3 papers
hep-ph2025
Discriminative versus Generative Approaches to Simulation-based Inference
Benjamin Sluijter, Sascha Diefenbacher, Wahid Bhimji +1
Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate…
physics.ins-det2023
Refining Fast Calorimeter Simulations with a Schrödinger Bridge
Sascha Diefenbacher, Vinicius Mikuni, Benjamin Nachman
Machine learning-based simulations, especially calorimeter simulations, are promising tools for approximating the precision of classical high energy physics simulations with a frac…
physics.ins-det2023
New Angles on Fast Calorimeter Shower Simulation
Sascha Diefenbacher, Engin Eren, Frank Gaede +5
The demands placed on computational resources by the simulation requirements of high energy physics experiments motivate the development of novel simulation tools. Machine learning…