2024-05-28 カリフォルニア工科大学(Caltech)
＜関連情報＞
- https://www.caltech.edu/about/news/speeding-up-calculations-that-reveal-how-electrons-interact-in-materials
- https://journals.aps.org/prx/abstract/10.1103/PhysRevX.14.021023
電子-フォノン相互作用のデータ駆動型圧縮 Data-Driven Compression of Electron-Phonon Interactions
Yao Luo, Dhruv Desai, Benjamin K. Chang, Jinsoo Park, and Marco Bernardi
Physical Review X Published: 1 May 2024
DOI:https://doi.org/10.1103/PhysRevX.14.021023
ABSTRACT
First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (−ph) interactions being a prime example. However, these techniques use large matrices encoding the interactions on dense momentum grids, which reduces computational efficiency and obscures interpretability. For −ph interactions, existing interpolation techniques leverage locality in real space, but the high dimensionality of the data remains a bottleneck to balance cost and accuracy. Here we show an efficient way to compress −ph interactions based on singular value decomposition (SVD), a widely used matrix and image compression technique. Leveraging (un)constrained SVD methods, we accurately predict material properties related to −ph interactions—including charge mobility, spin relaxation times, band renormalization, and superconducting critical temperature—while using only a small fraction (1%–2%) of the interaction data. These findings unveil the hidden low-dimensional nature of −ph interactions. Furthermore, they accelerate state-of-the-art first-principles −ph calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of −ph interactions can be readily generalized to electron-electron and electron-defect interactions, as well as to other couplings, advancing quantitative studies of condensed matter.
