Bridging Simulators with Conditional Optimal Transport

• URL: http://arxiv.org/abs/2510.24631v1
• Date: Tue, 28 Oct 2025 16:59:42 GMT
• Title: Bridging Simulators with Conditional Optimal Transport
• Authors: Justine Zeghal, Benjamin Remy, Yashar Hezaveh, Francois Lanusse, Laurence Perreault Levasseur,
• Abstract summary: We propose a new field-level emulator that bridges two simulators using unpaired simulation datasets.<n>We employ Optimal Transport Flow Matching to ensure that the transformation minimally distorts the underlying structure of the data.
• Score: 4.480951785759067
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a new field-level emulator that bridges two simulators using unpaired simulation datasets. Our method leverages a flow-based approach to learn the likelihood transport from one simulator to the other. Since multiple transport maps exist, we employ Conditional Optimal Transport Flow Matching (COT-FM) to ensure that the transformation minimally distorts the underlying structure of the data. We demonstrate the effectiveness of this approach by bridging weak lensing simulators: a Lagrangian Perturbation Theory (LPT) to a N-body Particle-Mesh (PM). We demonstrate that our emulator captures the full correction between the simulators by showing that it enables full-field inference to accurately recover the true posterior, validating its accuracy beyond traditional summary statistics.

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