Results 1 to 10 of about 24,628,551 (174)

Consistent searches for SMEFT effects in non-resonant dilepton events [PDF]

Journal of High Energy Physics, 2017
Employing the framework of the Standard Model Effective Field Theory, we perform a detailed reinterpretation of measurements of the Weinberg angle in dilepton production as a search for new-physics effects. We truncate our signal prediction at order 1/Λ2,
Stefan Alte, Matthias König, W. Shepherd   +2 more
semanticscholar   +1 more source

Superconformal field theory in three dimensions: correlation functions of conserved currents

Journal of High Energy Physics, 2015
For N\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathcal{N} $$\end{
E. Buchbinder, S. Kuzenko, I. Samsonov
semanticscholar   +1 more source

On the central charge of spacetime current algebras and correlators in string theory on AdS3

Journal of High Energy Physics, 2015
Spacetime Virasoro and affine Lie algebras for strings propagating in AdS3 are known to all orders in α′. The central extension of such algebras is a string vertex, whose expectation value can depend on the number of long strings present in the ...
Jihun Kim, M. Porrati
semanticscholar   +1 more source

Evaluating Awkward Arrays, uproot, and coffea as a query platform for High Energy Physics Data

Journal of Physics, Conference Series, 2023
Query languages for High Energy Physics (HEP) are an ever present topic within the field. A query language that can efficiently represent the nested data structures that encode the statistical and physical meaning of HEP data will help analysts by ...
L. Gray, N. Smith
semanticscholar   +1 more source

RG flow and thermodynamics of causal horizons in higher-derivative AdS gravity

Journal of High Energy Physics, 2016
In arXiv:1508.01343 [hep-th], one of the authors proposed that in AdS/CFT the gravity dual of the boundary c-theorem is the second law of thermodynamics satisfied by causal horizons in AdS and this was verified for Einstein gravity in the bulk.
Shamik Banerjee, Arpan Bhattacharyya
semanticscholar   +1 more source

FeynTune: large language models for high-energy theory [PDF]

Machine Learning: Science and Technology
We present specialized large language models (LLMs) for theoretical high-energy physics, obtained as 20 fine-tuned variants of the 8 billion parameter Llama-3.1 model.
Paul Richmond, C. Papageorgakis, V. Niarchos, Borun D. Chowdhury, P. Agarwal   +4 more
semanticscholar   +1 more source

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

Machine 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

Quantum information meets high-energy physics: input to the update of the European strategy for particle physics [PDF]

The European Physical Journal Plus
Some of the most astonishing and prominent properties of Quantum Mechanics, such as entanglement and Bell nonlocality, have only been studied extensively in dedicated low-energy laboratory setups.
Y. Afik, F. Fabbri, M. Low, L. Marzola, J. A. Aguilar-Saavedra, M. Altakach, N. Asbah, Yang Bai, Hannah Banks, Alan J. Barr, Alexander Bernal, T. Browder, P. Caban, J. A. Casas, Kun Cheng, F. D'eliot, R. Demina, A. Di Domenico, M. Eckstein, M. Fabbrichesi, Benjamin Fuks, Emidio Gabrielli, Dorival Gonçalves, R. Grabarczyk, Michele Grossi, Tao Han, T. Hobbs, Paweł Horodecki, J. Howarth, Shih-Chieh Hsu, S. Jiggins, E. Jones, A. Jung, A. Knue, S. Korn, T. Lagouri, P. Lamba, G. Landi, Haifeng Li, Qiang Li, I. Low, F. Maltoni, J. Mcfayden, N. McGinnis, Roberto A. Morales, J. M. Moreno, J. D. de Nova, Giulia Negro, D. Pagani, G. Pelliccioli, M. Pinamonti, L. Pintucci, B. Ravina, Alim Ruzi, K. Sakurai, E. Simpson, M. Sioli, Shu-Fang Su, S. Trifinopoulos, S. Vahsen, S. Vallecorsa, A. Vicini, M. Vos, E. Vryonidou, Chris D. White, Martin J. White, A. Wildridge, T. Wu, L. Zani, Yu-Lei Zhang, K. Zoch   +70 more
semanticscholar   +1 more source

Masked particle modeling on sets: towards self-supervised high energy physics foundation models [PDF]

Machine Learning: Science and Technology
We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data.
Lukas Heinrich, T. Golling, M. Kagan, Samuel Klein, Matthew Leigh, Margarita Osadchy, John Andrew Raine   +6 more
semanticscholar   +1 more source

Enabling stable preservation of ML algorithms in high-energy physics with petrifyML [PDF]

SciPost Physics Codebases
Machine learning (ML) in high-energy physics (HEP) has moved in the LHC era from an internal detail of experiment software, to an unavoidable public component of many physics data analyses.
Andy Buckley, L. Corpe, M. Habedank, T. Procter   +3 more
semanticscholar   +1 more source