Zobrazeno 1 - 10
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pro vyhledávání: '"Childers, J."'
Autor:
Lersch, Daniel, Schram, Malachi, Dai, Zhenyu, Rajput, Kishansingh, Wu, Xingfu, Sato, N., Childers, J. Taylor
Large scale, inverse problem solving deep learning algorithms have become an essential part of modern research and industrial applications. The complexity of the underlying inverse problem often poses challenges to the algorithm and requires the prop
Externí odkaz:
http://arxiv.org/abs/2407.00051
Autor:
Campbell, J. M., Diefenthaler, M., Hobbs, T. J., Höche, S., Isaacson, J., Kling, F., Mrenna, S., Reuter, J., Alioli, S., Andersen, J. R., Andreopoulos, C., Ankowski, A. M., Aschenauer, E. C., Ashkenazi, A., Baker, M. D., Barrow, J. L., van Beekveld, M., Bewick, G., Bhattacharya, S., Bierlich, C., Bothmann, E., Bredt, P., Broggio, A., Buckley, A., Butter, A., Butterworth, J. M., Byrne, E. P., Calame, C. M. Carloni, Chakraborty, S., Chen, X., Chiesa, M., Childers, J. T., Cruz-Martinez, J., Currie, J., Darvishi, N., Dasgupta, M., Denner, A., Dreyer, F. A., Dytman, S., El-Menoufi, B. K., Engel, T., Ravasio, S. Ferrario, Figueroa, D., Flower, L., Forshaw, J. R., Frederix, R., Friedland, A., Frixione, S., Gallagher, H., Gallmeister, K., Gardiner, S., Gauld, R., Gaunt, J., Gavardi, A., Gehrmann, T., Ridder, A. Gehrmann-De, Gellersen, L., Giele, W., Gieseke, S., Giuli, F., Glover, E. W. N., Grazzini, M., Grohsjean, A., Gütschow, C., Hamilton, K., Han, T., Hatcher, R., Heinrich, G., Helenius, I., Hen, O., Hirschi, V., Höfer, M., Holguin, J., Huss, A., Ilten, P., Jadach, S., Jentsch, A., Jones, S. P., Ju, W., Kallweit, S., Karlberg, A., Katori, T., Kerner, M., Kilian, W., Kirchgaeßer, M. M., Klein, S., Knobbe, M., Krause, C., Krauss, F., Lang, J., Lang, J. -N., Lee, G., Li, S. W., Lim, M. A., Lindert, J. M., Lombardi, D., Lönnblad, L., Löschner, M., Lurkin, N., Ma, Y., Machado, P., Magerya, V., Maier, A., Majer, I., Maltoni, F., Marcoli, M., Marinelli, G., Masouminia, M. R., Mastrolia, P., Mattelaer, O., Mazzitelli, J., McFayden, J., Medves, R., Meinzinger, P., Mo, J., Monni, P. F., Montagna, G., Morgan, T., Mosel, U., Nachman, B., Nadolsky, P., Nagar, R., Nagy, Z., Napoletano, D., Nason, P., Neumann, T., Nevay, L. J., Nicrosini, O., Niehues, J., Niewczas, K., Ohl, T., Ossola, G., Pandey, V., Papadopoulou, A., Papaefstathiou, A., Paz, G., Pellen, M., Pelliccioli, G., Peraro, T., Piccinini, F., Pickering, L., Pires, J., Płaczek, W., Plätzer, S., Plehn, T., Pozzorini, S., Prestel, S., Preuss, C. T., Price, A. C., Quackenbush, S., Re, E., Reichelt, D., Reina, L., Reuschle, C., Richardson, P., Rocco, M., Rocco, N., Roda, M., Garcia, A. Rodriguez, Roiser, S., Rojo, J., Rottoli, L., Salam, G. P., Schönherr, M., Schuchmann, S., Schumann, S., Schürmann, R., Scyboz, L., Seymour, M. H., Siegert, F., Signer, A., Chahal, G. Singh, Siódmok, A., Sjöstrand, T., Skands, P., Smillie, J. M., Sobczyk, J. T., Soldin, D., Soper, D. E., Soto-Ontoso, A., Soyez, G., Stagnitto, G., Tena-Vidal, J., Tomalak, O., Tramontano, F., Trojanowski, S., Tu, Z., Uccirati, S., Ullrich, T., Ulrich, Y., Utheim, M., Valassi, A., Verbytskyi, A., Verheyen, R., Wagman, M., Walker, D., Webber, B. R., Weinstein, L., White, O., Whitehead, J., Wiesemann, M., Wilkinson, C., Williams, C., Winterhalder, R., Wret, C., Xie, K., Yang, T-Z., Yazgan, E., Zanderighi, G., Zanoli, S., Zapp, K.
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular
Externí odkaz:
http://arxiv.org/abs/2203.11110
Massive upgrades to science infrastructure are driving data velocities upwards while stimulating adoption of increasingly data-intensive analytics. While next-generation exascale supercomputers promise strong support for I/O-intensive workflows, HPC
Externí odkaz:
http://arxiv.org/abs/2105.06571
Publikováno v:
SciPost Physics, Vol 16, Iss 5, p 130 (2024)
We provide an overview of the status of Monte-Carlo event generators for high-energy particle physics. Guided by the experimental needs and requirements, we highlight areas of active development, and opportunities for future improvements. Particular
Externí odkaz:
https://doaj.org/article/6d302e68b67d446fb25dfe23dc60084a
Autor:
Salim, Michael A., Uram, Thomas D., Childers, J. Taylor, Balaprakash, Prasanna, Vishwanath, Venkatram, Papka, Michael E.
We introduce the Balsam service to manage high-throughput task scheduling and execution on supercomputing systems. Balsam allows users to populate a task database with a variety of tasks ranging from simple independent tasks to dynamic multi-task wor
Externí odkaz:
http://arxiv.org/abs/1909.08704
Autor:
Vidal, X. Cid, D'Onofrio, M., Fox, P. J., Torre, R., Ulmer, K. A., Aboubrahim, A., Albert, A., Alimena, J., Allanach, B. C., Alpigiani, C., Altakach, M., Amoroso, S., Anders, J. K., Araz, J. Y., Arbey, A., Azzi, P., Babounikau, I., Baer, H., Baker, M. J., Barducci, D., Barger, V., Baron, O., Navarro, L. Barranco, Battaglia, M., Bay, A., Bhatia, D., Biswas, S., Bloch, D., Bogavac, D., Borschensky, C., Bugge, M. K., Buttazzo, D., Cacciapaglia, G., Cadamuro, L., Calandri, A., Camargo, D. A., Canepa, A., Carminati, L., Carrá, S., Montoya, C. A. Carrillo, De Oliveira, A. Carvalho Antunes, Castillo, F. L., Cavaliere, V., Cavalli, D., Cecchi, C., Celis, A., Cerri, A., Chahal, G. S., Chakraborty, A., Chekanov, S. V., Cheng, H. J., Childers, J. T., Cirelli, M., Colegrove, O., Corcella, G., Corradi, M., Costa, M. J., Covarelli, R., Dang, N. P., Deandrea, A., De Curtis, S., De la Torre, H., Rose, L. Delle, Del Re, D., Demela, A., Demers, S., Dermisek, R., De Santo, A., Deshpande, K., Dey, B., Donini, J., Duncan, A. K., Dutta, V., Escobar, C., Fanó, L., Ferretti, G., Fiaschi, J., Fischer, O., Flacke, T., Frangipane, E. D., Frank, M., Frattari, G., Frizzell, D., Fuchs, E., Fuks, B., Gabrielli, E., Gainer, J., Gao, Y., Navarro, J. E. García, Genest, M. H., Giagu, S., Giudice, G. F., Goh, J., Gouzevitch, M., Govoni, P., Greljo, A., Grohsjean, A., Gurrola, A., Gustavino, G., Guyot, C., Gwilliam, C. B., Ha, S., Haisch, U., Haller, J., Han, T., Hayden, D., Heikinheimo, M., Heintz, U., Helsens, C., Hoepfner, K., Hogan, J. M., Huitu, K., Ilten, P., Ippolito, V., Ismail, A., Iyer, A. M., Jain, Sa., Jamin, D. O., Jeanty, L., Jezo, T., Johns, W., Kalogeropoulos, A., Karancsi, J., Kats, Y., Keller, H., Khanov, A., Kieseler, J., Kim, B., Kim, M. S., Kim, Y. G., Klasen, M., Klimek, M. D., Kogler, R., Komaragiri, J. R., Krämer, M., Kubota, S., Kulesza, A. K., Kulkarni, S., Lari, T., Ledovskoy, A., Lee, G. R., Lee, L., Lee, S. W., Leonardi, R., Les, R., Lewis, I. M., Li, Q., Li, T., Lim, I. T., Lim, S. H., Lin, K., Liu, Z., Long, K., Low, M., Lunghi, E., Madaffari, D., Mahmoudi, F., Majumder, D., Malvezzi, S., Mangano, M. L., Manoni, E., Marcano, X., Mariotti, A., Marjanovic, M., Marlow, D., Camalich, J. Martin, Cuevas, P. Matorras, McCullough, M., McDonald, E. F., Guisao, J. Mejia, Mele, B., Meloni, F., Melzer-Pellmann, I. -A., Merlassino, C., Meyer, A. B., Michielin, E., Miller, A. J., Mittnacht, L., Mondal, S., Moretti, S., Mukhopadhyay, S., Nachman, B. P., Nam, K., Narain, M., Nardecchia, M., Nath, P., Navarro-González, J., Nisati, A., Nitta, T., Noel, D. L., Nojiri, M. M., Ochoa-Ricoux, J. P., Oide, H., Ojeda, M. L., Griso, S. Pagan, Cortezon, E. Palencia, Panella, O., Pani, P., Panizzi, L., Panwar, L., Park, C. B., Pazzini, J., Pedro, K., Perego, M. M., Perrozzi, L., Petersen, B. A., Pierce, A., Polesello, G., Policicchio, A., Potter, C. J., Pralavorio, P., Presilla, M., Proudfoot, J., Queiroz, F. S., Ramirez-Sanchez, G., Redigolo, D., Reimers, A., Resconi, S., Rimoldi, M., Vergara, J. C. Rivera, Rizzo, T., Rogan, C., Romeo, F., Rosten, R., Ruiz, R., Ruiz-Alvarez, J., Iglesias, J. A. Sabater, Samani, B. Safarzadeh, Sagir, S., Saito, M., Saito, S., Sala, F., Salazar, C., Savin, A., Sawada, R., Sawant, S., Schienbein, I., Schlaffer, M., Schneider, B., Schuler, S. C., Sebastiani, C. D., Sekmen, S., Selvaggi, M., Sengupta, D., Serce, H., Serodio, H., Sestini, L., Shakya, B., Haghi, B. Shams Es, Sheldon, P., Shin, S., Simonetto, F., Soffi, L., Spannowsky, M., Stupak, J., Sullivan, M. J., Sunder, M., Takahashi, Y., Tata, X., Teagle, H., Terashi, K., Tesi, A., Thamm, A., Tobioka, K., Tornambe, P., Trovato, F., Tsiakkouri, D., Ungaro, F. C., Urbano, A., Usai, E., Vanegas, N., Vaslin, L., Sierra, C. Vázquez, Vivarelli, I., Milosavljevic, M. Vranjes, Waltari, H., Wang, R., Wang, X., Weber, M. S., Weiland, C., Wielers, M., Williams, J. M., Willocq, S., Xu, D., Yagyu, K., Yazgan, E., Ye, R., Yoo, H. D., You, T., Yu, F., Della Porta, G. Zevi, Zhang, W., Zhu, C., Zhuang, X., Zobec, J., Zupan, J., Zurita, J.
This is the third out of five chapters of the final report [1] of the Workshop on Physics at HL-LHC, and perspectives on HE-LHC [2]. It is devoted to the study of the potential, in the search for Beyond the Standard Model (BSM) physics, of the High L
Externí odkaz:
http://arxiv.org/abs/1812.07831
Autor:
Falkowski, Alan G., da Costa, Romarly F., Lima, Marco A. P., de A. Cadena, Alexi, Pocoroba, Ronald, Jones, Regan, Mathur, Mahak, Childers, J. G., Khakoo, Murtadha A., Kossoski, Fábris
Publikováno v:
Journal of Chemical Physics; 11/21/2023, Vol. 159 Issue 19, p1-15, 15p
Publikováno v:
JINST 13 (2018) P05022
This paper explores the physics reach of the High-Luminosity Large Hadron Collider (HL-LHC) for searches of new particles decaying to two jets. We discuss inclusive searches in dijets and b-jets, as well as searches in semi-inclusive events by requir
Externí odkaz:
http://arxiv.org/abs/1710.09484
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As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted
Externí odkaz:
http://arxiv.org/abs/1511.07312