Jeremy McMinis

Hybrid algorithms in quantum Monte Carlo

With advances in algorithms and growing computing powers, quantum Monte Carlo (QMC) methods have become a leading contender for high accuracy calculations for the electronic structure of realistic systems. The performance gain on recent HPC systems is largely driven by increasing parallelism: the number of compute cores of a SMP and the number of SMPs have been going up, as the Top500 list attests. However, the available memory as well as the communication and memory bandwidth per element has not kept pace with the increasing parallelism. This severely limits the applicability of QMC and the problem size it can handle. OpenMP/MPI hybrid programming provides applications with simple but effective solutions to overcome efficiency and scalability bottlenecks on large-scale clusters based on multi/many-core SMPs. We discuss the design and implementation of hybrid methods in QMCPACK and analyze its performance on current HPC platforms characterized by various memory and communication hierarchies.

Multideterminant Wave Functions in Quantum Monte Carlo

Quantum Monte Carlo (QMC) methods have received considerable attention over past decades due to their great promise for providing a direct solution to the many-body Schrodinger equation in electronic systems. Thanks to their low scaling with the number of particles, QMC methods present a compelling competitive alternative for the accurate study of large molecular systems and solid state calculations. In spite of such promise, the method has not permeated the quantum chemistry community broadly, mainly because of the fixed-node error, which can be large and whose control is difficult. In this Perspective, we present a systematic application of large scale multideterminant expansions in QMC and report on its impressive performance with first row dimers and the 55 molecules of the G1 test set. We demonstrate the potential of this strategy for systematically reducing the fixed-node error in the wave function and for achieving chemical accuracy in energy predictions. When compared to traditional quantum chemistry methods like MP2, CCSD(T), and various DFT approximations, the QMC results show a marked improvement over all of them. In fact, only the explicitly correlated CCSD(T) method with a large basis set produces more accurate results. Further developments in trial wave functions and algorithmic improvements appear promising for rendering QMC as the benchmark standard in large electronic systems.

Computing the energy of a water molecule using multideterminants: A simple, efficient algorithm

Quantum Monte Carlo (QMC) methods such as variational Monte Carlo and fixed node diffusion Monte Carlo depend heavily on the quality of the trial wave function. Although Slater-Jastrow wave functions are the most commonly used variational ansatz in electronic structure, more sophisticated wave functions are critical to ascertaining new physics. One such wave function is the multi-Slater-Jastrow wave function which consists of a Jastrow function multiplied by the sum of Slater determinants. In this paper we describe a method for working with these wave functions in QMC codes that is easy to implement, efficient both in computational speed as well as memory, and easily parallelized. The computational cost scales quadratically with particle number making this scaling no worse than the single determinant case and linear with the total number of excitations. Additionally, we implement this method and use it to compute the ground state energy of a water molecule.

Quantum Monte Carlo benchmark of exchange-correlation functionals for bulk water

The accurate description of the thermodynamic and dynamical properties of liquid water from first-principles is a very important challenge to the theoretical community. This represents not only a critical test of the predictive capabilities of first-principles methods, but it will also shed light into the microscopic properties of such an important substance. Density Functional Theory, the main workhorse in the field of first-principles methods, has been so far unable to properly describe water and its unusual properties in the liquid state. With the recent introduction of exact exchange and an improved description of dispersion interaction, the possibility of an accurate description of the liquid is finally within reach. Unfortunately, there is still no way to systematically improve exchange-correlation functionals, and the number of available functionals is very large. In this article we use highly accurate quantum Monte Carlo calculations to benchmark a selection of exchange-correlation functionals typically used in Density Functional Theory simulations of bulk water. This allows us to test the predictive capabilities of these functionals in water, giving us a way to choose optimal functionals for first-principles simulations. We compare and contrast the importance of different features of functionals, including the hybrid component, the vdW component, and their importance within different aspects of the PES. In addition, in order to correct the inaccuracies in the description of short-range interactions in the liquid, we test a recently introduced scheme that combines Density Functional Theory with Coupled Cluster calculations through a Many-Body expansion of the energy.

Momentum Distribution and Renormalization Factor in Sodium and the Electron Gas

We present experimental and theoretical results on the momentum distribution and the quasiparticle renormalization factor in sodium. From an x-ray Compton-profile measurement of the valence-electron-momentum density, we derive its discontinuity at the Fermi wave vector. This yields an accurate measure of the renormalization factor that we compare with quantum Monte Carlo and G0W0 calculations performed both on crystalline sodium and on the homogeneous electron gas.

Benchmarking exchange-correlation functionals for hydrogen at high pressures using quantum Monte Carlo

Department of Physical and Chemical Sciences,University of L’Aquila and CNISM UdR L’Aquila, Via Vetoio, I-67010 L’Aquila, Italy(Dated: January 30, 2014)The ab-initio phase diagram of dense hydrogen is very sensitive to errors in the treatment ofelectronic correlation. Recently, it has been shown that the choice of the density functional hasa large e ect on the predicted location of both the liquid-liquid phase transition and the solidinsulator-to-metal transition in dense hydrogen. To identify the most accurate functional for densehydrogen applications, we systematically benchmark some of the most commonly used functionalsusing Quantum Monte Carlo. By considering several measures of functional accuracy, we concludethat the van der Waals and hybrid functionals signi cantly out perform LDA and PBE. We supportthese conclusions by analyzing the impact of functional choice on structural optimization in themolecular solid, and on the location of the liquid-liquid phase transition.

Momentum distribution of the homogeneous electron gas.

We calculate the off-diagonal density matrix of the homogeneous electron gas at zero temperature using unbiased reptation Monte Carlo calculations for various densities and extrapolate the momentum distribution and the kinetic and potential energies to the thermodynamic limit. Our results on the renormalization factor allow us to validate approximate G0W0 calculations concerning quasiparticle properties over a broad density region (1≤r(s)≲10) and show that, near the Fermi surface, vertex corrections and self-consistency aspects almost cancel each other out.

QMCPACK: An open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

QMCPACK is an open source quantum Monte Carlo package for ab initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wavefunctions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary-field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit and graphical processing unit systems. We detail the programs capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://qmcpack.org.

Oscillating terms in the Renyi entropy of Fermi gases and liquids

In this work we compute subleading oscillating terms in the Renyi entropy of Fermi gases and Fermi liquids corresponding to

The Transition to the Metallic State in Low Density Hydrogen

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