Results 21 to 30 of about 5,283,131 (297)
Design, testing, commissioning, and early operation of the third-generation n_TOF neutron spallation target at CERN [PDF]
EPJ Web of Conferences, 2023 The n_TOF facility at the European Laboratory for Particle Physics (CERN) is a top-class, high-brightness neutron spallation source dedicated to high-resolution neutron time-of-flight experiments.
Esposito Raffaele +2 more
doaj +1 more source
A new advance on dimensional-aware scalar, vector and matrix operations in C++
Scientific Reports, 2023 We review the dimensional check problem of the high-level programming languages, discuss the existing solutions, and come up with a new solution suited for scientific and engineering computations.
Eduard George Stan +3 more
doaj +1 more source
Gapped Goldstones at the cut-off scale: a non-relativistic EFT
Journal of High Energy Physics, 2021 At finite density, the spontaneous breakdown of an internal non-Abelian symmetry dictates, along with gapless modes, modes whose gap is fixed by the algebra and proportional to the chemical potential: the gapped Goldstones.
G. Cuomo +5 more
doaj +1 more source
Particle Physics with ORCA [PDF]
EPJ Web of Conferences, 2019 KM3NeT is a Megaton-scale neutrino telescope currently under construction at the bottom of the Mediterranean Sea. When completed, it will consist of two separate detectors: ARCA (Astroparticle Research with Cosmics in the Abyss), optimised for high-energy neutrino astronomy, and ORCA (Oscillation Research with Cosmics in the Abyss) for neutrino ...
Domi, Alba, Bourret, Simon, Quinn, Liam
openaire +6 more sources
Learning from radiation at a very high energy lepton collider
Journal of High Energy Physics, 2022 We study the potential of lepton collisions with about 10 TeV center of mass energy to probe Electroweak, Higgs and Top short-distance physics at the 100 TeV scale, pointing out the interplay with the long-distance (100 GeV) phenomenon of Electroweak ...
Siyu Chen +4 more
doaj +1 more source
Graph neural networks in particle physics [PDF]
Machine Learning: Science and Technology, 2020 Particle physics is a branch of science aiming at discovering the fundamental laws of matter and forces. Graph neural networks are trainable functions which operate on graphs—sets of elements and their pairwise relations—and are a central method within ...
Jonathan Shlomi +2 more
semanticscholar +1 more source
A resource efficient approach for quantum and classical simulations of gauge theories in particle physics [PDF]
Quantum, 2020 Gauge theories establish the standard model of particle physics, and lattice gauge theory (LGT) calculations employing Markov Chain Monte Carlo (MCMC) methods have been pivotal in our understanding of fundamental interactions.
J. Haase +6 more
semanticscholar +1 more source
On phase-space integrals with Heaviside functions
Journal of High Energy Physics, 2022 We discuss peculiarities that arise in the computation of real-emission contributions to observables that contain Heaviside functions. A prominent example of such a case is the zero-jettiness soft function in SCET, whose calculation at next-to-next-to ...
Daniel Baranowski +3 more
doaj +1 more source
On non-factorisable contributions to t-channel single-top production
Journal of High Energy Physics, 2021 We compute the non-factorisable contribution to the two-loop helicity amplitude for t-channel single-top production, the last missing piece of the two-loop virtual corrections to this process.
Christian Brønnum-Hansen +3 more
doaj +1 more source
SciPost Physics Proceedings, 2021 Particle physics results of constant value and significant impact have been obtained at PSI, and several efforts are presently ongoing and expected to deliver new findings in the near future. In this special SciPost volume we collect them together in a concise manner.
Adrian Signer +4 more
openaire +3 more sources