How do we establish the accuracy of a method ? Full CI quantum Monte Carlo

Tags: testing Accuracy ExcitedStates

One of the topics that is often discussed within the electronic structure community is that of accuracy: how accurate is a given method. While DFT is efficient and widely applicable, it has many known limitations, and rarely comes close to what is called chemical accuracy (1 kcal/mol or around 40meV). Recent years have seen various efforts to improve the accuracy of DFT (I have blogged about this before: here, here and here for instance), but while these additions have had some success, they are necessarily limited, and there is no systematic way to improve accuracy in DFT. There is, therefore, a need for well-defined benchmarks against which DFT and other methods can be tested. Experiment often forms one important touchstone, but we need to be confident that the calculation we perform corresponds to the experimental set-up (often a difficult problem). In this blog I will discuss a recently developed approach, full CI quantum Monte Carlo[1], that allows convergence to the exact, many-body wavefunction result (for a given basis set). This gives both an important way to test other methods, and a powerful method for studying problems that need this level of accuracy.

Going beyond standard DFT accuracy normally involves adding extra terms (such as a fraction of exact exchange in hybrid functionals), introducing new functionality (for instance via TDDFT) or using DFT wavefunctions as the input to perturbative expansions (such as GW). One advantage DFT holds over these other methods is in the size of system that can be modelled: it generally scales with the cube of the number of atoms, and can address systems with hundreds or thousands of atoms (with linear scaling DFT we can go to millions of atoms[2] or beyond). More accurate methods generally scale more strongly with atom number and are limited in the size of the system that they can address.

Quantum chemistry techniques differ fundamentally from DFT-based techniques in that they work with approximations to the many-body wavefunction rather than the charge density[3]. A systematic approach to improving accuracy can be defined within this formalism (which I should note is extremely sophisticated and requires more space than I can give here). The starting point is Hartree-Fock theory, which approximates the many-body wavefunction with a Slater determinant of molecular orbitals built from some basis set (almost inevitably Gaussian functions these days). The simplest improvements to Hartree-Fock invoke standard quantum mechanical perturbation theory (such as the MP2 method), but while these methods are powerful and reasonably accurate, they are limited. The configuration interaction (CI) method goes beyond the single determinant of Hartree-Fock, and adds determinants which include all possible excitations of one, two, three (or more) electrons. The full CI solution is prohibitively expensive beyond about ten electrons, though this limit also depends on the completeness of the basis set used.

The quantum Monte Carlo (QMC) family of methods provide an alternative, very accurate approach, and seek to calculate the ground state many-body wavefunction using a stochastic approach (see [4] for a recent overview of these methods, or a review like [5] for more details). However, I want to write about a recent development: full configuration interaction QMC, or FCI-QMC[1].

FCI-QMC works within the space of Slater determinants which are possible, given the system and the basis set chosen. Rather than adjust the coefficients of the determinants, it evolves a stochastic set of walkers, with different populations on different determinants, through the operations of spawning (creating a new walker on a new determinant), cloning (an existing walker on the same determinant) and annihilation (removing pairs of walker with opposite signs on the same determinant—this is needed for proper fermionic behaviour). While the number of walkers required is rather large, the computational and memory is very small for each, and it can be shown that this procedure converges to the exact, full configuration interaction result. The only error left is that of the basis set (this does not affect other QMC methods, which work in real space). There are well-established methods for extrapolating to a complete basis set limit.

In the paper which prompted me to write this post, the FCI-QMC method was applied to various solid state problems[6]. The paper is remarkable for several reasons, not the least of which is managing to get a purely computational paper, which largely presents benchmark calculations, into Nature.

The authors point out that full CI calculations form an important reference point for other quantum chemistry methods in molecular calculations, as they give the exact result for a given basis. However, these results are not available in the solid state. Recent work has seen a number of developments that allow quantum chemistry approaches to be applied to solid state problems (whether using traditional, gaussian basis sets, or plane wave basis sets).

A solid-state implementation of FCI-QMC is not trivial: the method scales essentially exponentially with k points, though this can be mitigated somewhat by ensuring that sampling between k points obeys momentum conservation. For small cells (LiH), even with modest k point sampling, there are approximately \(10^{30}\) determinants to sample. They demonstrate converged calculations on a wide variety of materials, and show that the most accurate of the widely used approximations (CCSD(T), or coupled cluster with singles, doubles and some triples) gives excellent results compared to the exact result.

The method is not cheap: for diamond carbon, with four k points in each direction, the calculation took 25,000 CPU hours, with a relatively modest basis set. However, it does allow us to test the well-established hierarchy of quantum chemical methods in solids, and demonstrate that the best of these go beyond chemical accuracy in solids (even for strongly correlated materials).

Why could this comparison not be made with existing QMC methods, such as diffusion Monte Carlo ? The difference in basis sets is the key issue: DMC works in real space, and the quantum chemistry calculations would have had to be converged to the complete basis set limit to enable comparisons. FCI-QMC works in the same space as the quantum chemistry calculations, and thus gives the exact result for any given choice of system and basis set.

There have been a number of other developments in FCI-QMC, many related to improving the efficiency of the method, but also recently showing that it is possible to sample excited states efficiently[7]. As with all QMC methods, the FCI-QMC method parallelises with very high efficiency (in all of these methods a given walker can operate almost independently), but it is not possible at the moment to evaluate forces accurately. They have a very specific domain of applicability, but within that domain, they are quite possibly the most accurate methods available.

[1] J. Chem. Phys. 131 054106 (2009) DOI:10.1063/1.3193710

[2] J. Phys.: Condens. Matter 22, 074207 (2010) DOI:10.1088/0953-8984/22/7/074207

[3] Indeed, these different approaches are often referred to, respectively, as wavefunction methods and density methods.

[4] J. Chem. Phys. 143, 164105 (2015) DOI:10.1063/1.4933112

[5] Rev. Mod. Phys. 143, 164105 (2015) DOI:10.1063/1.4933112

[6] Nature 493, 365 (2013) DOI:10.1038/nature11770

[7] J. Chem. Phys. 143 134117 (2015) DOI:10.1063/1.4932595

This entry was posted in accuracy on 2015/11/16.