activity
20232026
most citedCaloHadronic: a diffusion model for the generation of hadronic showers

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

physics.ins-det2026

Point-cloud generative models for fast calorimeter simulation across particles and geometries

Thorsten Buss, Henry Day-Hall, Frank Gaede +7

Detailed Geant4 simulation of calorimeter showers is the largest single computing cost of collider experiments, and the High-Luminosity LHC will need about ten times more simulated…

hep-ex2026

Jevons' Paradox and Fast Generative Simulation for HEP: Why Realistic Benchmarking is Essential

Thorsten Buss, Henry Day-Hall, Frank Gaede +7

Simulation is a major computational expense in HEP, and calorimeter simulation in particular drives the overall energy cost of our physics analyses. Future detectors will contain m…

physics.ins-det2026

SPADE: Split-and-Delay Embeddings for Autoregressive High-Granularity Calorimeter Simulation

Joschka Birk, Frank Gaede, Anna Hallin +3

We introduce SPADE (SPlit And Delay Embeddings), an autoregressive transformer for sequences whose tokens carry multiple features. Rather than embedding these features jointly, SPA…

physics.ins-det2025

CaloClouds3: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation

Thorsten Buss, Henry Day-Hall, Frank Gaede +7

We present CaloClouds3, a model for the fast simulation of photon showers in the barrel of a high granularity detector. This iteration demonstrates for the first time how a pointcl…

physics.ins-det2025★ 1 cited

CaloHadronic: a diffusion model for the generation of hadronic showers

Thorsten Buss, Frank Gaede, Gregor Kasieczka +4

Simulating showers of particles in highly-granular calorimeters is a key frontier in the application of machine learning to particle physics. Achieving high accuracy and speed with…

hep-ph2025

OmniJet-: Learning point cloud calorimeter simulations using generative transformers

Joschka Birk, Frank Gaede, Anna Hallin +3

We show the first use of generative transformers for generating calorimeter showers as point clouds in a high-granularity calorimeter. Using the tokenizer and generative part of th…

hep-ex2023

GNN for Deep Full Event Interpretation and hierarchical reconstruction of heavy-hadron decays in proton-proton collisions

Julián García Pardiñas, Marta Calvi, Jonas Eschle +4

The LHCb experiment at the Large Hadron Collider (LHC) is designed to perform high-precision measurements of heavy-hadron decays, which requires the collection of large data sample…