2 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
Differentiable Surrogate for Detector Simulation and Design with Diffusion Models
Xuan Tung Nguyen, Long Chen, Tommaso Dorigo +7
In this work, we present a conditional denoising-diffusion surrogate for electromagnetic calorimeter showers that is trained to generate high-fidelity energy-deposition maps condit…
End-to-End Detector Optimization with Diffusion models: A Case Study in Sampling Calorimeters
Kylian Schmidt, Nikhil Kota, Jan Kieseler +16
Recent advances in machine learning have opened new avenues for optimizing detector designs in high-energy physics, where the complex interplay of geometry, materials, and physics…
Hadron Identification Prospects With Granular Calorimeters
Andrea De Vita, Abhishek, Max Aehle +15
In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time…