Zobrazeno 1 - 10
of 231
pro vyhledávání: '"Buckley, Matthew R"'
Autor:
Krause, Claudius, Giannelli, Michele Faucci, Kasieczka, Gregor, Nachman, Benjamin, Salamani, Dalila, Shih, David, Zaborowska, Anna, Amram, Oz, Borras, Kerstin, Buckley, Matthew R., Buhmann, Erik, Buss, Thorsten, Cardoso, Renato Paulo Da Costa, Caterini, Anthony L., Chernyavskaya, Nadezda, Corchia, Federico A. G., Cresswell, Jesse C., Diefenbacher, Sascha, Dreyer, Etienne, Ekambaram, Vijay, Eren, Engin, Ernst, Florian, Favaro, Luigi, Franchini, Matteo, Gaede, Frank, Gross, Eilam, Hsu, Shih-Chieh, Jaruskova, Kristina, Käch, Benno, Kalagnanam, Jayant, Kansal, Raghav, Kim, Taewoo, Kobylianskii, Dmitrii, Korol, Anatolii, Korcari, William, Krücker, Dirk, Krüger, Katja, Letizia, Marco, Li, Shu, Liu, Qibin, Liu, Xiulong, Loaiza-Ganem, Gabriel, Madula, Thandikire, McKeown, Peter, Melzer-Pellmann, Isabell-A., Mikuni, Vinicius, Nguyen, Nam, Ore, Ayodele, Schweitzer, Sofia Palacios, Pang, Ian, Pedro, Kevin, Plehn, Tilman, Pokorski, Witold, Qu, Huilin, Raikwar, Piyush, Raine, John A., Reyes-Gonzalez, Humberto, Rinaldi, Lorenzo, Ross, Brendan Leigh, Scham, Moritz A. W., Schnake, Simon, Shimmin, Chase, Shlizerman, Eli, Soybelman, Nathalie, Srivatsa, Mudhakar, Tsolaki, Kalliopi, Vallecorsa, Sofia, Yeo, Kyongmin, Zhang, Rui
We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge. We study state-of-the-art generative models on four calorimeter shower datasets of increasing dimensionality, ranging from a few hundred voxels to a few t
Externí odkaz:
http://arxiv.org/abs/2410.21611
Autor:
Ramirez, Edward D., Sun, Yitian, Buckley, Matthew R., Mishra-Sharma, Siddharth, Slatyer, Tracy R.
Descriptions of the Galactic Center using Fermi gamma-ray data have so far modeled the Galactic Center Excess (GCE) as a template with fixed spatial morphology or as a linear combination of such templates. Although these templates are informed by var
Externí odkaz:
http://arxiv.org/abs/2410.21367
Supermassive black holes with masses $\gtrsim 10^9\,M_\odot$ have been discovered by JWST at high redshifts ($z\sim 7$). It is difficult to explain such objects as the result of accretive growth of stellar-mass seeds, as the rate at which baryons can
Externí odkaz:
http://arxiv.org/abs/2410.06252
Cosmological first order phase transitions are typically associated with physics beyond the Standard Model, and thus of great theoretical and observational interest. Models of phase transitions where the energy is mostly converted to dark radiation c
Externí odkaz:
http://arxiv.org/abs/2402.13309
Autor:
McQuinn, Kristen B. W., Mao, Yao-Yuan, Tollerud, Erik J., Cohen, Roger E., Shih, David, Buckley, Matthew R., Dolphin, Andrew E.
We report the discovery of two ultra-faint dwarf galaxies, Leo M and Leo K, that lie outside the halo of the Milky Way. Using Hubble Space Telescope imaging of the resolved stars, we create color-magnitude diagrams reaching the old main sequence turn
Externí odkaz:
http://arxiv.org/abs/2307.08738
We present a novel, data-driven analysis of Galactic dynamics, using unsupervised machine learning -- in the form of density estimation with normalizing flows -- to learn the underlying phase space distribution of 6 million nearby stars from the Gaia
Externí odkaz:
http://arxiv.org/abs/2305.13358
Publikováno v:
Phys. Rev. D 109, 033006 (2024)
Simulating particle detector response is the single most expensive step in the Large Hadron Collider computational pipeline. Recently it was shown that normalizing flows can accelerate this process while achieving unprecedented levels of accuracy, bu
Externí odkaz:
http://arxiv.org/abs/2305.11934
Autor:
Pettee, Mariel, Thanvantri, Sowmya, Nachman, Benjamin, Shih, David, Buckley, Matthew R., Collins, Jack H.
Large-scale astrophysics datasets present an opportunity for new machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional searches. To this end, we use Classification Without Labels (CWoLa), a weak
Externí odkaz:
http://arxiv.org/abs/2305.03761
Publikováno v:
JHEP 02 (2024) 029
Well-motivated models of dark matter often result in a population of electrons and positrons within galaxies produced through dark matter annihilation -- usually in association with gamma rays. As they diffuse through galactic magnetic fields, these
Externí odkaz:
http://arxiv.org/abs/2303.11354
We present an update to Via Machinae, an automated stellar stream-finding algorithm based on the deep learning anomaly detector ANODE. Via Machinae identifies stellar streams within Gaia, using only angular positions, proper motions, and photometry,
Externí odkaz:
http://arxiv.org/abs/2303.01529