Results 31 to 40 of about 5,077 (103)

Finetuning foundation models for joint analysis optimization in High Energy Physics [PDF]

open access: yesMachine Learning: Science and Technology
In this work we demonstrate that significant gains in performance and data efficiency can be achieved in High Energy Physics (HEP) by moving beyond the standard paradigm of sequential optimization or reconstruction and analysis components.
M. Vigl, N. Hartman, L. Heinrich
semanticscholar   +1 more source

Software Training in High Energy Physics [PDF]

open access: yesJournal of Physics: Conference Series, 2022
Among the upgrades in current high energy physics (HEP) experiments and the new facilities coming online, solving software challenges has become integral to the success of the collaborations.
M. Villanueva   +2 more
semanticscholar   +1 more source

Quantum frontiers in high energy physics [PDF]

open access: yesScience China Physics, Mechanics & Astronomy
Numerous challenges persist in High Energy Physics (HEP), the addressing of which requires advancements in detection technology, computational methods, data analysis frameworks, and phenomenological designs.
Yaquan Fang   +8 more
semanticscholar   +1 more source

Neutrino Mass, Coupling Unification, Verifiable Proton Decay, Vacuum Stability, and WIMP Dark Matter in SU(5)

open access: yesAdvances in High Energy Physics, Volume 2018, Issue 1, 2018., 2018
Nonsupersymmetric minimal SU(5) with Higgs representations 24H and 5H and standard fermions in 5¯F⊕10F is well known for its failure in unification of gauge couplings and lack of predicting neutrino masses. Like standard model, it is also affected by the instability of the Higgs scalar potential.
Biswonath Sahoo   +3 more
wiley   +1 more source

Machine learning in scientific grant review: algorithmically predicting project efficiency in high energy physics

open access: yesEuropean Journal for Philosophy of Science, 2022
As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we
Vlasta Sikimić, S. Radovanović
semanticscholar   +1 more source

Abstracts

open access: yes, 2021
Research and Practice in Thrombosis and Haemostasis, Volume 5, Issue S2, October 2021.
wiley   +1 more source

Analysis of Requirements for the Design of a Detector Control System in a High Energy Physics (HEP) Experiment [PDF]

open access: yesProceedings of 7th Annual Conference on Large Hadron Collider Physics — PoS(LHCP2019), 2019
In this work the use of the Rational Unified Process (RUP) to model the design of a Detector Control System (DCS) in a High-Energy Physics (HEP) experiment is proposed.
J. C. Cabanillas-Noris   +3 more
semanticscholar   +1 more source

Very High Energy Physics and Astronomy with Tau and Photon Probes

open access: yesProceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022), 2022
Very-high energy physics (VHEP) is the development of a higher energy frontier complementary to accelerator-based HEP to investigate interactions in space caused by fundamental particles and to study the structure and fundamental interactions of ...
M. Sasaki
semanticscholar   +1 more source

Abstract Book: 25th Congress of the European Hematology Association Virtual Edition, 2020

open access: yes, 2020
HemaSphere, Volume 4, Issue S1, Page 1-1168, June 2020.
wiley   +1 more source

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

open access: yesFrontiers in High Performance Computing
Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High ...
C. Lee   +7 more
semanticscholar   +1 more source

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