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arXiv · 2509.26527

Interdisciplinary Digital Twin Engine InterTwin for calorimeter simulation

Corentin Allaire·Vera Maiboroda·David Rousseau
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Abstract

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. Invertible generative network CaloINN provides a trade-off between simulation quality and efficiency. The ongoing study targets introducing a set of post-processing modifications of analysis-level observables aimed at improving the accuracy of distribution tails. As part of interTwin project initiative developing an open-source Digital Twin Engine, we implemented the CaloINN within the interTwin AI framework.

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Corentin Allaire, Vera Maiboroda, David Rousseau. 2025-09-30. Interdisciplinary Digital Twin Engine InterTwin for calorimeter simulation. https://arxiv.org/abs/2509.26527

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