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Found 6 papers, 1 papers with code
Accelerating Markov Chain Monte Carlo sampling with diffusion models
Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions.
A survey of machine learning-based physics event generation
Event generators in high-energy nuclear and particle physics play an important role in facilitating studies of particle reactions.
First analysis of world polarized DIS data with small-$x$ helicity evolution
We present a Monte Carlo based analysis of the combined world data on polarized lepton-nucleon deep-inelastic scattering at small Bjorken $x$ within the polarized quark dipole formalism.
High Energy Physics - Phenomenology High Energy Physics - Experiment Nuclear Experiment Nuclear Theory
Simultaneous Monte Carlo analysis of parton densities and fragmentation functions
We perform a comprehensive new Monte Carlo analysis of high-energy lepton-lepton, lepton-hadron and hadron-hadron scattering data to simultaneously determine parton distribution functions (PDFs) in the proton and parton to hadron fragmentation functions (FFs).
High Energy Physics - Phenomenology High Energy Physics - Experiment Nuclear Theory
Octet and decuplet baryon self-energies in relativistic SU(3) chiral effective theory
The self-energies of the full set of flavor SU(3) octet and decuplet baryons are computed within a relativistic chiral effective theory framework.
High Energy Physics - Phenomenology Nuclear Theory
Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN)
We apply generative adversarial network (GAN) technology to build an event generator that simulates particle production in electron-proton scattering that is free of theoretical assumptions about underlying particle dynamics.
