Physical Review X · 2024 · 11 citations · 70 references
Natural SciencesMaterials SciencePhysicsComputational Materials ScienceElectronic MaterialsMaterials PhysicsAb Initio MethodsApproximation MethodsElectron CorrelationElectron-phonon InteractionsExchange InteractionsStrongly Correlated Electron SystemsComputational EfficiencyElectron-electron InteractionsElectron-phonon ScatteringPhonon CalculationsPhonon-phonon Interactions
First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (<a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mi>e</a:mi><a:mtext>−</a:mtext><a:mrow><a:mi>ph</a:mi></a:mrow></a:mrow></a:math>) 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 <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" display="inline"><c:mrow><c:mi>e</c:mi><c:mtext>−</c:mtext><c:mrow><c:mi>ph</c:mi></c:mrow></c:mrow></c:math> 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:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"><e:mrow><e:mi>e</e:mi><e:mtext>−</e:mtext><e:mrow><e:mi>ph</e:mi></e:mrow></e:mrow></e:math> 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 <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" display="inline"><g:mrow><g:mi>e</g:mi><g:mtext>−</g:mtext><g:mrow><g:mi>ph</g:mi></g:mrow></g:mrow></g:math> 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 <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"><i:mrow><i:mi>e</i:mi><i:mtext>−</i:mtext><i:mrow><i:mi>ph</i:mi></i:mrow></i:mrow></i:math> interactions. Furthermore, they accelerate state-of-the-art first-principles <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" display="inline"><k:mrow><k:mi>e</k:mi><k:mtext>−</k:mtext><k:mrow><k:mi>ph</k:mi></k:mrow></k:mrow></k:math> calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:mrow><m:mi>e</m:mi><m:mtext>−</m:mtext><m:mrow><m:mi>ph</m:mi></m:mrow></m:mrow></m:math> interactions can be readily generalized to electron-electron and electron-defect interactions, as well as to other couplings, advancing quantitative studies of condensed matter. Published by the American Physical Society 2024
70
Generalized Gradient Approximation Made Simple
John P. Perdew, Kieron Burke, Matthias Ernzerhof · Physical Review Letters · 1996 · 211.5K citations · Full text
Natural Sciences, Chemistry, Physics +16
SciPy 1.0: fundamental algorithms for scientific computing in Python
Nature Methods · 2020 · 37.9K citations · Full text
Deformation Potentials and Mobilities in Non-Polar Crystals
J. Bardeen, W. Shockley · Physical Review · 1950 · 3.8K citations