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An analytical gradient theory for single-state N-electron valence state perturbation theory (NEVPT2), using both strongly contracted (SC) and partially contracted (PC) internal contraction schemes, is developed. We demonstrate the utility…

Chemical Physics · Physics 2020-12-16 Jae Woo Park

We present a many-body expansion (MBE) formulation and implementation for efficient computation of analytical energy gradients from OSV-MP2 theory based on our earlier work (Zhou et al. J. Chem. Theory Comput. 2020, 16, 196-210). The…

Chemical Physics · Physics 2021-11-15 Qiujiang Liang , Jun Yang

We derive analytic energy gradients of the driven similarity renormalization group (DSRG) multireference second-order perturbation theory (MRPT2) using the method of Lagrange multipliers. In the Lagrangian, we impose constraints for a…

Chemical Physics · Physics 2021-09-30 Shuhe Wang , Chenyang Li , Francesco A. Evangelista

We develop SOS-RILT-MP2, an efficient Gaussian-based periodic scaled opposite-spin second-order M{\o}ller-Plesset perturbation theory (SOS-MP2) algorithm that utilizes the resolution-of-the-identity approximation (RI) combined with the…

Chemical Physics · Physics 2025-03-27 Idan Haritan , Xiao Wang , Tamar Goldzak

Analytic energy gradients are presented for a variational two-electron reduced-density-matrix-driven complete active space self-consistent field (v2RDM-CASSCF) procedure that employs the density-fitting (DF) approximation to the…

Chemical Physics · Physics 2018-11-29 J. Wayne Mullinax , Evgeny Epifanovsky , Gergely Gidofalvi , A. Eugene DePrince

The second-order multireference driven similarity renormalization group perturbation theory (DSRG-MRPT2) theory provides an efficient means of correcting the dynamical correlation with the multiconfiguration reference function. The…

Chemical Physics · Physics 2022-02-01 Jae Woo Park

Analytical nuclear gradients for fully internally contracted complete active space second-order perturbation theory (CASPT2) are reported. This implementation has been realized by an automated code generator that can handle spin-free…

Chemical Physics · Physics 2015-02-11 Matthew K. MacLeod , Toru Shiozaki

Gradient compression is of growing interests for solving constrained optimization problems including compressed sensing, noisy recovery and matrix completion under limited communication resources and storage costs. Convergence analysis of…

Optimization and Control · Mathematics 2024-10-30 Zhaoyue Xia , Jun Du , Chunxiao Jiang , H. Vincent Poor , Yong Ren

The analytic energy gradients with respect to nuclear motion are derived for natural orbital functional (NOF) theory. The resulting equations do not require to resort to linear-response theory, so the computation of NOF energy gradients is…

Chemical Physics · Physics 2017-09-13 Ion Mitxelena , Mario Piris

A non-linear conjugate gradient optimization scheme is used to obtain excitation energies within the Random Phase Approximation (RPA). The solutions to the RPA eigenvalue equation are located through a variational characterization using a…

Materials Science · Physics 2011-11-21 Melissa J. Lucero , Anders M. N. Niklasson , Sergei Tretiak , Matt Challacombe

We introduce a reusable geometry-optimization engine in PyBEST for analytic, gradient-driven molecular structure optimization, with particular emphasis on orbital-optimized pair coupled-cluster doubles (OOpCCD/AP1roG). The engine interfaces…

Chemical Physics · Physics 2026-03-24 Saman Behjou , Iulia Emilia Brumboiu , Katharina Boguslawski

A stochastic orbital approach to the resolution of identity (RI) approximation for 4-index 2-electron electron repulsion integrals (ERIs) is presented. The stochastic RI-ERIs are then applied to M\o ller-Plesset perturbation theory (MP2)…

Chemical Physics · Physics 2017-04-10 Tyler Y. Takeshita , Wibe A. de Jong , Daniel Neuhauser , Roi Baer , Eran Rabani

We introduce a method for accurate quantum chemical calculations based on a simple variational wave function, defined by a single geminal that couples all the electrons into singlet pairs, combined with a real space correlation factor. The…

Materials Science · Physics 2009-10-22 M. Marchi , S. Azadi , M. Casula , S. Sorella

We present a revision to the well known Stormer-Verlet algorithm for simulating second order differential equations. The revision addresses the inclusion of linear friction with associated stochastic noise, and we analytically demonstrate…

Statistical Mechanics · Physics 2013-06-25 Niels Grønbech-Jensen , Oded Farago

We present a perturbative method for ab initio calculations of rotational and rovibrational effective Hamiltonians of both rigid and non-rigid molecules. Our approach is based on a curvilinear implementation of second order vibrational…

Chemical Physics · Physics 2016-11-04 P. Bryan Changala , Joshua H. Baraban

We present two efficient and intruder-free methods for treating dynamic correlation on top of general multi-configuration reference wave functions---including such as obtained by the density matrix renormalization group (DMRG) with large…

Chemical Physics · Physics 2016-09-13 Sandeep Sharma , Gerald Knizia , Sheng Guo , Ali Alavi

Quantum chemical methods dealing with challenging systems while retaining low computational costs have attracted attention. In particular, many efforts have been devoted to developing new methods based on the second-order perturbation that…

Chemical Physics · Physics 2023-10-30 Nhan Tri Tran , Hoang Thanh Nguyen , Lan Nguyen Tran

We develop and test methods that include second and third-order perturbation theory (MP3) using orbitals obtained from regularized orbital-optimized second-order perturbation theory, $\kappa$-OOMP2, denoted as MP3:$\kappa$-OOMP2. Testing…

Chemical Physics · Physics 2019-10-15 Luke W. Bertels , Joonho Lee , Martin Head-Gordon

Leveraging matrix sparsity has proven a fruitful strategy for accelerating quantum chemical calculations. Here we present the hierarchical SOS-MP2 algorithm, which uses hierarchical matrix ($\mathcal{H}^{2}$) compression of the electron…

Chemical Physics · Physics 2025-06-23 Hongji Gao , Xiangmin Jiao , Benjamin G. Levine

Gradient-based minimax optimal algorithms have greatly promoted the development of continuous optimization and machine learning. One seminal work due to Yurii Nesterov [Nes83a] established $\tilde{\mathcal{O}}(\sqrt{L/\mu})$ gradient…

Machine Learning · Computer Science 2023-12-07 Yuanshi Liu , Hanzhen Zhao , Yang Xu , Pengyun Yue , Cong Fang
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