Zobrazeno 1 - 10
of 15 535
pro vyhledávání: '"A Nachman"'
Autor:
Bhimji, Wahid, Calafiura, Paolo, Chakkappai, Ragansu, Chou, Yuan-Tang, Diefenbacher, Sascha, Dudley, Jordan, Farrell, Steven, Ghosh, Aishik, Guyon, Isabelle, Harris, Chris, Hsu, Shih-Chieh, Khoda, Elham E, Lyscar, Rémy, Michon, Alexandre, Nachman, Benjamin, Nugent, Peter, Reymond, Mathis, Rousseau, David, Sluijter, Benjamin, Thorne, Benjamin, Ullah, Ihsan, Zhang, Yulei
The FAIR Universe -- HiggsML Uncertainty Challenge focuses on measuring the physics properties of elementary particles with imperfect simulators due to differences in modelling systematic errors. Additionally, the challenge is leveraging a large-comp
Externí odkaz:
http://arxiv.org/abs/2410.02867
Autor:
Zhu, Huanbiao, Desai, Krish, Kuusela, Mikael, Mikuni, Vinicius, Nachman, Benjamin, Wasserman, Larry
In many experimental contexts, it is necessary to statistically remove the impact of instrumental effects in order to physically interpret measurements. This task has been extensively studied in particle physics, where the deconvolution task is calle
Externí odkaz:
http://arxiv.org/abs/2409.10421
Autor:
Kumar, Shachi H, Sahay, Saurav, Mazumder, Sahisnu, Okur, Eda, Manuvinakurike, Ramesh, Beckage, Nicole, Su, Hsuan, Lee, Hung-yi, Nachman, Lama
Large Language Models (LLMs) have excelled at language understanding and generating human-level text. However, even with supervised training and human alignment, these LLMs are susceptible to adversarial attacks where malicious users can prompt the m
Externí odkaz:
http://arxiv.org/abs/2408.03907
We introduce Resonant Anomaly Detection with Optimal Transport (RAD-OT), a method for generating signal templates in resonant anomaly detection searches. RAD-OT leverages the fact that the conditional probability density of the target features vary a
Externí odkaz:
http://arxiv.org/abs/2407.19818
Deconvolving ("unfolding'') detector distortions is a critical step in the comparison of cross section measurements with theoretical predictions in particle and nuclear physics. However, most existing approaches require histogram binning while many t
Externí odkaz:
http://arxiv.org/abs/2407.11284
Autor:
Dreyer, Etienne, Gross, Eilam, Kobylianskii, Dmitrii, Mikuni, Vinicius, Nachman, Benjamin, Soybelman, Nathalie
Detector simulation and reconstruction are a significant computational bottleneck in particle physics. We develop Particle-flow Neural Assisted Simulations (Parnassus) to address this challenge. Our deep learning model takes as input a point cloud (p
Externí odkaz:
http://arxiv.org/abs/2406.01620
Determining the form of the Higgs potential is one of the most exciting challenges of modern particle physics. Higgs pair production directly probes the Higgs self-coupling and should be observed in the near future at the High-Luminosity LHC. We expl
Externí odkaz:
http://arxiv.org/abs/2405.15847
Autor:
collaboration, CODEX-b, Aielli, Giulio, Alimena, Juliette, Beacham, James, Haim, Eli Ben, Burucs, Andras, Cardarelli, Roberto, Charles, Matthew, Vidal, Xabier Cid, De Roeck, Albert, Dey, Biplab, Dobrescu, Silviu, Durmus, Ozgur, Elashri, Mohamed, Gligorov, Vladimir, Suarez, Rebeca Gonzalez, Gorordo, Thomas, Gray, Zarria, Henderson, Conor, Henry, Louis, Ilten, Philip, Johnson, Daniel, Kautz, Jacob, Knapen, Simon, Liu, Bingxuan, Liu, Yang, Solino, Saul Lopez, Mombacher, Titus, Nachman, Benjamin, Northacker, David, Nowak, Gabriel, Papucci, Michele, Pasztor, Gabriella, Rial, Eloi Pazos, Pfaller, Jake, Pizzimento, Luca, Casasus, Maximo Plo, Rassati, Gian Andrea, Robinson, Dean, Fernandez, Emilio Xose Rodriguez, Sahoo, Debashis, Simsek, Sinem, Sokoloff, Michael, Suresh, Aditya, Swallow, Paul, Swanson, James, Vari, Riccardo, Sierra, Carlos Vazquez, Veres, Gabor, Watson, Nigel, Wilkinson, Michael, Williams, Michael
The CODEX-$\beta$ apparatus is a demonstrator for the proposed future CODEX-b experiment, a long-lived-particle detector foreseen for operation at IP8 during HL-LHC data-taking. The demonstrator project, intended to collect data in 2025, is described
Externí odkaz:
http://arxiv.org/abs/2406.12880
Autor:
Kobylianskii, Dmitrii, Soybelman, Nathalie, Kakati, Nilotpal, Dreyer, Etienne, Nachman, Benjamin, Gross, Eilam
The computational intensity of detector simulation and event reconstruction poses a significant difficulty for data analysis in collider experiments. This challenge inspires the continued development of machine learning techniques to serve as efficie
Externí odkaz:
http://arxiv.org/abs/2405.10106
We propose a new machine-learning-based anomaly detection strategy for comparing data with a background-only reference (a form of weak supervision). The sensitivity of previous strategies degrades significantly when the signal is too rare or there ar
Externí odkaz:
http://arxiv.org/abs/2405.08889