Kimberly J Daas, Heng Zhao, Elias Polak, Stefan Vuckovic
{"title":"Exact Mo̷ller-Plesset Adiabatic Connection Correlation Energy Densities.","authors":"Kimberly J Daas, Heng Zhao, Elias Polak, Stefan Vuckovic","doi":"10.1021/acs.jctc.5c00348","DOIUrl":null,"url":null,"abstract":"<p><p>The Mo̷ller-Plesset adiabatic connection (MPAC) provides a powerful tool for developing density functional theory (DFT)-like approximations that map Hartree-Fock densities to the wave function-based correlation energy, thereby leveraging both wave function and DFT concepts for electronic structure approximations. A key object in this context is the correlation energy density, which represents the local (pointwise) contribution to the total correlation energy. While well-studied in DFT, it remains largely unexplored in the wave function framework. Here, we introduce a rigorous formulation of the wave function-based correlation energy density within MPAC, implement it via full configuration interaction calculations, and analyze its behavior and physically meaningful contributions for representative small (di)atomic systems. We define this quantity by employing a general gauge strategy, from which the conventional DFT correlation energy density gauge also arises. We then discuss the resulting commonalities and differences between correlation energy densities in the DFT and wave function frameworks and derive the small-interaction (MP2) limit of the latter in terms of Hartree-Fock orbitals. Finally, we show how these newly introduced energy densities can serve as new approximation targets in both machine-learning-assisted and traditional electronic structure methods for mapping HF-density-based features to correlation energy within the wave function framework.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"5501-5513"},"PeriodicalIF":5.5000,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Chemical Theory and Computation","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acs.jctc.5c00348","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/21 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The Mo̷ller-Plesset adiabatic connection (MPAC) provides a powerful tool for developing density functional theory (DFT)-like approximations that map Hartree-Fock densities to the wave function-based correlation energy, thereby leveraging both wave function and DFT concepts for electronic structure approximations. A key object in this context is the correlation energy density, which represents the local (pointwise) contribution to the total correlation energy. While well-studied in DFT, it remains largely unexplored in the wave function framework. Here, we introduce a rigorous formulation of the wave function-based correlation energy density within MPAC, implement it via full configuration interaction calculations, and analyze its behavior and physically meaningful contributions for representative small (di)atomic systems. We define this quantity by employing a general gauge strategy, from which the conventional DFT correlation energy density gauge also arises. We then discuss the resulting commonalities and differences between correlation energy densities in the DFT and wave function frameworks and derive the small-interaction (MP2) limit of the latter in terms of Hartree-Fock orbitals. Finally, we show how these newly introduced energy densities can serve as new approximation targets in both machine-learning-assisted and traditional electronic structure methods for mapping HF-density-based features to correlation energy within the wave function framework.
Mo ^ lller - plesset绝热连接(MPAC)为开发类似密度泛函理论(DFT)的近似提供了一个强大的工具,该近似将Hartree-Fock密度映射到基于波函数的相关能,从而利用波函数和DFT概念进行电子结构近似。在这种情况下,一个关键对象是相关能量密度,它表示局部(点方向)对总相关能量的贡献。虽然在DFT中得到了很好的研究,但在波函数框架中仍未得到很大程度的探索。在此,我们引入了MPAC中基于波函数的相关能量密度的严格公式,通过全构型相互作用计算实现了它,并分析了它的行为和具有代表性的小(di)原子系统的物理意义贡献。我们通过采用一般规范策略来定义这个量,由此也产生了传统的DFT相关能量密度规范。然后,我们讨论了DFT和波函数框架中相关能量密度的共性和差异,并推导了后者在Hartree-Fock轨道下的小相互作用(MP2)极限。最后,我们展示了这些新引入的能量密度如何在机器学习辅助和传统电子结构方法中作为新的近似目标,用于将基于高频密度的特征映射到波函数框架内的相关能量。
期刊介绍:
The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.