Ansmann, Markus, Arute, Frank, Arya, Kunal, Asfaw, Abraham, Atalaya, Juan, Ballard, Brian, Bardin, Joseph C., Bengtsson, Andreas, Bilmes, Alexander, Bortoli, Gina, Bourassa, Alexandre, Bovaird, Jenna, Brill, Leon, Broughton, Michael, Browne, David A., Buchea, Brett, Buckley, Bob B., Buell, David A., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Cabrera, Anthony, Campero, Juan, Chang, Hung-Shen, Chen, Zijun, Chiaro, Ben, Claes, Jahan, Cleland, Agnetta Y., Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Das, Sayan, Debroy, Dripto M., De Lorenzo, Laura, Barba, Alexander Del Toro, Demura, Sean, Donohoe, Paul, Dunsworth, Andrew, Earle, Clint, Eickbusch, Alec, Elbag, Aviv Moshe, Elzouka, Mahmoud, Erickson, Catherine, Faoro, Lara, Fatemi, Reza, Ferreira, Vinicius S., Burgos, Leslie Flores, Fowler, Austin G., Foxen, Brooks, Ganjam, Suhas, Gasca, Robert, Giang, William, Gidney, Craig, Gilboa, Dar, Giustina, Marissa, Gosula, Raja, Dau, Alejandro Grajales, Graumann, Dietrich, Greene, Alex, Habegger, Steve, Hamilton, Michael C., Hansen, Monica, Harrigan, Matthew P., Harrington, Sean D., Heslin, Stephen, Heu, Paula, Hill, Gordon, Hoffmann, Markus R., Huang, Hsin-Yuan, Huang, Trent, Huff, Ashley, Huggins, William J., Isakov, Sergei V., Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Jordan, Stephen, Joshi, Chaitali, Juhas, Pavol, Kafri, Dvir, Kang, Hui, Kechedzhi, Kostyantyn, Khaire, Trupti, Khattar, Tanuj, Khezri, Mostafa, Kieferová, Mária, Kim, Seon, Kitaev, Alexei, Klimov, Paul V., Korotkov, Alexander N., Kostritsa, Fedor, Kreikebaum, John Mark, Landhuis, David, Langley, Brandon W., Laptev, Pavel, Lau, Kim-Ming, Guevel, Loïck Le, Ledford, Justin, Lee, Joonho, Lee, Kenny, Lensky, Yuri D., Lester, Brian J., Li, Wing Yan, Lill, Alexander T., Liu, Wayne, Livingston, William P., Locharla, Aditya, Lundahl, Daniel, Lunt, Aaron, Madhuk, Sid, Maloney, Ashley, Mandrà, Salvatore, Martin, Leigh S., Martin, Orion, Martin, Steven, Maxfield, Cameron, McClean, Jarrod R., McEwen, Matt, Meeks, Seneca, Miao, Kevin C., Mieszala, Amanda, Molina, Sebastian, Montazeri, Shirin, Morvan, Alexis, Movassagh, Ramis, Neill, Charles, Nersisyan, Ani, Newman, Michael, Nguyen, Anthony, Nguyen, Murray, Ni, Chia-Hung, Niu, Murphy Yuezhen, Oliver, William D., Ottosson, Kristoffer, Pizzuto, Alex, Potter, Rebecca, Pritchard, Orion, Pryadko, Leonid P., Quintana, Chris, Reagor, Matthew J., Rhodes, David M., Roberts, Gabrielle, Rocque, Charles, Rosenberg, Eliott, Rubin, Nicholas C., Saei, Negar, Sankaragomathi, Kannan, Satzinger, Kevin J., Schurkus, Henry F., Schuster, Christopher, Shearn, Michael J., Shorter, Aaron, Shutty, Noah, Shvarts, Vladimir, Sivak, Volodymyr, Skruzny, Jindra, Small, Spencer, Smith, W. Clarke, Springer, Sofia, Sterling, George, Suchard, Jordan, Szalay, Marco, Sztein, Alex, Thor, Douglas, Torres, Alfredo, Torunbalci, M. Mert, Vaishnav, Abeer, Vdovichev, Sergey, Villalonga, Benjamin, Heidweiller, Catherine Vollgraff, Waltman, Steven, Wang, Shannon X., White, Theodore, Wong, Kristi, Woo, Bryan W., Xing, Cheng, Yao, Z. Jamie, Yeh, Ping, Ying, Bicheng, Yoo, Juhwan, Yosri, Noureldin, Young, Grayson, Zalcman, Adam, Zhu, Ningfeng, Zobrist, Nicholas, Neven, Hartmut, Babbush, Ryan, Boixo, Sergio, Hilton, Jeremy, Lucero, Erik, Megrant, Anthony, Kelly, Julian, Chen, Yu, Smelyanskiy, Vadim, Vidal, Guifre, Roushan, Pedram, Lauchli, Andreas M., Abanin, Dmitry A., and Mi, Xiao
Subjects: Quantum Physics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Strongly Correlated Electrons
Abstract: Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators. Unlocking the full potential of such systems toward this goal requires flexible initial state preparation, precise time evolution, and extensive probes for final state characterization. We present a quantum simulator comprising 69 superconducting qubits which supports both universal quantum gates and high-fidelity analog evolution, with performance beyond the reach of classical simulation in cross-entropy benchmarking experiments. Emulating a two-dimensional (2D) XY quantum magnet, we leverage a wide range of measurement techniques to study quantum states after ramps from an antiferromagnetic initial state. We observe signatures of the classical Kosterlitz-Thouless phase transition, as well as strong deviations from Kibble-Zurek scaling predictions attributed to the interplay between quantum and classical coarsening of the correlated domains. This interpretation is corroborated by injecting variable energy density into the initial state, which enables studying the effects of the eigenstate thermalization hypothesis (ETH) in targeted parts of the eigenspectrum. Finally, we digitally prepare the system in pairwise-entangled dimer states and image the transport of energy and vorticity during thermalization. These results establish the efficacy of superconducting analog-digital quantum processors for preparing states across many-body spectra and unveiling their thermalization dynamics.
Published: 2024

31. High-precision spectroscopy of $^{20}$O benchmarking ab-initio calculations in light nuclei

Author: Zanon, I., Clément, E., Goasduff, A., Menéndez, J., Miyagi, T., Assié, M., Ciemała, M., Flavigny, F., Lemasson, A., Matta, A., Ramos, D., Rejmund, M., Achouri, L., Ackermann, D., Barrientos, D., Beaumel, D., Benzoni, G., Boston, A. J., Boston, H. C., Bottoni, S., Bracco, A., Brugnara, D., de France, G., de Sereville, N., Delaunay, F., Desesquelles, P., Didierjean, F., Domingo-Prato, C., Dudouet, J., Eberth, J., Fernández, D., Fougères, C., Gadea, A., Galtarossa, F., Girard-Alcindor, V., Gonzales, V., Gottardo, A., Hammache, F., Harkness-Brennan, L. J., Hess, H., Judson, D. S, Jungclaus, A., Kaşkaş, A., Kim, Y. H., Kuşoğlu, A., Labiche, M., Leblond, S., Lenain, C., Lenzi, S. M., Leoni, S., Li, H., Ljungvall, J., Lois-Fuentes, J., Lopez-Martens, A., Maj, A., Menegazzo, R., Mengoni, D., Michelagnoli, C., Million, B., Napoli, D. R., Nyberg, J., Pasqualato, G., Podolyak, Zs., Pullia, A., Quintana, B., Recchia, F., Regueira-Castro, D., Reiter, P., Rezynkina, K., Rojo, J. S., Salsac, M. D., Sanchis, E., Şenyiğit, M., Siciliano, M., Sohler, D., Stezowski, O., Theisen, Ch., Utepov, A., Valiente-Dobón, J. J., Verney, D., and Zielinska, M.
Subjects: Nuclear Experiment, Nuclear Theory
Abstract: The excited states of unstable $^{20}$O were investigated via $\gamma$-ray spectroscopy following the $^{19}$O$(d,p)^{20}$O reaction at 8 $A$MeV. By exploiting the Doppler Shift Attenuation Method, the lifetime of the 2$^+_2$ and 3$^+_1$ states were firmly established. From the $\gamma$-ray branching and E2/M1 mixing ratios for transitions deexciting the 2$^+_2$ and 3$^+_1$ states, the B(E2) and B(M1) were determined. Various chiral effective field theory Hamiltonians, describing the nuclear properties beyond ground states, along with a standard USDB interaction, were compared with the experimentally obtained data. Such a comparison for a large set of $\gamma$-ray transition probabilities with the valence space in medium similarity renormalization group ab-initio calculations was performed for the first time in a nucleus far from stability. It was shown that the ab-initio approaches using chiral EFT forces are challenged by detailed high-precision spectroscopic properties of nuclei. The reduced transition probabilities were found to be a very constraining test of the performance of the ab-initio models., Comment: Supplemental Material available
Published: 2024
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32. How Stellar Stream Torsion may reveal aspherical Dark Matter Haloes

Author: Bariego-Quintana, Adriana
Subjects: Astrophysics - Astrophysics of Galaxies, General Relativity and Quantum Cosmology
Abstract: Flat rotation curves follow from elongated Dark Matter distributions, as shown by our earlier competitive fits to the SPARC database. Intending to probe that distortion of the DM halo one needs observables not contained by the galactic plane. Stellar streams are caused by tidal stretching of massive substructures such as satellite dwarf galaxies, and would lie on a plane should the DM-halo gravitational field be spherically symmetric. But if the field does not display such spherical symmetry, stellar trajectories, as well as stellar streams, should torsion out of the plane. This is where the torsion of the stream can be of use: it is a local observable that measures the deviation from planarity of a curve; thus, it quantifies how noncentral the gravitational potential is. We have performed small simulations to confirm that indeed a galactic central force produces negligible torsion, and quantified the torsion for prolate haloes instead. Examining observational data, we select several streams at large distance from the galactic center, as most promising for the study, and by means of helicoidal fits extract their differential torsion. We see that their torsion is much larger than expected for a central spherical bulb alone, pointing to an elongated Milky Way halo., Comment: 4 pages, 1 figure, proceedings for ICWIP 2023
Published: 2024

33. Are Generics and Negativity about Social Groups Common on Social Media? A Comparative Analysis of Twitter (X) Data

Author: Peters, Uwe and Quintana, Ignacio Ojea
Subjects: Computer Science - Social and Information Networks, Computer Science - Computers and Society, Computer Science - Machine Learning
Abstract: Generics (unquantified generalizations) are thought to be pervasive in communication and when they are about social groups, this may offend and polarize people because generics gloss over variations between individuals. Generics about social groups might be particularly common on Twitter (X). This remains unexplored, however. Using machine learning (ML) techniques, we therefore developed an automatic classifier for social generics, applied it to more than a million tweets about people, and analyzed the tweets. We found that most tweets (78%) about people contained no generics. However, tweets with social generics received more 'likes' and retweets. Furthermore, while recent psychological research may lead to the prediction that tweets with generics about political groups are more common than tweets with generics about ethnic groups, we found the opposite. However, consistent with recent claims that political animosity is less constrained by social norms than animosity against gender and ethnic groups, negative tweets with generics about political groups were significantly more prevalent and retweeted than negative tweets about ethnic groups. Our study provides the first ML-based insights into the use and impact of social generics on Twitter.
Published: 2024

34. Component Separation method for CMB using Convolutional Neural Networks

Author: Quintana-Estellés, A., Ruiz-Granados, B., and Ruiz-Lapuente, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: The aim of this project is to recover the CMB anisotropies maps in temperature and polarized intensity by means of a deep convolutional neural network (CNN) which, after appropiate training, can remove the foregrounds from Planck and QUIJOTE data. The results are then compared with those obtained by COMMANDER, based on Bayesian parametric component separation. The CNN successfully recovered the CMB signal for both All Sky and Partial Sky maps showing frequency dependant results, being optimum for central frequencies where there is less contamination by foregrounds emissions such as galactic synchrotron and thermal dust emissions. Recovered maps in temperature are consistent with those obtained by Planck Collaboration, while polarized intensity has been recovered as a new observable. The polarized intensity maps recovered from QUIJOTE experiment are novel and of potential interest to the scientific community for the detection of primordial gravitational waves. The way forward will be to recover the maps at higher NSIDE and make them available to the scientific community., Comment: 2 pages, 2 figures, Contribution to the 2024 Cosmology session of the 58th Rencontres de Moriond
Published: 2024

35. Exploring the Potential of Robot-Collected Data for Training Gesture Classification Systems

Author: Garcia-Sosa, Alejandro, Quintana-Hernandez, Jose J., Ballester, Miguel A. Ferrer, and Carmona-Duarte, Cristina
Subjects: Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract: Sensors and Artificial Intelligence (AI) have revolutionized the analysis of human movement, but the scarcity of specific samples presents a significant challenge in training intelligent systems, particularly in the context of diagnosing neurodegenerative diseases. This study investigates the feasibility of utilizing robot-collected data to train classification systems traditionally trained with human-collected data. As a proof of concept, we recorded a database of numeric characters using an ABB robotic arm and an Apple Watch. We compare the classification performance of the trained systems using both human-recorded and robot-recorded data. Our primary objective is to determine the potential for accurate identification of human numeric characters wearing a smartwatch using robotic movement as training data. The findings of this study offer valuable insights into the feasibility of using robot-collected data for training classification systems. This research holds broad implications across various domains that require reliable identification, particularly in scenarios where access to human-specific data is limited.
Published: 2024

36. Mapping Parallel Matrix Multiplication in GotoBLAS2 to the AMD Versal ACAP for Deep Learning

Author: Lei, Jie and Quintana-Ortí, Enrique S.
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing
Abstract: This paper investigates the design of parallel general matrix multiplication (GEMM) for a Versal Adaptive Compute Accelerated Platform (ACAP) equipped with a VC1902 system-on-chip and multiple Artificial Intelligence Engines (AIEs). Our efforts aim to port standard optimization techniques applied in the high-performance realization of GEMM on CPUs to the Versal ACAP. In particular, 1) we address the flexible exploitation of the Versal ACA multi-level memory hierarchy; 2) we delve into the efficient use of the vector units in the AIE tiles, proposing an architecture-specific micro-kernel for mixed precision arithmetic to address the strong demand for adaptive-precision inference in deep learning; and 3) we introduce a parallel design for GEMM that spans multiple AIE tiles, enhancing the computational throughput. We conduct experimental profiling, with up to 32 AI Engines, that demonstrates the high parallel scalability of the solution., Comment: 12 pages
Published: 2024

37. A Multiwavelength Survey of Nearby M dwarfs: Optical and Near-Ultraviolet Flares and Activity with Contemporaneous TESS, Kepler/K2, \textit{Swift}, and HST Observations

Author: Paudel, Rishi R., Barclay, Thomas, Youngblood, Allison, Quintana, Elisa V., Schlieder, Joshua E., Vega, Laura D., Gilbert, Emily A., Osten, Rachel A., Peacock, Sarah, Tristan, Isaiah I., Feliz, Dax L., Boyd, Patricia T., Davenport, James R. A., Huber, Daniel, Kowalski, Adam F., Monsue, Teresa A., and Silverstein, Michele L.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: We present a comprehensive multiwavelength investigation into flares and activity in nearby M~dwarf stars. We leverage the most extensive contemporaneous dataset obtained through the Transiting Exoplanet Sky Survey (TESS), Kepler/K2, the Neil Gehrels Swift Observatory (\textit{Swift}), and the Hubble Space Telescope (HST), spanning the optical and near-ultraviolet (NUV) regimes. In total, we observed 213 NUV flares on 24 nearby M dwarfs, with $\sim$27\% of them having detected optical counterparts, and found that all optical flares had NUV counterparts. We explore NUV/optical energy fractionation in M dwarf flares. Our findings reveal a slight decrease in the ratio of optical to NUV energies with increasing NUV energies, a trend in agreement with prior investigations on G-K stars' flares at higher energies. Our analysis yields an average NUV fraction of flaring time for M0-M3 dwarfs of 2.1\%, while for M4-M6 dwarfs, it is 5\%. We present an empirical relationship between NUV and optical flare energies and compare to predictions from radiative-hydrodynamic and blackbody models. We conducted a comparison of the flare frequency distribution (FFDs) of NUV and optical flares, revealing the FFDs of both NUV and optical flares exhibit comparable slopes across all spectral subtypes. NUV flares on stars affect the atmospheric chemistry, the radiation environment, and the overall potential to sustain life on any exoplanets they host. We find that early and mid-M dwarfs (M0-M5) have the potential to generate NUV flares capable of initiating abiogenesis., Comment: 41 pages, 22 figures, Accepted for publication in the Astrophysical Journal
Published: 2024

38. Using Micromegas detectors for direct dark matter searches: challenges and perspectives

Author: Altenmueller, K., Antolin, ., Calvet, D., Candon, F. R., Castel, J., Cebrian, S., Cogollos, C., Dafni, T., Ibanez, D. Diez, Ferrer-Ribas, E., Galan, J., Garcia, J. A., Gomez, H., Gu, Y., Ezquerro, A., Irastorza, I. G, Luzon, G., Margalejo, C., Mirallas, H., Obis, L., de Solorzano, A. Ortiz, Papaevangelou, T., Perez, O., Picatoste, E., Porron, J., Puyuelo, M. J., Quintana, A., Ruiz-Choliz, E., Ruz, J., and Vogel, J.
Subjects: Physics - Instrumentation and Detectors
Abstract: Gas time projection chambers (TPCs) with Micromegas pixelated readouts are being used in dark matter searches and other rare event searches, due to their potential in terms of low background levels, energy and spatial resolution, gain, and operational stability. Moreover, these detectors can provide precious features,such as topological information, allowing for event directionality and powerful signal-background discrimination. The Micromegas technology of the microbulk type is particularly suited to low-background applications and is being exploited by detectors for CAST and IAXO (solar axions) and TREX-DM (low-mass WIMPs) experiments. Challenges for the future include reducing intrinsic background levels, reaching lower energy detection levels, and technical issues such as robustness of detector, new design choices, novel gas mixtures and operation points, scaling up to larger detector sizes, handling large readout granularity, etc. We report on the status and prospects of the development ongoing in the context of IAXO and TREX-DM experiments, pointing to promising perspectives for the use of Micromegas detectors in directdark matter searches
Published: 2024

39. Search for Neutrino Emission from GRB 221009A using the KM3NeT ARCA and ORCA detectors

Author: Aiello, S., Albert, A., Alshamsi, M., Garre, S. Alves, Ambrosone, A., Ameli, F., Andre, M., Androutsou, E., Anguita, M., Aphecetche, L., Ardid, M., Ardid, S., Atmani, H., Aublin, J., Badaracco, F., Bailly-Salins, L., Bardačová, Z., Baret, B., Bariego-Quintana, A., Pree, S. Basegmez du, Becherini, Y., Bendahman, M., Benfenati, F., Benhassi, M., Benoit, D. M., Berbee, E., Bertin, V., Biagi, S., Boettcher, M., Bonanno, D., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Bozza, R. M., Brânzaş, H., Bretaudeau, F., Breuhaus, M., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Campion, S., Capone, A., Carenini, F., Carretero, V., Cartraud, T., Castaldi, P., Cecchini, V., Celli, S., Cerisy, L., Chabab, M., Chadolias, M., Chen, A., Cherubini, S., Chiarusi, T., Circella, M., Cocimano, R., Coelho, J. A. B., Coleiro, A., Condorelli, A., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., Darras, Y., De Benedittis, A., De Martino, B., Decoene, V., Del Burgo, R., Del Rosso, I., Di Mauro, L. S., Di Palma, I., Díaz, A. F., Diaz, C., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Dörr, M., Drakopoulou, E., Drouhin, D., Ducoin, J. G., Dvornický, R., Eberl, T., Eckerová, E., Eddymaoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Enzenhöfer, A., Ferrara, G., Filipović, M. D., Filippini, F., Franciotti, D., Fusco, L. A., Gagliardini, S., Gal, T., Méndez, J. García, Soto, A. Garcia, Oliver, C. Gatius, Geißelbrecht, N., Ghaddari, H., Gialanella, L., Gibson, B. K., Giorgio, E., Goos, I., Goswami, P., Gozzini, S. R., Gracia, R., Graf, K., Guidi, C., Guillon, B., Gutiérrez, M., Haack, C., van Haren, H., Heijboer, A., Hekalo, A., Hennig, L., Hernández-Rey, J. J., Ibnsalih, W. Idrissi, Illuminati, G., Joly, D., de Jong, M., de Jong, P., Jung, B. J., Kalekin, O., Katz, U. F., Kharkhelauri, L., Kistauri, G., Kopper, C., Kouchner, A., Kueviakoe, V., Kulikovskiy, V., Kvatadze, R., Labalme, M., Lahmann, R., Larosa, G., Lastoria, C., Lazo, A., Stum, S. Le, Lehaut, G., Leonora, E., Lessing, N., Levi, G., Longhitano, F., Magnani, F., Majumdar, J., Malerba, L., Mamedov, F., Mańczak, J., Manfreda, A., Marconi, M., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Marzaioli, F., Mastrodicasa, M., Mastroianni, S., Miccichè, S., Miele, G., Migliozzi, P., Migneco, E., Mitsou, M. L., Mollo, C. M., Morales-Gallegos, L., Moretti, G., Moussa, A., Mateo, I. Mozun, Muller, R., Musone, M. R., Musumeci, M., Navas, S., Nayerhoda, A., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, Oliviero, V., Orlando, A., Oukacha, E., Paesani, D., González, J. Palacios, Papalashvili, G., Parisi, V., Gomez, E. J. Pastor, Păun, A. M., Păvălaş, G. E., Pelegris, I., Martínez, S. Pena, Perrin-Terrin, M., Perronnel, J., Pestel, V., Pestes, R., Piattelli, P., Poirè, C., Popa, V., Pradier, T., Prado, J., Pulvirenti, S., Quiroz-Rangel, C. A., Rahaman, U., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Riccobene, G., Robinson, J., Romanov, A., Šaina, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanfilippo, S., Sanguineti, M., Santonastaso, C., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Schutte, H. M., Seneca, J., Sennan, N., Setter, B., Sgura, I., Shanidze, R., Sharma, A., Shitov, Y., Šimkovic, F., Simonelli, A., Sinopoulou, A., Smirnov, M. V., Spisso, B., Spurio, M., Stavropoulos, D., Štekl, I., Taiuti, M., Tangorra-Cascione, R., Tayalati, Y., Thiersen, H., Melo, I. Tosta e, Tragia, E., Trocmé, B., Tsourapis, V., Tudorache, A., Tzamariudaki, E., Ukleja, A., Vacheret, A., Melchor, A. Valer, Valsecchi, V., Van Elewyck, V., Vannoye, G., Vasileiadis, G., de Sola, F. Vazquez, Veutro, A., Viola, S., Vivolo, D., Wilms, J., de Wolf, E., Yepes-Ramirez, H., Yvon, I., Zarpapis, G., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., and Zywucka, N.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Gamma-ray bursts are promising candidate sources of high-energy astrophysical neutrinos. The recent GRB 221009A event, identified as the brightest gamma-ray burst ever detected, provides a unique opportunity to investigate hadronic emissions involving neutrinos. The KM3NeT undersea neutrino detectors participated in the worldwide follow-up effort triggered by the event, searching for neutrino events. In this letter, we summarize subsequent searches, in a wide energy range from MeV up to a few PeVs. No neutrino events are found in any of the searches performed. Upper limits on the neutrino emission associated with GRB 221009A are computed., Comment: 11 pages, 2 PDF figures. Submitted to JCAP
Published: 2024

40. Learning Alternative Ways of Performing a Task

Author: Nieves, David, Ramírez-Quintana, María José, Monserrat, Carlos, Ferri, César, and Hernández-Orallo, José
Subjects: Computer Science - Artificial Intelligence, I.2.6, I.5.4
Abstract: A common way of learning to perform a task is to observe how it is carried out by experts. However, it is well known that for most tasks there is no unique way to perform them. This is especially noticeable the more complex the task is because factors such as the skill or the know-how of the expert may well affect the way she solves the task. In addition, learning from experts also suffers of having a small set of training examples generally coming from several experts (since experts are usually a limited and expensive resource), being all of them positive examples (i.e. examples that represent successful executions of the task). Traditional machine learning techniques are not useful in such scenarios, as they require extensive training data. Starting from very few executions of the task presented as activity sequences, we introduce a novel inductive approach for learning multiple models, with each one representing an alternative strategy of performing a task. By an iterative process based on generalisation and specialisation, we learn the underlying patterns that capture the different styles of performing a task exhibited by the examples. We illustrate our approach on two common activity recognition tasks: a surgical skills training task and a cooking domain. We evaluate the inferred models with respect to two metrics that measure how well the models represent the examples and capture the different forms of executing a task showed by the examples. We compare our results with the traditional process mining approach and show that a small set of meaningful examples is enough to obtain patterns that capture the different strategies that are followed to solve the tasks., Comment: 32 pages, Github repository, published paper, authors' version
Published: 2024
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41. Creating synthetic energy meter data using conditional diffusion and building metadata

Author: Fu, Chun, Kazmi, Hussain, Quintana, Matias, and Miller, Clayton
Subjects: Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract: Advances in machine learning and increased computational power have driven progress in energy-related research. However, limited access to private energy data from buildings hinders traditional regression models relying on historical data. While generative models offer a solution, previous studies have primarily focused on short-term generation periods (e.g., daily profiles) and a limited number of meters. Thus, the study proposes a conditional diffusion model for generating high-quality synthetic energy data using relevant metadata. Using a dataset comprising 1,828 power meters from various buildings and countries, this model is compared with traditional methods like Conditional Generative Adversarial Networks (CGAN) and Conditional Variational Auto-Encoders (CVAE). It explicitly handles long-term annual consumption profiles, harnessing metadata such as location, weather, building, and meter type to produce coherent synthetic data that closely resembles real-world energy consumption patterns. The results demonstrate the proposed diffusion model's superior performance, with a 36% reduction in Frechet Inception Distance (FID) score and a 13% decrease in Kullback-Leibler divergence (KL divergence) compared to the following best method. The proposed method successfully generates high-quality energy data through metadata, and its code will be open-sourced, establishing a foundation for a broader array of energy data generation models in the future., Comment: 17 pages, 11 figures, submitted to journal "Energy and Buildings"
Published: 2024
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42. Performance Analysis of Matrix Multiplication for Deep Learning on the Edge

Author: Ramírez, Cristian, Castelló, Adrián, Martínez, Héctor, and Quintana-Ortí, Enrique S.
Subjects: Computer Science - Hardware Architecture
Abstract: The devices designed for the Internet-of-Things encompass a large variety of distinct processor architectures, forming a highly heterogeneous zoo. In order to tackle this, we employ a simulator to estimate the performance of the matrix-matrix multiplication (GEMM) kernel on processors designed to operate at the edge. Our simulator adheres to the modern implementations of GEMM, advocated by GotoBLAS2, BLIS, OpenBLAS, etc., to carefully account for the amount of data transfers across the memory hierarchy of different algorithmic variants of the kernel. %Armed with this tool, A small collection of experiments provide the necessary data to calibrate the simulator and deliver highly accurate estimations of the execution time for a given processor architecture., Comment: 12 pages, 2 Tables, 6 Figures
Published: 2024
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43. Background discrimination with a Micromegas detector prototype and veto system for BabyIAXO

Author: Altenmüller, K., Castel, J. F., Cebrián, S., Dafni, T., Díez-Ibañez, D., Ezquerro, A., Ferrer-Ribas, E., Galan, J., Galindo, J., García, J. A., Giganon, A., Goblin, C., Irastorza, I. G., Loiseau, C., Luzón, G., Navick, X. F., Margalejo, C., Mirallas, H., Obis, L., de Solórzano, A. Ortiz, Papaevangelou, T., Pérez, O., Quintana, A., Ruz, J., and Vogel, J. K.
Subjects: Physics - Instrumentation and Detectors
Abstract: In this paper we present measurements performed with a Micromegas X-ray detector setup. The detector is a prototype in the context of the BabyIAXO helioscope, which is under construction to search for an emission of the hypothetical axion particle from the sun. An important component of such a helioscope is a low background X-ray detector with a high efficiency in the 1-10 keV energy range. The goal of the measurement was to study techniques for background discrimination. In addition to common techniques we used a multi-layer veto system designed to tag cosmogenic neutron background. Over an effective time of 52 days, a background level of $8.6 \times 10^{-7}\,\text{counts keV}^{-1}\,\text{cm}^{-2} \, \text{s}^{-1}$ was reached in a laboratory at above ground level. This is the lowest background level achieved at surface level. In this paper we present the experimental setup, show simulations of the neutron-induced background, and demonstrate the process to identify background signals in the data. Finally, prospects to reach lower background levels down to $10^{-7} \, \text{counts keV}^{-1} \, \text{cm}^{-2} \, \text{s}^{-1}$ will be discussed.
Published: 2024

44. Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors

Author: Tomas, Andres E., Quintana-Orti, Enrique S., and Anzt, Hartwig
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, G.4.5
Abstract: We investigate the solution of low-rank matrix approximation problems using the truncated SVD. For this purpose, we develop and optimize GPU implementations for the randomized SVD and a blocked variant of the Lanczos approach. Our work takes advantage of the fact that the two methods are composed of very similar linear algebra building blocks, which can be assembled using numerical kernels from existing high-performance linear algebra libraries. Furthermore, the experiments with several sparse matrices arising in representative real-world applications and synthetic dense test matrices reveal a performance advantage of the block Lanczos algorithm when targeting the same approximation accuracy., Comment: 16 pages, 4 figures
Published: 2024
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45. Justice First : Interdisciplinary Approaches in Environmental Justice Research and Efforts

Author: Estien, Cesar O., Quintana, Brandon, Ramirez, Crystal, and Rodriguez, Leeza-Marie
Published: 2024

46. Evaluation of the Importance of Capsule Transparency in Dry Powder Inhalation Devices

Author: Arija, Rocio Reinoso, de la Espada, Rosario Ruiz-Serrano, Ollero, Ma Dolores Nunez, Hernandez, Laura Carrasco, Gallego, Esther Quintana, and Lopez-Campos, Jose Luis
Subjects: Pharmaceutical research, Inhalers -- Usage -- Design and construction, Capsules (Pharmacy) -- Usage -- Evaluation, Health, Science and technology
Abstract: The aim of this work is to test whether the use of a transparent capsule affects the residual capsule weight after inhalation as a surrogate of the inhaled delivered dose for patients with non-reversible chronic airway disease. Researchers conducted an observational cross-sectional study with patients using a single-dose dry powder inhaler. The weight of the capsule was measured with a precision microbalance before and after inhalation. Ninety-one patients were included, of whom 63 (69.2%) used a transparent capsule. Inhalation with a transparent capsule achieved a weight decrease of 30.1% vs 8.6% for devices with an opaque capsule (P Key words: chronic obstructive airway diseases; dry powder inhalers; dry powder capsules; clinical outcomes, https://doi.org/10.1370/afm.3147 INTRODUCTION One of the factors considered most important by patients when using inhaled medications is the verification of the dose taken. (1) Additionally, critical errors in dose delivery have [...]
Published: 2024
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47. Optimizing friction stir welding parameters for specific energy of aluminum alloys

Author: Terra, Caroline, Quintana, Karen J., and Silveira, Jose Luis
Published: 2024
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48. Phase transitions in random circuit sampling

Author: Morvan, A., Villalonga, B., Mi, X., Mandrà, S., Bengtsson, A., Klimov, P. V., Chen, Z., Hong, S., Erickson, C., Drozdov, I. K., Chau, J., Laun, G., Movassagh, R., Asfaw, A., Brandão, L. T. A. N., Peralta, R., Abanin, D., Acharya, R., Allen, R., Andersen, T. I., Anderson, K., Ansmann, M., Arute, F., Arya, K., Atalaya, J., Bardin, J. C., Bilmes, A., Bortoli, G., Bourassa, A., Bovaird, J., Brill, L., Broughton, M., Buckley, B. B., Buell, D. A., Burger, T., Burkett, B., Bushnell, N., Campero, J., Chang, H.-S., Chiaro, B., Chik, D., Chou, C., Cogan, J., Collins, R., Conner, P., Courtney, W., Crook, A. L., Curtin, B., Debroy, D. M., Barba, A. Del Toro, Demura, S., Paolo, A. Di, Dunsworth, A., Faoro, L., Farhi, E., Fatemi, R., Ferreira, V. S., Burgos, L. Flores, Forati, E., Fowler, A. G., Foxen, B., Garcia, G., Genois, É., Giang, W., Gidney, C., Gilboa, D., Giustina, M., Gosula, R., Dau, A. Grajales, Gross, J. A., Habegger, S., Hamilton, M. C., Hansen, M., Harrigan, M. P., Harrington, S. D., Heu, P., Hoffmann, M. R., Huang, T., Huff, A., Huggins, W. J., Ioffe, L. B., Isakov, S. V., Iveland, J., Jeffrey, E., Jiang, Z., Jones, C., Juhas, P., Kafri, D., Khattar, T., Khezri, M., Kieferová, M., Kim, S., Kitaev, A., Klots, A. R., Korotkov, A. N., Kostritsa, F., Kreikebaum, J. M., Landhuis, D., Laptev, P., Lau, K.-M., Laws, L., Lee, J., Lee, K. W., Lensky, Y. D., Lester, B. J., Lill, A. T., Liu, W., Livingston, W. P., Locharla, A., Malone, F. D., Martin, O., Martin, S., McClean, J. R., McEwen, M., Miao, K. C., Mieszala, A., Montazeri, S., Mruczkiewicz, W., Naaman, O., Neeley, M., Neill, C., Nersisyan, A., Newman, M., Ng, J. H., Nguyen, A., Nguyen, M., Niu, M. Yuezhen, O’Brien, T. E., Omonije, S., Opremcak, A., Petukhov, A., Potter, R., Pryadko, L. P., Quintana, C., Rhodes, D. M., Rocque, C., Rosenberg, E., Rubin, N. C., Saei, N., Sank, D., Sankaragomathi, K., Satzinger, K. J., Schurkus, H. F., Schuster, C., Shearn, M. J., Shorter, A., Shutty, N., Shvarts, V., Sivak, V., Skruzny, J., Smith, W. C., Somma, R. D., Sterling, G., Strain, D., Szalay, M., Thor, D., Torres, A., Vidal, G., Heidweiller, C. Vollgraff, White, T., Woo, B. W. K., Xing, C., Yao, Z. J., Yeh, P., Yoo, J., Young, G., Zalcman, A., Zhang, Y., Zhu, N., Zobrist, N., Rieffel, E. G., Biswas, R., Babbush, R., Bacon, D., Hilton, J., Lucero, E., Neven, H., Megrant, A., Kelly, J., Roushan, P., Aleiner, I., Smelyanskiy, V., Kechedzhi, K., Chen, Y., and Boixo, S.
Published: 2024
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49. Social acceptance of renewable energies: a meta-analytic review of 40 years of related literature

Author: Rojas-Peña, D., Quintana-Rojo, C., Tarancón, M. A., and Ruiz-Fuensanta, M. J.
Published: 2024
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50. DEM modeling of advanced manufacturing technologies: from SLS to 3D concrete printing

Author: Quintana-Ruiz, Osvaldo D. and Campello, Eduardo M. B.
Published: 2024
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