240 citations · 1.9k across the 47 of their papers we have counts for
6 papers · 1 filter
Kicking it Off(-shell) with Direct Diffusion
Anja Butter, Tomas Jezo, Michael Klasen +3
Off-shell effects in large LHC backgrounds are crucial for precision predictions and, at the same time, challenging to simulate. We present a novel method to transform high-dimensi…
Rational Q-systems at Root of Unity I. Closed Chains
Jue Hou, Yunfeng Jiang, Yuan Miao
The solution of Bethe ansatz equations for XXZ spin chain with the parameter being a root of unity is infamously subtle. In this work, we develop the rational -system for th…
Precision-Machine Learning for the Matrix Element Method
Theo Heimel, Nathan Huetsch, Ramon Winterhalder +2
The matrix element method is the LHC inference method of choice for limited statistics. We present a dedicated machine learning framework, based on efficient phase-space integratio…
Artificial Intelligence for the Electron Ion Collider (AI4EIC)
C. Allaire, R. Ammendola, E. -C. Aschenauer +92
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. This is an opportune t…
Jet Diffusion versus JetGPT -- Modern Networks for the LHC
Anja Butter, Nathan Huetsch, Sofia Palacios Schweitzer +3
We introduce two diffusion models and an autoregressive transformer for LHC physics simulations. Bayesian versions allow us to control the networks and capture training uncertainti…
Searching for dark matter subhalos in the Fermi-LAT catalog with Bayesian neural networks
Anja Butter, Michael Krämer, Silvia Manconi +1
About a third of the -ray sources detected by the Fermi Large Area Telescope (Fermi-LAT) remain unidentified, and some of these could be exotic objects such as dark matter subha…