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arXiv:1611.02689 · Physical review. B./Physical review. B

Many-body computations by stochastic sampling in Hartree-Fock-Bogoliubov space

Hao Shi, Shiwei Zhang

Published Jan 27, 2017• 28 citations
arXivHTMLPDF

Abstract

We describe the computational ingredients for an approach to treat interacting fermion systems with pairing fields, based on path integrals in the space of Hartree-Fock-Bogoliubov (HFB) wave functions. The path integrals can be evaluated by Monte Carlo, via random walks of HFB wave functions whose orbitals evolve stochastically. The approach combines the advantage of HFB theory in paired fermion systems and many-body quantum Monte Carlo techniques. The properties of HFB states, written in the form of either product states or Thouless states, are discussed. The states preserve forms when propagated by generalized one-body operators. They can be stabilized for numerical iteration. Overlaps and one-body Green's functions between two such states can be computed. A constrained-path or phaseless approximation can be applied to the random walks of the HFB states if a sign problem or phase problem is present. The method is illustrated with an exact numerical projection in the Kitaev model, and in the Hubbard model with attractive interaction under an external pairing field.

DOI
10.1103/physrevb.95.045144

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We describe the computational ingredients for an approach to treat interacting fermion systems with pairing fields, based on path integrals in the space of Hartree-Fock-Bogoliubov (HFB) wave functions. The path integrals can be evaluated by Monte Carlo, via random walks of HFB wave functions whose orbitals evolve stochastically. The approach combines the advantage of HFB theory in paired fermion systems and many-body quantum Monte Carlo techniques. The properties of HFB states, written in the form of either product states or Thouless states, are discussed. The states preserve forms when propagated by generalized one-body operators. They can be stabilized for numerical iteration. Overlaps and one-body Green's functions between two such states can be computed. A constrained-path or phaseless approximation can be applied to the random walks of the HFB states if a sign problem or phase problem is present. The method is illustrated with an exact numerical projection in the Kitaev model, and in the Hubbard model with attractive interaction under an external pairing field.
Abstract The so-called phaseless quantum Monte-Carlo method currently offers one of the best performing theoretical framework to investigate interacting Fermi systems. It allows to extract an approximate ground-state wavefunction by averaging independent-particle states undergoing a Brownian motion in imaginary-time. Here, we extend the approach to a random walk in the space of Hartree–Fock–Bogoliubov (HFB) vacua that are better suited for superconducting or superfluid systems. Well-controlled statistical errors are ensured by constraining stochastic paths with the help of a trial wavefunction. It also guides the dynamics and takes the form of a linear combination of HFB ansätze. Estimates for the observables are reconstructed through an extension of Wick’s theorem to matrix elements between HFB product states. The usual combinatory complexity associated to the application of this theorem for four- and more- body operators is bypassed with a compact expression in terms of Pfaffians. The limiting case of a stochastic motion within Slater determinants but guided with HFB trial wavefunctions is also considered. Finally, exploratory results for the spin-polarized Hubbard model in the attractive regime are presented.
We explore the possibility of implementing random walks in the manifold of Hartree-Fock-Bogoliubov wave functions. The goal is to extend state-of-the-art quantum Monte Carlo approaches, in particular the constrained-path auxiliary-field quantum Monte Carlo technique, to systems where finite pairing order parameters or complex pairing mechanisms, e.g., Fulde-Ferrell-Larkin-Ovchinnikov pairing or triplet pairing, may be expected. Leveraging the flexibility to define a vacuum state tailored to the physical problem, we discuss a method to use imaginary-time evolution of Hartree-Fock-Bogoliubov states to compute ground state correlations, extending beyond situations spanned by current formalisms. Illustrative examples are provided.
We formulate and implement the phaseless auxiliary-field quantum Monte Carlo (AFQMC) method in the Hartree-Fock-Bogoliubov (HFB) manifold for systems with strong pairing correlations. Our formulation introduces a more flexible representation of HFB walkers with an explicit analytical expression for the normalization factor derived from the representation matrix with respect to the reference vacuum. We also extend our previously developed stochastic gauge formalism from the Slater determinant manifold to the HFB framework, providing additional flexibility for controlling stochastic fluctuations. Benchmark calculations for the Richardson model demonstrate the accuracy and numerical stability of the method.
Quantum many-body systems can be studied theoretically from first principles using microscopic models, but the computational cost of numerically exact calculations increases exponentially with the number of particles and the complexity of the interaction, limiting the systems that can be analysed. The Hartree-Fock-Bogoliubov (HFB) and quasiparticle random phase approximation (QRPA) methods, heavily used in nuclear physics, rely on mean-field approximations but scale more favourably with increasing system size and complexity. In this work we apply these methods to the problem of a two-dimensional harmonically trapped Fermi gas with attractive interactions, with the goal of investigating the validity of the approximations in the few-body limit. We implement the approximate methods in code and then compare them with exact calculations. We find that the HFB method can account for pairing correlations that arise due to the attractive interaction, predicting well the ground state energy even at high interaction strengths. Also, the excitation spectra predicted by the QRPA method qualitatively match the true spectra, reproducing the expected subset of excitations. Finally, we see that perturbative corrections can be used to improve the ground state energy estimate of the HFB.
The Hartree-Fock-Bogoliubov approximation is very useful for treating both long- and short-range correlations in finite quantum fermion systems, but it must be extended in order to describe detailed spectroscopic properties. One problem is the symmetry-breaking character of the HFB approximation. We present a general and systematic way to restore symmetries and to extend the configuration space using pfaffian formulas for the many-body matrix elements. The advantage of those formulas is that the sign of the matrix elements is unambiguously determined. It is also helpful to extend the space of configurations by constraining the HFB solutions in some way. A powerful method for finding these constrained solutions is the gradient method, based on the generalized Thouless transformation. The gradient method also preserves the number parity of the Bogoliubov transformation, which facilitates the application of the theory to systems with odd particle number.
We propose novel Quantum Monte Carlo (QMC) methods for interacting many-fermion systems by leveraging the stochastic gauge freedom, originally developed in Gaussian phase-space QMC, within the phaseless auxiliary-field QMC (AFQMC) framework. In particular, we reinterpret the conventional force bias in phaseless AFQMC as a drift gauge and explore Fermi gauges based on natural orbitals of a reduced one-body density matrix defined via a mixed estimator, yielding stochastic, time-dependent Hartree-Fock-like dynamics. We propose a symmetry-projection sampling scheme to enhance the sampling efficiency. As a proof of concept, we apply these gauge-augmented AFQMC methods to a simple shell-model Hamiltonian: the Lipkin-Meshkov-Glick model. Numerical results illustrate the potential of stochastic gauges to enhance accuracy and reduce fluctuations, underscoring the promise for advancing these new techniques toward more realistic shell-model applications.