Zobrazeno 1 - 10
of 1 688
pro vyhledávání: '"PEREZ, ANDRES"'
We carry out a Bayesian analysis of dark matter (DM) direct detection data to determine particle model parameters using the Truncated Marginal Neural Ratio Estimation (TMNRE) machine learning technique. TMNRE avoids an explicit calculation of the lik
Externí odkaz:
http://arxiv.org/abs/2407.21008
The detection of Dark Matter (DM) remains a significant challenge in particle physics. This study exploits advanced machine learning models to improve detection capabilities of liquid xenon time projection chamber experiments, utilizing state-of-the-
Externí odkaz:
http://arxiv.org/abs/2406.10372
Autor:
Abbas, Ammar N., Amazu, Chidera W., Mietkiewicz, Joseph, Briwa, Houda, Perez, Andres Alonzo, Baldissone, Gabriele, Demichela, Micaela, Chasparis, Georgios G., Kelleher, John D., Leva, Maria Chiara
Publikováno v:
International Journal of Human-Computer Interaction, 2024
In complex industrial and chemical process control rooms, effective decision-making is crucial for safety and efficiency. The experiments in this paper evaluate the impact and applications of an AI-based decision support system integrated into an imp
Externí odkaz:
http://arxiv.org/abs/2402.13219
Autor:
Arganda, Ernesto, Díaz, Daniel A., Perez, Andres D., Seoane, Rosa M. Sandá, Szynkman, Alejandro
We study the impact of machine-learning algorithms on LHC searches for leptoquarks in final states with hadronically decaying tau leptons, multiple $b$-jets, and large missing transverse momentum. Pair production of scalar leptoquarks with decays onl
Externí odkaz:
http://arxiv.org/abs/2309.05407
Autor:
Kasliwal, Mansi M., Bally, John, Masci, Frank, Cody, Ann Marie, Bond, Howard E., Jencson, Jacob E., Tinyanont, Samaporn, Cao, Yi, Contreras, Carlos, Dykhoff, Devin A., Amodeo, Samuel, Armus, Lee, Boyer, Martha, Cantiello, Matteo, Carlon, Robert L., Cass, Alexander C., Cook, David, Corgan, David T., Faella, Joseph, Fox, Ori D., Green, Wayne, Gehrz, R. D., Helou, George, Hsiao, Eric, Johansson, Joel, Khan, Rubab M., Lau, Ryan M., Langer, Norbert, Levesque, Emily, Milne, Peter, Mohamed, Shazrene, Morrell, Nidia, Monson, Andy, Moore, Anna, Ofek, Eran O., Sullivan, Donal O’, Parthasarathy, Mudumba, Perez, Andres, Perley, Daniel A., Phillips, Mark, Prince, Thomas A., Shenoy, Dinesh, Smith, Nathan, Surace, Jason, Dyk, Schuyler D. Van, Whitelock, Patricia A., Williams, Robert
We present an ongoing, five-year systematic search for extragalactic infrared transients, dubbed SPIRITS-SPitzer InfraRed Intensive Transients Survey. In the first year, using Spitzer/IRAC, we searched 190 nearby galaxies with cadence baselines of on
Externí odkaz:
http://hdl.handle.net/10150/624045
http://arizona.openrepository.com/arizona/handle/10150/624045
http://arizona.openrepository.com/arizona/handle/10150/624045
Machine-Learned Likelihoods (MLL) combines machine-learning classification techniques with likelihood-based inference tests to estimate the experimental sensitivity of high-dimensional data sets. We extend the MLL method by including Kernel Density E
Externí odkaz:
http://arxiv.org/abs/2211.04806
A palha de cana-de-açúcar está se tornando uma biomassa lignocelulósica disponível a partir da progressiva introdução da colheita mecanizada da cana-deaçúcar no Brasil, situação que possibilita a utilização de uma parte desta como matér
Publikováno v:
JCAP04(2023)050
We investigate the possibility that right-handed (RH) sneutrinos and gravitinos can coexist and explain the dark matter (DM) problem. We compare extensions of the minimal supersymmetric standard model (MSSM) and the next-to-MSSM (NMSSM) adding RH neu
Externí odkaz:
http://arxiv.org/abs/2206.04715