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arXiv · 2503.23657

JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport Equations

Wenjie Shang·Jiahang Zhou·J. P. Panda·Zhihao Xu·Yi Liu·Pan Du·Jian-Xun Wang·Tengfei Luo
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Abstract

This paper introduces JAX-BTE, a GPU-accelerated, differentiable solver for the phonon Boltzmann Transport Equation (BTE) based on differentiable programming. JAX-BTE enables accurate, efficient and differentiable multiscale thermal modeling by leveraging high-performance GPU computing and automatic differentiation. The solver efficiently addresses the high-dimensional and complex integro-differential nature of the phonon BTE, facilitating both forward simulations and data-augmented inverse simulations through end-to-end optimization. Validation is performed across a range of 1D to 3D simulations, including complex FinFET structures, in both forward and inverse settings, demonstrating excellent performance and reliability. JAX-BTE significantly outperforms state-of-the-art BTE solvers in forward simulations and uniquely enables inverse simulations, making it a powerful tool for multiscale thermal analysis and design for semiconductor devices.

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Wenjie Shang, Jiahang Zhou, J. P. Panda, Zhihao Xu, Yi Liu, Pan Du, Jian-Xun Wang, Tengfei Luo. 2025-04-01. JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport Equations. https://arxiv.org/abs/2503.23657

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