14 citations · 35 across the 15 of their papers we have counts for
23 papers
Cross-geometry transfer and model collapse in point cloud calorimeter shower generation
Thorsten Buss, Frank Gaede, Gregor Kasieczka +2
Particle shower simulation is a major computational cost in high-energy physics. Monte Carlo methods such as Geant4 are accurate but expensive, while most machine learning surrogat…
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…
Interferometric Quantum Polynomial Chaos Expansion as a Generative Model for Calorimeter Shower Simulation
Jamal Slim, Saverio Monaco, Florian Rehm +3
We present the quantum polynomial chaos expansion, a generative algorithm in which a single circuit is the entire model, and we use it to learn calorimeter images. In a classical c…
Transferable Fast Calorimeter Shower Generation via Multi-Geometry Pre-training
Thorsten Buss, Henry Day-Hall, Frank Gaede +4
Detailed Geant4 simulation of calorimeter showers dominates the computing budget of high-energy physics experiments. Deep generative surrogates reduce this cost, but they have rema…
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…
AllShowers: One model for all calorimeter showers
Thorsten Buss, Henry Day-Hall, Frank Gaede +2
Accurate and efficient detector simulation is essential for modern collider experiments. To reduce the high computational cost, various fast machine learning surrogate models have…
Cross-Geometry Transfer Learning in Fast Electromagnetic Shower Simulation
Frank Gaede, Gregor Kasieczka, Lorenzo Valente
Accurate particle shower simulation remains a critical computational bottleneck for high-energy physics. Traditional Monte Carlo methods, such as Geant4, are computationally prohib…
A First Full Physics Benchmark for Highly Granular Calorimeter Surrogates
Thorsten Buss, Henry Day-Hall, Frank Gaede +5
The physics programs of current and future collider experiments necessitate the development of surrogate simulators for calorimeter showers. While much progress has been made in th…
Physics Briefing Book: Input for the 2026 update of the European Strategy for Particle Physics
Jorge de Blas, Monica Dunford, Emanuele Bagnaschi +127
The European Strategy for Particle Physics (ESPP) reflects the vision and presents concrete plans of the European particle physics community for advancing human knowledge in fundam…
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…
MuCol Milestone Report No. 7: Consolidated Parameters
Rebecca Taylor, Antoine Chancé, Dario Augusto Giove +459
This document is comprised of a collection of consolidated parameters for the key parts of the muon collider. These consolidated parameters follow on from the October 2024 Prelimin…
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…
The Muon Collider
Carlotta Accettura, Simon Adrian, Rohit Agarwal +450
Muons offer a unique opportunity to build a compact high-energy electroweak collider at the 10 TeV scale. A Muon Collider enables direct access to the underlying simplicity of the…
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…
Physics Performance and Detector Requirements at an Asymmetric Higgs Factory
Antoine Laudrain, Ties Behnke, Carl Mikael Berggren +7
The Hybrid Asymmetric Linear Higgs Factory (HALHF) proposes a shorter and cheaper design for a future Higgs factory. It reaches a GeV using a 500 GeV electron beam…
CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation
Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka +66
We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge. We study state-of-the-art generative models on four calorimeter shower datasets of i…
Sustainable computing workshops in high-energy physics at DESY
J. Alimena, C. Beyer, B. Bruers +8
This perspective article details the program of sustainable computing workshops launched within the High Energy Physics department at DESY in 2023. The workshop series targets scie…
Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows
Thorsten Buss, Frank Gaede, Gregor Kasieczka +2
In the quest to build generative surrogate models as computationally efficient alternatives to rule-based simulations, the quality of the generated samples remains a crucial fronti…
Focus topics for the ECFA study on Higgs / Top / EW factories
Jorge de Blas, Patrick Koppenburg, Jenny List +105
In order to stimulate new engagement and trigger some concrete studies in areas where further work would be beneficial towards fully understanding the physics potential of an $e^+e…
Towards podio v1.0 -- A first stable release of the EDM toolkit
Juan Miguel Carceller, Frank Gaede, Gerardo Ganis +6
A performant and easy-to-use event data model (EDM) is a key component of any HEP software stack. The podio EDM toolkit provides a user friendly way of generating such a performant…
Of Frames and schema evolution -- The newest features of podio
Placido Fernandez Declara, Frank Gaede, Gerardo Ganis +6
The podio event data model (EDM) toolkit provides an easy way to generate a performant implementation of an EDM from a high level description in yaml format. We present the most re…
Key4hep: Progress Report on Integrations
Erica Brondolin, Juan Miguel Carceller, Wouter Deconinck +22
Detector studies for future experiments rely on advanced software tools to estimate performance and optimize their design and technology choices. The Key4hep project provides a fle…
The Key4hep software stack: Beyond Future Higgs factories
Andre Sailer, Benedikt Hegner, Clement Helsens +18
The Key4hep project aims to provide a turnkey software solution for the full experiment lifecycle, based on established community tools. Several future collider communities (CEPC,…