Search Results for author:
Found 5 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.
Artificial Intelligence for the Electron Ion Collider (AI4EIC)
The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028.
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.
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
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.
