数据驱动的电子-鹭鸶相互作用压缩

IF 11.6 1区 物理与天体物理 Q1 PHYSICS, MULTIDISCIPLINARY Physical Review X Pub Date : 2024-05-01 DOI:10.1103/physrevx.14.021023
Yao Luo, Dhruv Desai, Benjamin K. Chang, Jinsoo Park, Marco Bernardi
{"title":"数据驱动的电子-鹭鸶相互作用压缩","authors":"Yao Luo, Dhruv Desai, Benjamin K. Chang, Jinsoo Park, Marco Bernardi","doi":"10.1103/physrevx.14.021023","DOIUrl":null,"url":null,"abstract":"First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (<math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></math> interactions. Furthermore, they accelerate state-of-the-art first-principles <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></math> calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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.","PeriodicalId":20161,"journal":{"name":"Physical Review X","volume":null,"pages":null},"PeriodicalIF":11.6000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data-Driven Compression of Electron-Phonon Interactions\",\"authors\":\"Yao Luo, Dhruv Desai, Benjamin K. Chang, Jinsoo Park, Marco Bernardi\",\"doi\":\"10.1103/physrevx.14.021023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (<math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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 <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></math> interactions. Furthermore, they accelerate state-of-the-art first-principles <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></math> calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mrow><mi>e</mi><mtext>−</mtext><mrow><mi>ph</mi></mrow></mrow></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.\",\"PeriodicalId\":20161,\"journal\":{\"name\":\"Physical Review X\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.6000,\"publicationDate\":\"2024-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical Review X\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1103/physrevx.14.021023\",\"RegionNum\":1,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Review X","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1103/physrevx.14.021023","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

近年来,材料中电子相互作用的第一性原理计算进展迅速,电子-声子(e-ph)相互作用就是一个典型的例子。然而,这些技术使用大型矩阵在密集动量网格上对相互作用进行编码,从而降低了计算效率,模糊了可解释性。对于 e-ph 相互作用,现有的插值技术利用了实空间的局部性,但数据的高维度仍然是平衡成本和精度的瓶颈。在这里,我们展示了一种基于奇异值分解(SVD)的高效方法来压缩电子相位相互作用,奇异值分解是一种广泛使用的矩阵和图像压缩技术。利用(无)约束的 SVD 方法,我们准确地预测了与 e-ph 相互作用相关的材料特性--包括电荷迁移率、自旋弛豫时间、带重正化和超导临界温度--同时只使用了一小部分(1%-2%)的相互作用数据。这些发现揭示了电子ph相互作用隐藏的低维性质。此外,它们还在不牺牲精度的情况下,将最先进的第一原理 e-ph 计算速度提高了约 2 个数量级。我们对 e-ph 相互作用的帕累托最优参数化很容易推广到电子-电子和电子-缺陷相互作用以及其他耦合,从而推进凝聚态物质的定量研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Data-Driven Compression of Electron-Phonon Interactions
First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (eph) 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 eph 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 eph 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 eph 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 eph interactions. Furthermore, they accelerate state-of-the-art first-principles eph calculations by about 2 orders of magnitude without sacrificing accuracy. Our Pareto-optimal parametrization of eph interactions can be readily generalized to electron-electron and electron-defect interactions, as well as to other couplings, advancing quantitative studies of condensed matter.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Physical Review X
Physical Review X PHYSICS, MULTIDISCIPLINARY-
CiteScore
24.60
自引率
1.60%
发文量
197
审稿时长
3 months
期刊介绍: Physical Review X (PRX) stands as an exclusively online, fully open-access journal, emphasizing innovation, quality, and enduring impact in the scientific content it disseminates. Devoted to showcasing a curated selection of papers from pure, applied, and interdisciplinary physics, PRX aims to feature work with the potential to shape current and future research while leaving a lasting and profound impact in their respective fields. Encompassing the entire spectrum of physics subject areas, PRX places a special focus on groundbreaking interdisciplinary research with broad-reaching influence.
期刊最新文献
Impact of Nuclear Motion on Light-Induced Bimolecular Interaction Dynamics Quantum Entanglement between Optical and Microwave Photonic Qubits Geometric Landscape Annealing as an Optimization Principle Underlying the Coherent Ising Machine Theory of Stimulated Brillouin Scattering in Fibers for Highly Multimode Excitations Theoretical Description of Pump-Probe Experiments in Charge-Density-Wave Materials out to Long Times
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1