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Title: Exploring the synergy of kinematics and dynamics for collider physics

Journal Article · · Physical Review. D.

In collider experiments, an event is characterized by two distinct yet mutually complementary features: the “global features” and the “local features.” Kinematic information such as the event topology of a hard process, masses, and spins of particles comprises global features spanning the entire phase space. This global feature can be inferred from reconstructed objects. In contrast, representations of particles in gauge groups, such as quantum chromodynamics (QCD), offer localized features revealing the dynamics of an underlying theory. These local features, particularly observed in the patterns of radiation as raw data in various detector components, complement the global kinematic features. We propose a simple but effective neural network architecture that seamlessly integrates information from both kinematics and QCD to enhance the signal sensitivity at colliders. Published by the American Physical Society 2024

Sponsoring Organization:
USDOE
Grant/Contract Number:
SC0024673
OSTI ID:
2483744
Journal Information:
Physical Review. D., Journal Name: Physical Review. D. Journal Issue: 11 Vol. 110; ISSN PRVDAQ; ISSN 2470-0010
Publisher:
American Physical SocietyCopyright Statement
Country of Publication:
United States
Language:
English

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