JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport Equations
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915222139174912 |
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| author | Shang, Wenjie Zhou, Jiahang Panda, J. P. Xu, Zhihao Liu, Yi Du, Pan Wang, Jian-Xun Luo, Tengfei |
| author_facet | Shang, Wenjie Zhou, Jiahang Panda, J. P. Xu, Zhihao Liu, Yi Du, Pan Wang, Jian-Xun Luo, Tengfei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_23657 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport Equations Shang, Wenjie Zhou, Jiahang Panda, J. P. Xu, Zhihao Liu, Yi Du, Pan Wang, Jian-Xun Luo, Tengfei Computational Physics Mesoscale and Nanoscale Physics 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. |
| title | JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport Equations |
| topic | Computational Physics Mesoscale and Nanoscale Physics |
| url | https://arxiv.org/abs/2503.23657 |