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28,552 results on '"Molina, P"'

201. A unitary coupled-channel three-body amplitude with pions and kaons

Author

Feng, Yuchuan, Gil, Fernando, Döring, Michael, Molina, Raquel, Mai, Maxim, Shastry, Vanamali, and Szczepaniak, Adam

Subjects
Nuclear Theory, High Energy Physics - Lattice, High Energy Physics - Phenomenology, Nuclear Experiment
Abstract

Three-body dynamics above threshold is required for the reliable extraction of many amplitudes and resonances from experiment and lattice QCD. The S-matrix principle of unitarity can be used to construct dynamical coupled-channel approaches in which three particles scatter off each other, re-arranging two-body subsystems by particle exchange. This paper reports the development of a three-body coupled-channel, amplitude including pions and kaons. The unequal-mass amplitude contains two-body S- and P-wave subsystems ("isobars") of all isospins, $I=0,\,1/2,\,1,\, 3/2, \, 2$, and it also allows for transitions within a given isobar. The $f_0(500)\, ("\sigma"),\,f_0(980),\,\rho(700), K_0^*(700)\,("\kappa")$, and $K^*(892)$ resonances are included, apart from repulsive isobars. Different methods to evaluate the amplitude for physical momenta are discussed. Production amplitudes for $a_1$ quantum numbers are shown as a proof of principle for the numerical implementation., Comment: 27 pages, 11 figures, version accepted for publication

Published
2024

202. The infrastructure powering IBM's Gen AI model development

Author

Gershon, Talia, Seelam, Seetharami, Belgodere, Brian, Bonilla, Milton, Hoang, Lan, Barnett, Danny, Chung, I-Hsin, Mohan, Apoorve, Chen, Ming-Hung, Luo, Lixiang, Walkup, Robert, Evangelinos, Constantinos, Salaria, Shweta, Dombrowa, Marc, Park, Yoonho, Kayi, Apo, Schour, Liran, Alim, Alim, Sydney, Ali, Maniotis, Pavlos, Schares, Laurent, Metzler, Bernard, Karacali-Akyamac, Bengi, Wen, Sophia, Chiba, Tatsuhiro, Choochotkaew, Sunyanan, Yoshimura, Takeshi, Misale, Claudia, Elengikal, Tonia, Connor, Kevin O, Liu, Zhuoran, Molina, Richard, Schneidenbach, Lars, Caden, James, Laibinis, Christopher, Fonseca, Carlos, Tarasov, Vasily, Sundararaman, Swaminathan, Schmuck, Frank, Guthridge, Scott, Cohn, Jeremy, Eshel, Marc, Muench, Paul, Liu, Runyu, Pointer, William, Wyskida, Drew, Krull, Bob, Rose, Ray, Wolfe, Brent, Cornejo, William, Walter, John, Malone, Colm, Perucci, Clifford, Franco, Frank, Hinds, Nigel, Calio, Bob, Druyan, Pavel, Kilduff, Robert, Kienle, John, McStay, Connor, Figueroa, Andrew, Connolly, Matthew, Fost, Edie, Roma, Gina, Fonseca, Jake, Levy, Ido, Payne, Michele, Schenkel, Ryan, Malki, Amir, Schneider, Lion, Narkhede, Aniruddha, Moshref, Shekeba, Kisin, Alexandra, Dodin, Olga, Rippon, Bill, Wrieth, Henry, Ganci, John, Colino, Johnny, Habeger-Rose, Donna, Pandey, Rakesh, Gidh, Aditya, Gaur, Aditya, Patterson, Dennis, Salmani, Samsuddin, Varma, Rambilas, Rumana, Rumana, Sharma, Shubham, Mishra, Mayank, Panda, Rameswar, Prasad, Aditya, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Cox, David, Puri, Ruchir, Agrawal, Dakshi, Thorstensen, Drew, Belog, Joel, Tang, Brent, Gupta, Saurabh Kumar, Biswas, Amitabha, Maheshwari, Anup, Gampel, Eran, Van Patten, Jason, Runion, Matthew, Kaki, Sai, Bogin, Yigal, Reitz, Brian, Pritko, Steve, Najam, Shahan, Nambala, Surya, Chirra, Radhika, Welp, Rick, DiMitri, Frank, Telles, Felipe, Arvelo, Amilcar, Chu, King, Seminaro, Ed, Schram, Andrew, Eickhoff, Felix, Hanson, William, Mckeever, Eric, Light, Michael, Joseph, Dinakaran, Chaudhary, Piyush, Shivam, Piyush, Chaudhary, Puneet, Jones, Wesley, Guthrie, Robert, Bostic, Chris, Islam, Rezaul, Duersch, Steve, Sawdon, Wayne, Lewars, John, Klos, Matthew, Spriggs, Michael, McMillan, Bill, Gao, George, Kamra, Ashish, Singh, Gaurav, Curry, Marc, Katarki, Tushar, Talerico, Joe, Shi, Zenghui, Malleni, Sai Sindhur, and Gallen, Erwan

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence
Abstract

AI Infrastructure plays a key role in the speed and cost-competitiveness of developing and deploying advanced AI models. The current demand for powerful AI infrastructure for model training is driven by the emergence of generative AI and foundational models, where on occasion thousands of GPUs must cooperate on a single training job for the model to be trained in a reasonable time. Delivering efficient and high-performing AI training requires an end-to-end solution that combines hardware, software and holistic telemetry to cater for multiple types of AI workloads. In this report, we describe IBM's hybrid cloud infrastructure that powers our generative AI model development. This infrastructure includes (1) Vela: an AI-optimized supercomputing capability directly integrated into the IBM Cloud, delivering scalable, dynamic, multi-tenant and geographically distributed infrastructure for large-scale model training and other AI workflow steps and (2) Blue Vela: a large-scale, purpose-built, on-premises hosting environment that is optimized to support our largest and most ambitious AI model training tasks. Vela provides IBM with the dual benefit of high performance for internal use along with the flexibility to adapt to an evolving commercial landscape. Blue Vela provides us with the benefits of rapid development of our largest and most ambitious models, as well as future-proofing against the evolving model landscape in the industry. Taken together, they provide IBM with the ability to rapidly innovate in the development of both AI models and commercial offerings., Comment: Corresponding Authors: Talia Gershon, Seetharami Seelam,Brian Belgodere, Milton Bonilla

Published
2024

203. Nash epidemics

Author

Schnyder, Simon K., Molina, John J., Yamamoto, Ryoichi, and Turner, Matthew S.

Subjects
Economics - Theoretical Economics, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control, Physics - Physics and Society
Abstract

Faced with a dangerous epidemic humans will spontaneously social distance to reduce their risk of infection at a socio-economic cost. Compartmentalised epidemic models have been extended to include this endogenous decision making: Individuals choose their behaviour to optimise a utility function, self-consistently giving rise to population behaviour. Here we study the properties of the resulting Nash equilibria, in which no member of the population can gain an advantage by unilaterally adopting different behaviour. We leverage a new analytic solution to obtain, (1) a simple relationship between rational social distancing behaviour and the current number of infections; (2) new scaling results for how the infection peak and number of total cases depend on the cost of contracting the disease; (3) characteristic infection costs that divide regimes of strong and weak behavioural response and depend only on the basic reproduction number of the disease; (4) a closed form expression for the value of the utility. We discuss how these analytic results provide a deep and intuitive understanding into the disease dynamics, useful for both individuals and policymakers. In particular the relationship between social distancing and infections represents a heuristic that could be communicated to the population to encourage, or "bootstrap", rational behaviour.

Published
2024

204. A detailed study of the very-high-energy Crab pulsar emission with the LST-1

Author

Project, CTA-LST, Abe, K., Abe, S., Abhishek, A., Acero, F., Aguasca-Cabot, A., Agudo, I., Crespo, N. Alvarez, Antonelli, L. A., Aramo, C., Arbet-Engels, A., Arcaro, C., Artero, M., Asano, K., Aubert, P., Baktash, A., Bamba, A., Larriva, A. Baquero, Baroncelli, L., de Almeida, U. Barres, Barrio, J. A., Batkovic, I., Baxter, J., González, J. Becerra, Bernardini, E., Medrano, J. Bernete, Berti, A., Bhattacharjee, P., Bigongiari, C., Bissaldi, E., Blanch, O., Bonnoli, G., Bordas, P., Brunelli, G., Bulgarelli, A., Burelli, I., Burmistrov, L., Buscemi, M., Cardillo, M., Caroff, S., Carosi, A., Carrasco, M. S., Cassol, F., Castrejón, N., Cauz, D., Cerasole, D., Ceribella, G., Chai, Y., Cheng, K., Chiavassa, A., Chikawa, M., Chon, G., Chytka, L., Cicciari, G. M., Cifuentes, A., Contreras, J. L., Cortina, J., Costantini, H., Da Vela, P., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Lotto, B., de Menezes, R., Del Peral, L., Delgado, C., Mengual, J. Delgado, della Volpe, D., Dellaiera, M., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsässer, D., Emery, G., Escudero, J., Ramazani, V. Fallah, Ferrarotto, F., Fiasson, A., Foffano, L., Coromina, L. Freixas, Fröse, S., Fukazawa, Y., López, R. Garcia, Gasbarra, C., Gasparrini, D., Gavira, L., Geyer, D., Paiva, J. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Grau, R., Green, D., Green, J., Gunji, S., Günther, P., Hackfeld, J., Hadasch, D., Hahn, A., Hassan, T., Hayashi, K., Heckmann, L., Heller, M., Llorente, J. Herrera, Hirotani, K., Hoffmann, D., Horns, D., Houles, J., Hrabovsky, M., Hrupec, D., Hui, D., Iarlori, M., Imazawa, R., Inada, T., Inome, Y., Ioka, K., Iori, M., Martinez, I. Jimenez, Quiles, J. Jiménez, Jurysek, J., Kagaya, M., Karas, V., Katagiri, H., Kataoka, J., Kerszberg, D., Kobayashi, Y., Kohri, K., Kong, A., Kubo, H., Kushida, J., Lainez, M., Lamanna, G., Lamastra, A., Lemoigne, L., Linhoff, M., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Bahilo, J. Lozano, Luque-Escamilla, P. L., Majumdar, P., Makariev, M., Mallamaci, M., Mandat, D., Manganaro, M., Manicò, G., Mannheim, K., Marchesi, S., Mariotti, M., Marquez, P., Marsella, G., Martí, J., Martinez, O., Martínez, G., Martínez, M., Mas-Aguilar, A., Maurin, G., Mazin, D., Guillen, E. Mestre, Micanovic, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., Mizuno, T., Gonzalez, M. Molero, Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moya, V., Muraishi, H., Nagataki, S., Nakamori, T., Neronov, A., Nickel, L., Rosillo, M. Nievas, Nikolic, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Oka, T., Okumura, A., Orito, R., Otero-Santos, J., Ottanelli, P., Owen, E., Palatiello, M., Paneque, D., Pantaleo, F. R., Paoletti, R., Paredes, J. M., Pech, M., Pecimotika, M., Peresano, M., Pfeiffle, F., Pietropaolo, E., Pihet, M., Pirola, G., Plard, C., Podobnik, F., Pons, E., Prandini, E., Priyadarshi, C., Prouza, M., Rando, R., Rhode, W., Ribó, M., Righi, C., Rizi, V., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Saito, T., Sakurai, S., Sanchez, D. A., Sano, H., Šarić, T., Sato, Y., Saturni, F. G., Savchenko, V., Schiavone, F., Schleicher, B., Schmuckermaier, F., Schubert, J. L., Schussler, F., Schweizer, T., Arroyo, M. Seglar, Siegert, T., Silvia, R., Sitarek, J., Sliusar, V., Strišković, J., Strzys, M., Suda, Y., Tajima, H., Takahashi, H., Takahashi, M., Takata, J., Takeishi, R., Tam, P. H. T., Tanaka, S. J., Tateishi, D., Tavernier, T., Temnikov, P., Terada, Y., Terauchi, K., Terzic, T., Teshima, M., Tluczykont, M., Tokanai, F., Torres, D. F., Travnicek, P., Truzzi, S., Tutone, A., Vacula, M., Vallania, P., van Scherpenberg, J., Acosta, M. Vázquez, Verna, G., Viale, I., Vigliano, A., Vigorito, C. F., Visentin, E., Vitale, V., Voitsekhovskyi, V., Voutsinas, G., Vovk, I., Vuillaume, T., Walter, R., Wan, L., Will, M., Yamamoto, T., Yamazaki, R., Yeung, P. K. H., Yoshida, T., Yoshikoshi, T., Zhang, W., and Zywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Context: There are currently three pulsars firmly detected by imaging atmospheric Cherenkov telescopes (IACTs), two of them reaching TeV energies, challenging models of very-high-energy (VHE) emission in pulsars. More precise observations are needed to better characterize pulsar emission at these energies. The LST-1 is the prototype of the Large-Sized Telescope, that will be part of the Cherenkov Telescope Array Observatory (CTAO). Its improved performance over previous IACTs makes it well suited for studying pulsars. Aims: To study the Crab pulsar emission with the LST-1, improving and complementing the results from other telescopes. These observations can also be used to characterize the potential of the LST-1 to study other pulsars and detect new ones. Methods: We analyzed a total of $\sim$103 hours of gamma-ray observations of the Crab pulsar conducted with the LST-1 in the period from September 2020 to January 2023. The observations were carried out at zenith angles less than 50 degrees. A new analysis of the Fermi-LAT data was also performed, including $\sim$14 years of observations. Results: The Crab pulsar phaseogram, long-term light-curve, and phase-resolved spectra are reconstructed with the LST-1 from 20 GeV to 450 GeV for P1 and up to 700 GeV for P2. The pulsed emission is detected with a significance of 15.2$\sigma$. The two characteristic emission peaks of the Crab pulsar are clearly detected (>10$\sigma$), as well as the so-called bridge emission (5.7$\sigma$). We find that both peaks are well described by power laws, with spectral indices of $\sim$3.44 and $\sim$3.03 respectively. The joint analysis of Fermi-LAT and LST-1 data shows a good agreement between both instruments in the overlapping energy range. The detailed results obtained in the first observations of the Crab pulsar with LST-1 show the potential that CTAO will have to study this type of sources., Comment: Accepted by A&A

Published
2024

205. Nonequilibrium relaxation of soft responsive colloids

Author

López-Molina, José, Groh, Sebastien, Dzubiella, Joachim, and Moncho-Jordá, Arturo

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

Stimuli-responsive macromolecules display large conformational changes during their dynamics, sometimes switching states, and are an integral property for the development of soft functional materials. Here, we introduce a mean-field dynamical density functional theory (DDFT) for a model of responsive colloids (RCs) to study the nonequilibrium dynamics of a colloidal dispersion in time-dependent external fields, with a focus on the coupling of translational and conformational dynamics during their relaxation. Specifically, we consider soft Gaussian particles with a bimodal size distribution between two confining walls with time-dependent (switching-on and off) external gravitational and osmotic fields. We find a rich relaxation behavior of the systems in excellent agreement with particle-based Brownian dynamics (BD) computer simulations. In particular, we find time-asymmetric relaxations of integrated observables (wall pressures, mean size, liquid center-of-mass) for activation/deactivation of external potentials, respectively, which are tuneable by the ratio of translational and conformational diffusion time scales. Our work paves thus the way for studying the nonequilibrium relaxation dynamics of complex soft matter with multiple degrees of freedom and hierarchical relaxations., Comment: 14 pages, 8 figures

Published
2024

223. Clinical advances and practice updates in genitourinary cancers: a 2024 review from the multidisciplinary Spanish ‘Cambados annual meeting’

Author

Peláez, Ignacio, Lázaro-Quintela, Martín, Pérez-Fentes, Daniel, Esteban-González, Emilio, Gallardo, Enrique, Álvarez-Fernández, Carlos, Álvarez Rodríguez, Pablo, Anido-Herranz, Urbano, Azpitarte Raposeiras, Cristina, Castro-Iglesias, Ángel Maximino, Fernández Calvo, Ovidio, Fernández Núñez, Natalia, Folgar-Torres, Alicia, García Lorenzo, Carme, González-del-Alba, Aránzazu, Méndez-Vidal, María José, Molina Díaz, Aurea, Rodríguez Gómez, Ignacio Rodríguez, and Vázquez-Estévez, Sergio

Published
2025
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234. Thermalization and criticality on an analogue–digital quantum simulator

Author

Andersen, T. I., Astrakhantsev, N., Karamlou, A. H., Berndtsson, J., Motruk, J., Szasz, A., Gross, J. A., Schuckert, A., Westerhout, T., Zhang, Y., Forati, E., Rossi, D., Kobrin, B., Paolo, A. Di, Klots, A. R., Drozdov, I., Kurilovich, V., Petukhov, A., Ioffe, L. B., Elben, A., Rath, A., Vitale, V., Vermersch, B., Acharya, R., Beni, L. A., Anderson, K., Ansmann, M., Arute, F., Arya, K., Asfaw, A., Atalaya, J., Ballard, B., Bardin, J. C., Bengtsson, A., Bilmes, A., Bortoli, G., Bourassa, A., Bovaird, J., Brill, L., Broughton, M., Browne, D. A., Buchea, B., Buckley, B. B., Buell, D. A., Burger, T., Burkett, B., Bushnell, N., Cabrera, A., Campero, J., Chang, H.-S., Chen, Z., Chiaro, B., Claes, J., Cleland, A. Y., Cogan, J., Collins, R., Conner, P., Courtney, W., Crook, A. L., Das, S., Debroy, D. M., Lorenzo, L. De, Barba, A. Del Toro, Demura, S., Donohoe, P., Dunsworth, A., Earle, C., Eickbusch, A., Elbag, A. M., Elzouka, M., Erickson, C., Faoro, L., Fatemi, R., Ferreira, V. S., Burgos, L. Flores, Fowler, A. G., Foxen, B., Ganjam, S., Gasca, R., Giang, W., Gidney, C., Gilboa, D., Giustina, M., Gosula, R., Dau, A. Grajales, Graumann, D., Greene, A., Habegger, S., Hamilton, M. C., Hansen, M., Harrigan, M. P., Harrington, S. D., Heslin, S., Heu, P., Hill, G., Hoffmann, M. R., Huang, H.-Y., Huang, T., Huff, A., Huggins, W. J., Isakov, S. V., Jeffrey, E., Jiang, Z., Jones, C., Jordan, S., Joshi, C., Juhas, P., Kafri, D., Kang, H., Kechedzhi, K., Khaire, T., Khattar, T., Khezri, M., Kieferová, M., Kim, S., Kitaev, A., Klimov, P., Korotkov, A. N., Kostritsa, F., Kreikebaum, J. M., Landhuis, D., Langley, B. W., Laptev, P., Lau, K.-M., Guevel, L. Le, Ledford, J., Lee, J., Lee, K. W., Lensky, Y. D., Lester, B. J., Li, W. Y., Lill, A. T., Liu, W., Livingston, W. P., Locharla, A., Lundahl, D., Lunt, A., Madhuk, S., Maloney, A., Mandrà, S., Martin, L. S., Martin, O., Martin, S., Maxfield, C., McClean, J. R., McEwen, M., Meeks, S., Miao, K. C., Mieszala, A., Molina, S., Montazeri, S., Morvan, A., Movassagh, R., Neill, C., Nersisyan, A., Newman, M., Nguyen, A., Nguyen, M., Ni, C.-H., Niu, M. Y., Oliver, W. D., Ottosson, K., Pizzuto, A., Potter, R., Pritchard, O., Pryadko, L. P., Quintana, C., Reagor, M. J., Rhodes, D. M., Roberts, G., Rocque, C., Rosenberg, E., Rubin, N. C., Saei, N., Sankaragomathi, K., Satzinger, K. J., Schurkus, H. F., Schuster, C., Shearn, M. J., Shorter, A., Shutty, N., Shvarts, V., Sivak, V., Skruzny, J., Small, S., Smith, W. Clarke, Springer, S., Sterling, G., Suchard, J., Szalay, M., Sztein, A., Thor, D., Torres, A., Torunbalci, M. M., Vaishnav, A., Vdovichev, S., Villalonga, B., Heidweiller, C. Vollgraff, Waltman, S., Wang, S. X., White, T., Wong, K., Woo, B. W. K., Xing, C., Yao, Z. Jamie, Yeh, P., Ying, B., Yoo, J., Yosri, N., Young, G., Zalcman, A., Zhu, N., Zobrist, N., Neven, H., Babbush, R., Boixo, S., Hilton, J., Lucero, E., Megrant, A., Kelly, J., Chen, Y., Smelyanskiy, V., Vidal, G., Roushan, P., Läuchli, A. M., Abanin, D. A., and Mi, X.

Published
2025
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248. Human immune organoids to decode B cell response in healthy donors and patients with lymphoma

Author

Zhong, Zhe, Quiñones-Pérez, Manuel, Dai, Zhonghao, Juarez, Valeria M., Bhatia, Eshant, Carlson, Christopher R., Shah, Shivem B., Patel, Anjali, Fang, Zhou, Hu, Thomas, Allam, Mayar, Hicks, Sakeenah L., Gupta, Mansi, Gupta, Sneh Lata, Weeks, Ethan, Vagelos, Stephanie D., Molina, Alejandro, Mulero-Russe, Adriana, Mora-Boza, Ana, Joshi, Devyani J., Sekaly, Rafick P., Sulchek, Todd, Goudy, Steven L., Wrammert, Jens, Roy, Krishnendu, Boss, Jeremy M., Coskun, Ahmet F., Scharer, Christopher D., García, Andrés J., Koff, Jean L., and Singh, Ankur

Published
2025
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