2 citations · 3 across the 6 of their papers we have counts for
6 papers
New framework for extracting GPDs from exclusive photon electroproduction
Jian-Wei Qiu, Nobuo Sato, Zhite Yu
Recently, a new framework for studying generic hard exclusive reactions, referred to as single-diffractive hard exclusive processes, has been introduced to provide a clea…
Variational Neural Network Approach to QFT in the Field Basis
Kevin Braga, Nobuo Sato, Adam P. Szczepaniak
We present a variational neural network approach for solving quantum field theories in the field basis, focusing on the free Klein-Gordon model formulated in momentum space. While…
Point cloud-based diffusion models for the Electron-Ion Collider
Jack Y. Araz, Vinicius Mikuni, Felix Ringer +3
At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standar…
Unified and optimal frame choice for generalized parton distributions
Jian-Wei Qiu, Nobuo Sato, Zhite Yu
Reconstructing the internal three-dimensional quark and gluon structures of hadrons through generalized parton distributions (GPDs) from hard exclusive scattering processes is one…
Diffusion model approach to simulating electron-proton scattering events
Peter Devlin, Jian-Wei Qiu, Felix Ringer +1
Generative AI is a fast-growing area of research offering various avenues for exploration in high-energy nuclear physics. In this work, we explore the use of generative models for…
Accelerating Markov Chain Monte Carlo sampling with diffusion models
N. T. Hunt-Smith, W. Melnitchouk, F. Ringer +3
Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions. We introduce a novel method for accelerating Markov Ch…