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arXiv:2401.00019

Symbolic, numeric, and quantum computation of Hartree-Fock equation

Ichio Kikuchi, Akihito Kikuchi

Published Dec 27, 2023• 2 citations
arXivHTMLPDF

Abstract

In this article, we discuss how a kind of hybrid computation, which employs symbolic, numeric, classic, and quantum algorithms, allows us to conduct Hartree-Fock electronic structure computation of molecules. In the proposed algorithm, we replace the Hartree-Fock equations with a set of equations composed of multivariate polynomials. We transform those polynomials to the corresponding Gr\"obner bases, and then we investigate the corresponding quotient ring, wherein the orbital energies, the LCAO coefficients, or the atomic coordinates are represented by the variables in the ring. In this quotient ring, the variables generate the transformation matrices that represent the multiplication with the monomial bases, and the eigenvalues of those matrices compose the roots of the equation. The quantum phase estimation (QPE) algorithm enables us to record those roots in the quantum states, which would be used in the input data for more advanced and more accurate quantum computations.

DOI
10.31219/osf.io/e5d6w

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In this article, we discuss how a kind of hybrid computation, which employs symbolic, numeric, classic, and quantum algorithms, allows us to conduct Hartree-Fock electronic structure computation of molecules. In the proposed algorithm, we replace the Hartree-Fock equations with a set of equations composed of multivariate polynomials. We transform those polynomials to the corresponding Gr"obner bases, and then we investigate the corresponding quotient ring, wherein the orbital energies, the LCAO coefficients, or the atomic coordinates are represented by the variables in the ring. In this quotient ring, the variables generate the transformation matrices that represent the multiplication with the monomial bases, and the eigenvalues of those matrices compose the roots of the equation. The quantum phase estimation (QPE) algorithm enables us to record those roots in the quantum states, which would be used in the input data for more advanced and more accurate quantum computations.
This article presents a construction of a variational quantum eigensolver that allows us to calculate molecular orbitals. As the authors of the presented work have discussed in their preceding works, the variables in the molecular Hartree-Fock equation are represented by a set of transformation matrices. Those matrices have common eigenvectors, and the corresponding eigenvalues give the individual values of the variables that construct the solution of the Hatree-Fock equation. In other words, one can get the wavefunctions and the orbital energies through eigenvalue problems, which could be evaluated by quantum phase estimation. In this article, we use this formalism for another purpose: the transformation matrices are used to construct the total energy function so that the minimization of the total energy leads to an alternative approach of variational quantum eigensolver if the computation is conducted in a quantum computer.
In this paper, we present a quantum algorithm that enables us to perform first-principles molecular dynamics. In this algorithm, the optimum of wavefunctions and atomic structures is given by a root of a system of polynomial equations derived from the first principles of quantum mechanics. The computational steps consist of symbolic and quantum parts. First, the symbolic computation prepares a set of matrices whose eigenvalues are the roots of the given equation. Second, the quantum computation evaluates the eigenvectors and eigenvalues. In a preceding work, the authors presented another algorithm directed to the same end, and its deficiency is the complexity of the symbolic computations, which would be enormous in the worst cases. In this study, we try to reduce the cost of symbolic computation, utilizing the latest achievements of classical algorithms. Finally, we show how to transform this classical algorithm into a quantum one.
The full configuration interaction (full-CI) method is capable of providing the numerically best wave functions and energies of atoms and molecules within basis sets being used, although it is intractable for classical computers. Quantum computers can perform full-CI calculations in polynomial time against the system size by adopting a quantum phase estimation algorithm (QPEA). In the QPEA, the preparation of initial guess wave functions having sufficiently large overlap with the exact wave function is recommended. The Hartree-Fock (HF) wave function is a good initial guess only for closed shell singlet molecules and high-spin molecules carrying no spin-β unpaired electrons, around their equilibrium geometry, and thus, the construction of multiconfigurational wave functions without performing post-HF calculations on classical computers is highly desired for applying the method to a wide variety of chemistries and physics. In this work, we propose a method to construct multiconfigurational initial guess wave functions suitable for QPEA-based full-CI calculations on quantum computers, by utilizing diradical characters computed from spin-projected UHF wave functions. The proposed approach drastically improves the wave function overlap, particularly in molecules with intermediate diradical characters.
This article shows a proof of concept regarding the feasibility of ab initio molecular simulation, wherein the wavefunctions and the positions of nuclei are simultaneously determined by the quantum algorithm, as is realized by the so-called Car-Parrinello method by classical computing. The approach used in this article is of a hybrid style, which shall be realized by future fault-tolerant quantum computer. First, the basic equations are approximated by polynomials. Second, those polynomials are transformed to a specific form, wherein all variables (representing the wavefunctions and the atomic coordinates) are given by the transformations acting on a linear space of monomials with finite dimension, and the unknown variables could be determined as the eigenvalues of those transformation matrices. Third, the eigenvalues are determined by quantum phase estimation. Following these three steps, namely, symbolic, numeric, and quantum steps, we can determine the optimized electronic and atomic structures of molecules.
In this educational paper, we will discuss calculations on the hydrogen molecule on both classical and quantum computers. In the former case, we will discuss the calculation of molecular integrals that can then be used to calculate potential energy curves at the Hartree-Fock level and to correct them by obtaining the exact results for all states in the minimal basis. Some aspects of spin-symmetry will also be discussed. In the case of quantum computing, we will start out from the second-quantized Hamiltonian and qubit mappings. We then provide circuits for quantum phase estimation using two different algorithms: Trotterization and qubitization. Finally, the significance of quantum error correction will be briefly discussed.
In this article, we demonstrate the first-principles computation of quantum chemistry through symbolic computation, using computational algebraic geometry. We have developed a Python program that generates symbolic formulas of one- and two-electron integrals. The approximations of those integrals by multivariate polynomials yield the set of equations required by quantum chemistry. We solve these equations in hybrid ways where numeric and symbolic computations are intertwined. We discuss the possibility of the extension of our scheme to treat the models beyond the Born-Oppenheimer approximation.