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Data-Driven Compression of Electron-Phonon Interactions
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DOI：10.1103/PhysRevX.14.021023.png)
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First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (e-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 e-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 e-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 e-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 e-ph interactions. Furthermore, they accelerate state-of-the-art first-principles e-ph calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of e-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.
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DENSITY
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期刊
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15.7
论文数:
2.7K
被引数:
3.4W
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Wannier interpolation of the electron-phonon matrix elements in polar semiconductors: Polar-optical coupling in GaAs.png)
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