Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI

Leander Thiele; Adrian E. Bayer; Naoya Takeishi

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arXiv · 2507.00514

Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI

Leander Thiele·Adrian E. Bayer·Naoya Takeishi

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Abstract

The simulation cost for cosmological simulation-based inference can be decreased by combining simulation sets of varying fidelity. We propose an approach to such multi-fidelity inference based on feature matching and knowledge distillation. Our method results in improved posterior quality, particularly for small simulation budgets and difficult inference problems.

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Leander Thiele, Adrian E. Bayer, Naoya Takeishi. 2025-07-01. Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI. https://arxiv.org/abs/2507.00514

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