Highly Accurate Electronic Structure of Metallic Solids from Coupled-Cluster Theory with Nonperturbative Triple Excitations.

Coupled-cluster theory with single, double, and perturbative triple excitations (CCSD(T))-often considered the "gold standard" of main-group quantum chemistry-is inapplicable to three-dimensional metals due to an infrared divergence, preventing its application to many important problems in materials science. We study the full, nonperturbative inclusion of triple excitations (CCSDT) and propose a new, iterative method, which we call ring-CCSDT, that resums the essential triple excitations with the same N^{7} run-time scaling as CCSD(T). CCSDT and ring-CCSDT are used to calculate the correlation energy of the uniform electron gas at metallic densities and the structural properties of solid lithium. Inclusion of connected triple excitations is shown to be essential to achieving high accuracy. We also investigate semiempirical CC methods based on spin-component scaling and the distinguishable cluster approximation and find that they enhance the accuracy of their parent ab initio methods.

Accurate Quantum Chemical Reaction Energies for Lithium-Mediated Electrolyte Decomposition and Evaluation of Density Functional Approximations.

An important concern related to the performance of Li-ion batteries is the formation of a solid electrolyte interphase on the surface of the anode. This film is formed from the decomposition of electrolytes and can have important effects on the stability and performance. Here, we evaluate the decomposition pathway of ethylene carbonate and related organic electrolyte molecules using a series of density functional approximations and correlated wave function (WF) methods, including the coupled-cluster theory with single, double, and perturbative triple excitations [CCSD(T)] and auxiliary-field quantum Monte Carlo (AFQMC). We find that the transition state barrier associated with ring opening varies widely across different functionals, ranging from 3.01 to 17.15 kcal/mol, which can be compared to the value of 12.84 kcal/mol predicted by CCSD(T). This large variation underscores the importance of benchmarking against accurate WF methods. A performance comparison of all of the density functionals used in this study reveals that the M06-2X-D3 (a meta-hybrid GGA), CAM-B3LYP-D3 (a range-separated hybrid), and B2GP-PLYP-D3 (a double hybrid) perform the best, with average errors of about 1.50-1.60 kcal/mol compared to CCSD(T). We also compared the performance of the WF methods that are more scalable than CCSD(T), finding that DLPNO-CCSD(T) and phaseless AFQMC with a DFT trial wave function exhibit average errors of 1.38 and 1.74 kcal/mol, respectively.

A study of the dense uniform electron gas with high orders of coupled cluster.

We investigate the accuracies of different coupled cluster levels in a finite model solid, the 14 electron spin-non-polarised uniform electron gas. For densities between rs = 0.5 a0 and rs = 5 a0, we calculate ground state correlation energies with stochastic coupled cluster ranging from coupled cluster singles and doubles (CCSD) to coupled cluster including all excitations up to quintuples (CCSDTQ5). We find the need to add triple excitations for an accuracy of 0.01 eV/electron beyond rs = 0.5 a0. Quadruple excitations start being significant past rs = 3 a0. At rs = 5 a0, CCSD gives a correlation energy with a 16% error and coupled cluster singles doubles and triples is in error by 2% compared to the CCSDTQ5 result. CCSDTQ5 gives an energy in agreement with full configuration interaction quantum Monte Carlo results.

Ground-State Properties of Metallic Solids from Ab Initio Coupled-Cluster Theory.

Metallic solids are an enormously important class of materials, but they are a challenging target for accurate wave function-based electronic structure theories and have not been studied in great detail by such methods. Here, we use coupled-cluster theory with single and double excitations (CCSD) to study the structure of solid lithium and aluminum using optimized Gaussian basis sets. We calculate the equilibrium lattice constant, bulk modulus, and cohesive energy and compare them to experimental values, finding accuracy comparable to common density functionals. Because the quantum chemical "gold standard" CCSD(T) (CCSD with perturbative triple excitations) is inapplicable to metals in the thermodynamic limit, we test two approximate improvements to CCSD, which are found to improve the results.

Making the most of data: Quantum Monte Carlo postanalysis revisited.

In quantum Monte Carlo (QMC) methods, energy estimators are calculated as (functions of) statistical averages of quantities sampled during a calculation. Associated statistical errors of these averages are often estimated. This error estimation is not straightforward and there are several choices of the error estimation methods. We evaluate the performance of three methods (the Straatsma method, an autoregressive model, and a blocking analysis based on von Neumann's ratio test for randomness) for the energy time series given by three QMC methods [diffusion Monte Carlo, full configuration interaction Quantum Monte Carlo (FCIQMC), and coupled cluster Monte Carlo (CCMC)]. From these analyses, we describe a hybrid analysis method which provides reliable error estimates for a series of various lengths of FCIQMC and CCMC's time series. Equally important is the estimation of the appropriate start point of the equilibrated phase. We establish that a simple mean squared error rule method as described by White [K. P. White, Jr., Simulation 69(6), 323 (1997)10.1177/003754979706900601] can provide reasonable estimations.

Accelerating Convergence in Fock Space Quantum Monte Carlo Methods.

The convergence of full configuration interaction quantum Monte Carlo (FCIQMC) is accelerated using a quasi-Newton propagation (QN) which can also be applied to coupled cluster Monte Carlo (CCMC). The computational scaling of this optimized propagation is [Formula: see text], keeping the additional computational cost to a bare minimum. Its effects are investigated deterministically and stochastically on a model system, the uniform electron gas, with Hilbert space size up to 1040, and shown to accelerate convergence of the instantaneous projected energy by over an order of magnitude in the FCIQMC test case. Its capabilities are then demonstrated with FCIQMC on an archetypical quantum chemistry problem, the chromium dimer, in an all-electron basis set with Hilbert space size of about 1022 yielding highly accurate FCI energies.

Exciting Determinants in Quantum Monte Carlo: Loading the Dice with Fast, Low-Memory Weights.

High-quality excitation generators are crucial to the effectiveness of coupled cluster Monte Carlo (CCMC) and full configuration interaction Quantum Monte Carlo (FCIQMC) calculations. The heat bath sampling of Holmes et al. [Holmes, A. A.; Changlani, H. J.; Umrigar, C. J. J. Chem. Theory Comput. 2016, 12, 1561-1571.] dramatically increases the efficiency of the spawn step of such algorithms but requires memory storage scaling quartically with system size which can be prohibitive for large systems. Alternatively, Alavi et al. [Smart, S. D.; Booth, G. H.; Alavi, A. Unpublished results.] approximated these weights with weights based on Cauchy-Schwarz-like inequalities calculated on-the-fly. While reducing the memory cost, this algorithm scales linearly in system size computationally. We combine both of these ideas with the single-reference nature of many systems studied and introduce a spawn-sampling algorithm that has low memory requirements (quadratic in basis set size) compared to the heat bath algorithm and only scales either independently of system size (CCMC) or linearly in the number of electrons (FCIQMC) that works especially well on localized orbitals. Tests on small water chains with localized orbitals with CCMC and with an initiator point sample in FCIQMC indicate that it can be equally efficient as the other excitation generators. As the system gets larger, calculations with our new algorithm converge faster than the on-the-fly weight algorithm while having a much more favorable memory scaling than the heat bath algorithm.

The HANDE-QMC Project: Open-Source Stochastic Quantum Chemistry from the Ground State Up.

Building on the success of Quantum Monte Carlo techniques such as diffusion Monte Carlo, alternative stochastic approaches to solve electronic structure problems have emerged over the past decade. The full configuration interaction quantum Monte Carlo (FCIQMC) method allows one to systematically approach the exact solution of such problems, for cases where very high accuracy is desired. The introduction of FCIQMC has subsequently led to the development of coupled cluster Monte Carlo (CCMC) and density matrix quantum Monte Carlo (DMQMC), allowing stochastic sampling of the coupled cluster wave function and the exact thermal density matrix, respectively. In this Article, we describe the HANDE-QMC code, an open-source implementation of FCIQMC, CCMC and DMQMC, including initiator and semistochastic adaptations. We describe our code and demonstrate its use on three example systems; a molecule (nitric oxide), a model solid (the uniform electron gas), and a real solid (diamond). An illustrative tutorial is also included.