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Non-orthogonal multi-Slater determinant expansions in auxiliary field quantum Monte Carlo

Edgar Josué Landinez Borda

Published Jun 29, 2023• 38 citations
Publisher

Abstract

We investigate here the use of non-orthogonal multi-Slater determinant (NOMSD) expansions as trial wavefunctions in auxiliary field quantum Monte Carlo simulations of molecular systems. We show that NOMSD trial wavefunctions with as few as twenty determinants are sufficient in order to achieve chemical accuracy across most of the G1 molecular test set. We also show that NOMSD trial wavefunctions are useful for more challenging strongly correlated systems by computing relative energies along the isomerization path of the [Cu2O2]2+ molecule. Our results for [Cu2O2]2+ compare favorably with other accurate quantum many-body methods, including density matrix renormalization group and completely renormalized coupled cluster methods.

DOI
10.1063/1.5049143

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We investigate here the use of non-orthogonal multi-Slater determinant (NOMSD) expansions as trial wavefunctions in auxiliary field quantum Monte Carlo simulations of molecular systems. We show that NOMSD trial wavefunctions with as few as twenty determinants are sufficient in order to achieve chemical accuracy across most of the G1 molecular test set. We also show that NOMSD trial wavefunctions are useful for more challenging strongly correlated systems by computing relative energies along the isomerization path of the [Cu2O2]2+ molecule. Our results for [Cu2O2]2+ compare favorably with other accurate quantum many-body methods, including density matrix renormalization group and completely renormalized coupled cluster methods.
We investigate the use of non-orthogonal multi-Slater determinant (NOMSD) expansions as trial wavefunctions in auxiliary field quantum Monte Carlo simulations of molecular systems. We show that NOMSD trial wavefunctions with as few as twenty determinants are sufficient in order to achieve chemical accuracy across most of the G1 molecular test set. We also show that NOMSD trial wavefunctions are useful for more challenging strongly correlated systems by computing relative energies along the isomerization path of the [Cu2O2]2+ molecule. Our results for [Cu2O2]2+ compare favorably with other accurate quantum many-body methods, including density matrix renormalization group and completely renormalized coupled cluster methods.
For optimal accuracy, auxiliary-field quantum Monte Carlo (AFQMC) requires trial states consisting of multiple Slater determinants. We develop an efficient algorithm to select the determinants from an AFQMC random walk eliminating the need for other methods. When determinants contribute significantly to the non-orthogonal configuration interaction energy, we include them in the trial state. These refined trial wave functions significantly reduce the phaseless bias and sampling variance of the local energy estimator. With 100 to 200 determinants, we lower the error of AFQMC by up to a factor of 10 for second row elements that are not accurately described with a Hartree-Fock trial wave function. For the HEAT set, we improve the average error to within the chemical accuracy. For benzene, the largest studied system, we reduce AFQMC error by 80% with 214 Slater determinants and find a 10-fold increase of the time to solution. We show that the remaining error of the method prevails in systems with static correlation or strong spin contamination.
For optimal accuracy, auxiliary-field quantum Monte Carlo (AFQMC) requires trial states consisting of multiple Slater determinants. We develop an efficient algorithm to select the determinants from an AFQMC random walk eliminating the need for other methods. When determinants contribute significantly to the nonorthogonal configuration interaction energy, we include them in the trial state. These refined trial wave functions significantly reduce the phaseless bias and sampling variance of the local energy estimator. With 100 to 200 determinants, we lower the error of AFQMC by up to a factor of 10 for second-row elements that are not accurately described with a Hartree-Fock trial wave function. For the HEAT set, we improve the average error to within chemical accuracy. For benzene, the largest studied system, we reduce AFQMC error by 80% with 214 Slater determinants and find a 10-fold increase of the time to solution. We show that phaseless errors prevail in systems with static correlation or strong spin contamination. For such systems, improved trial states enable stable free-projection AFQMC calculations, achieving chemical accuracy even in the strongly correlated regime.
We explore different ways of incorporating accurate trial wave functions into free projection auxiliary field quantum Monte Carlo (fp-AFQMC). Trial states employed include coupled cluster singles and doubles, multi-Slater, and symmetry projected mean-field wave functions. We adapt a recently proposed fast multi-Slater local energy evaluation algorithm for fp-AFQMC, making the use of long expansions from selected configuration interaction methods feasible. We demonstrate how these trial wave functions serve to mitigate the sign problem and accelerate convergence in quantum chemical problems, allowing the application of fp-AFQMC to systems of substantial sizes. Our calculations on the widely studied Cu2O22+\text{Cu}_2\text{O}_2^{2+}Cu2​O22+​ model system show that many previously reported isomerization energies differ substantially from the near-exact fp-AFQMC value.
We explore different ways of incorporating accurate trial wave functions into free projection auxiliary-field quantum Monte Carlo (fp-AFQMC). States employed include coupled-cluster singles and doubles, multi-Slater, and symmetry-projected mean-field wave functions. We adapt a recently proposed fast multi-Slater local energy evaluation algorithm for fp-AFQMC, making the use of long expansions from selected configuration interaction methods feasible. We demonstrate how these wave functions serve to mitigate the sign problem and accelerate convergence in quantum chemical problems, allowing the application of fp-AFQMC to systems of substantial sizes. Our calculations on the widely studied model Cu 2 O 2 2+ system show that many previously reported isomerization energies differ substantially from the near-exact fp-AFQMC value.
We introduce an efficient approach to implement correlated many-body trial wave functions in auxiliary-field quantum Monte Carlo (AFQMC). To control the sign/phase problem in AFQMC, a constraint is derived from an exact gauge condition but is typically imposed approximately through a trial wave function or trial density matrix, whose quality can affect the accuracy of the method. Furthermore, the trial wave function can also affect the efficiency through importance sampling. The most natural form of the trial wave function has been single Slater determinants or their linear combinations. More sophisticated forms, for example, with the inclusion of a Jastrow factor or other explicit correlations, have been challenging to use, and their implementation is often assumed to require a quantum computer. In this work, we demonstrate that a large class of correlated wave functions, written in the general form of multi-dimensional integrals over hidden or auxiliary variables times Slater determinants, can be implemented as a trial wave function by coupling the random walkers to a generalized Metropolis sampling. We discuss the fidelity of AFQMC with stochastically sampled trial wave functions, which are relevant to both quantum and classical algorithms. We illustrate the method and show that an efficient implementation can be achieved, which preserves the computational scaling of AFQMC. We test our method in molecules under bond stretching and in transition metal diatomics. Significant improvements are seen in both accuracy and efficiency over typical trial wave functions, and the method yields total ground-state energies systematically within chemical accuracy. The method can be useful for incorporating other advanced wave functions, for example, neural quantum state wave functions optimized from machine learning techniques, or for other forms of fermion quantum Monte Carlo.