7th Inter-Experimental LHC Machine Learning Workshop

Interdisciplinary Digital Twin Engine InterTwin for calorimeter simulation

Not scheduled

20m

61/1-201 - Pas perdus - Not a meeting room - (CERN)

Poster 3 ML for simulation and surrogate model: Application of ML for simulation or cases of replacing an existing complex model Poster Session

Speaker

Vera Maiboroda (Université Paris-Saclay (FR))

Description

The interTwin project develops an open-source Digital Twin Engine to integrate application-specific Digital Twins (DTs) across scientific domains. Its framework for the development of DTs supports interoperability, performance, portability and accuracy. As part of this initiative, we implemented the CaloINN normalizing-flow model for calorimeter simulations within the interTwin framework. Calorimeter shower simulations are computationally expensive, and generative models offer an efficient alternative. However, achieving a balance between accuracy and speed remains a challenge, with distribution tail modeling being a key limitation. CaloINN provides a trade-off between simulation quality and efficiency. We validated the model using CaloChallenge datasets and high granularity simulations from the Open Data Detector. This work demonstrates the applicability of the interTwin platform for high-energy physics simulations and highlights its potential for broader scientific use.