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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

Traditional methods in quantum chemistry rely on Hartree-Fock-based Slater-determinant (SD) representations, whose underlying zeroth-order picture assumes separability by particle. Here, we explore a radically different approach, based on…

Quantum Physics · Physics 2022-03-02 Bill Poirier , Jonathan Jerke

The accuracy and efficiency of ab-initio quantum Monte Carlo (QMC) algorithms benefits greatly from compact variational trial wave functions that accurately reproduce ground state properties of a system. We investigate the possibility of…

Materials Science · Physics 2019-01-30 Shivesh Pathak , Lucas K. Wagner

Quantum simulation of chemical systems is one of the most promising near-term applications of quantum computers. The variational quantum eigensolver, a leading algorithm for molecular simulations on quantum hardware, has a serious…

Quantum Physics · Physics 2019-07-16 Harper R. Grimsley , Sophia E. Economou , Edwin Barnes , Nicholas J. Mayhall

Quantum Monte Carlo (QMC) methods such as variational Monte Carlo and fixed node diffusion Monte Carlo depend heavily on the quality of the trial wave function. Although Slater-Jastrow wave functions are the most commonly used variational…

Materials Science · Physics 2015-05-28 Bryan K. Clark , Miguel A. Morales , Jeremy McMinis , Jeongnim Kim , Gustavo E. Scuseria

Quantum-selected configuration interaction (QSCI) is an approach for quantum chemical calculations using current quantum computers. In conventional QSCI, Slater determinants used for the wave function expansion are sampled by iteratively…

Quantum Physics · Physics 2025-10-03 Kenji Sugisaki , Shu Kanno , Toshinari Itoko , Rei Sakuma , Naoki Yamamoto

Harnessing the full power of nascent quantum processors requires the efficient management of a limited number of quantum bits with finite lifetime. Hybrid algorithms leveraging classical resources have demonstrated promising initial results…

An algorithm to compute efficiently the first two derivatives of (very) large multideterminant wavefunctions for quantum Monte Carlo calculations is presented. The calculation of determinants and their derivatives is performed using the…

Chemical Physics · Physics 2017-04-20 Anthony Scemama , Thomas Applencourt , Emmanuel Giner , Michel Caffarel

A deep-learning approach to optimize the selection of Slater determinants in configuration interaction calculations for condensed-matter quantum many-body systems is developed. We exemplify our algorithm on the discrete version of the…

Strongly Correlated Electrons · Physics 2025-02-11 Pavlo Bilous , Louis Thirion , Henri Menke , Maurits W. Haverkort , Adriana Pálffy , Philipp Hansmann

Quantum computing brings a promise of new approaches into computational quantum chemistry. While universal, fault-tolerant quantum computers are still not available, we want to utilize today's noisy quantum processors. One of their flagship…

The variational quantum eigensolver (or VQE) uses the variational principle to compute the ground state energy of a Hamiltonian, a problem that is central to quantum chemistry and condensed matter physics. Conventional computing methods are…

Quantum chemistry provides a target for quantum simulation of considerable scientific interest and industrial importance. The majority of algorithms to date have been based on a second-quantized representation of the electronic structure…

Quantum Physics · Physics 2013-12-17 Borzu Toloui , Peter J. Love

A quantum Monte Carlo method of determining Jastrow-Slater wave functions for which the energy is stationary with respect to variations in the single-particle orbitals is presented. A potential is determined by a least-squares fitting of…

Condensed Matter · Physics 2007-05-23 Stephen Fahy , Claudia Filippi

Computationally efficient and accurate quantum mechanical approximations to solve the many-electron Schr\"odinger equation are at the heart of computational materials science. In that respect the coupled cluster hierarchy of methods plays a…

Materials Science · Physics 2022-01-11 Tina N. Mihm , Tobias Schäfer , Sai Kumar Ramadugu , Andreas Grüneis , James J. Shepherd

Selected configuration interaction (SCI) methods, when complemented with a second-order perturbative correction, provide near full configuration interaction (FCI) quality energies with only a small fraction of the Slater determinants of the…

Choosing a basis set is the first step of a quantum chemistry calculation and it sets its maximum accuracy. This choice of orbitals is limited by strong technical constraints as one must be able to compute a large number of six dimensional…

Strongly Correlated Electrons · Physics 2026-02-04 Nicolas Jolly , Yuriel Núñez Fernández , Xavier Waintal

By exploiting the invariance of the molecular Hamiltonian by a unitary transformation of the orbitals it is possible to significantly shorter the depth of the variational circuit in the Variational Quantum Eigensolver (VQE) algorithm by…

Quantum Physics · Physics 2025-09-03 Leonardo Ratini , Chiara Capecci , Leonardo Guidoni

We propose a modification of the Variational Quantum Eigensolver algorithm for electronic structure optimization using quantum computers, named non-unitary Variational Quantum Eigensolver (nu-VQE), in which a non-unitary operator is…

Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with unitary coupled cluster ansatz, we demonstrate that…

For the variational quantum eigensolver we propose to generate trial wavefunctions from a small amount of selected Pauli terms of the problem Hamiltonian. Two different approaches, one inspired by the quantum approximate optimization…

Quantum Physics · Physics 2019-08-27 Gian Salis , Nikolaj Moll
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