CMS FlashSim: how ML powers end-to-end simulation for HEP

The CMS Collaboration developed an end-to-end ML based simulation that can speed up the time for production of analysis samples of several orders of magnitude with a limited loss of accuracy. Detailed event simulation at the LHC is crucial for physics analyses and it is currently taking a large fraction of computing budget. Because the CMS experiment is adopting a common analysis level format (the NANOAOD) for a larger number of analyses, such an event representation is used as the target of this ultra fast simulation, which we call FlashSim. Generator level events, from PYTHIA or other generators, are directly translated into NANOAOD events at several hundred Hz rate with FlashSim. We show how training FlashSim on a limited number of full simulation events is sufficient to achieve very good accuracy on larger datasets for processes not seen at training time. With this work, we aim to update the community about recent and relevant developments behind the FlashSim framework.

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Publication Details

Published
2025-12-17
DOI
https://doi.org/10.22323/1.485.0077
Primary Topic
Particle physics theoretical and experimental studies
Type
article
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article

CMS FlashSim: how ML powers end-to-end simulation for HEP

Particle physics theoretical and experimental studies
article

CMS FlashSim: how ML powers end-to-end simulation for HEP

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Abstract

The CMS Collaboration developed an end-to-end ML based simulation that can speed up the time for production of analysis samples of several orders of magnitude with a limited loss of accuracy. Detailed event simulation at the LHC is crucial for physics analyses and it is currently taking a large fraction of computing budget. Because the CMS experiment is adopting a common analysis level format (the NANOAOD) for a larger number of analyses, such an event representation is used as the target of this ultra fast simulation, which we call FlashSim. Generator level events, from PYTHIA or other generators, are directly translated into NANOAOD events at several hundred Hz rate with FlashSim. We show how training FlashSim on a limited number of full simulation events is sufficient to achieve very good accuracy on larger datasets for processes not seen at training time. With this work, we aim to update the community about recent and relevant developments behind the FlashSim framework.

Scuola Normale Superiore (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Pisa (IT)
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Particle physics theoretical and experimental studies
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