Optimization of quantum Monte Carlo wave functions by energy minimization

We study three wave function optimization methods based on energy minimization in a variational Monte Carlo framework: the Newton, linear and perturbative methods. In the Newton method, the parameter variations are calculated from the energy gradient and Hessian, using a reduced variance statistical estimator for the latter. In the linear method, the parameter variations are found by diagonalizing a non-symmetric estimator of the Hamiltonian matrix in the space spanned by the wave function and its derivatives with respect to the parameters, making use of a strong zero-variance principle. In the less computationally expensive perturbative method, the parameter variations are calculated by approximately solving the generalized eigenvalue equation of the linear method by a nonorthogonal perturbation theory. These general methods are illustrated here by the optimization of wave functions consisting of a Jastrow factor multiplied by an expansion in configuration state functions (CSFs) for the C$_2$ molecule, including both valence and core electrons in the calculation. The Newton and linear methods are very efficient for the optimization of the Jastrow, CSF and orbital parameters. The perturbative method is a good alternative for the optimization of just the CSF and orbital parameters. Although the optimization is performed at the variational Monte Carlo level, we observe for the C$_2$ molecule studied here, and for other systems we have studied, that as more parameters in the trial wave functions are optimized, the diffusion Monte Carlo total energy improves monotonically, implying that the nodal hypersurface also improves monotonically.Comment: 18 pages, 8 figures, final versio

Compact and Flexible Basis Functions for Quantum Monte Carlo Calculations

Molecular calculations in quantum Monte Carlo frequently employ a mixed basis consisting of contracted and primitive Gaussian functions. While standard basis sets of varying size and accuracy are available in the literature, we demonstrate that reoptimizing the primitive function exponents within quantum Monte Carlo yields more compact basis sets for a given accuracy. Particularly large gains are achieved for highly excited states. For calculations requiring non-diverging pseudopotentials, we introduce Gauss-Slater basis functions that behave as Gaussians at short distances and Slaters at long distances. These basis functions further improve the energy and fluctuations of the local energy for a given basis size. Gains achieved by exponent optimization and Gauss-Slater basis use are exemplified by calculations for the ground state of carbon, the lowest lying excited states of carbon with $^5S^o$, $^3P^o$, $^1D^o$, $^3F^o$ symmetries, carbon dimer, and naphthalene. Basis size reduction enables quantum Monte Carlo treatment of larger molecules at high accuracy.Comment: 8 Pages, 2 Figures, 9 Table

Zero-variance zero-bias quantum Monte Carlo estimators of the spherically and system-averaged pair density

We construct improved quantum Monte Carlo estimators for the spherically- and system-averaged electron pair density (i.e. the probability density of finding two electrons separated by a relative distance u), also known as the spherically-averaged electron position intracule density I(u), using the general zero-variance zero-bias principle for observables, introduced by Assaraf and Caffarel. The calculation of I(u) is made vastly more efficient by replacing the average of the local delta-function operator by the average of a smooth non-local operator that has several orders of magnitude smaller variance. These new estimators also reduce the systematic error (or bias) of the intracule density due to the approximate trial wave function. Used in combination with the optimization of an increasing number of parameters in trial Jastrow-Slater wave functions, they allow one to obtain well converged correlated intracule densities for atoms and molecules. These ideas can be applied to calculating any pair-correlation function in classical or quantum Monte Carlo calculations.Comment: 13 pages, 9 figures, published versio

Magnetic transitions in CaMn7O12 : a Raman observation of spin-phonon couplings

The quadruple Calcium manganite (CaMn7O12) is a multiferroic material that exhibits a giant magnetically-induced ferroelectric polarization which makes it very interesting for magnetoelectric applications. Here, we report the Raman spectroscopy study on this compound of both the phonon modes and the low energy excitations from 4 K to room temperature. A detailed study of the Raman active phonon excitations shows that three phonon modes evidence a spin-phonon coupling at TN2 = 50 K. In particular, we show that the mode at 432 cm-1 associated to Mn(B)O6 (B position of the perovskite) rotations around the [111] cubic diagonal is impacted by the magnetic transition at 50 K and its coupling to the new modulation of the Mn spin in the (a,b) plane. At low energies, two large low energy excitations are observed at 25 and 47 cm-1. The first one disappears at 50 K and the second one at 90 K. We have associated these excitations to electro-magneto-active modes

Approaching Chemical Accuracy with Quantum Monte Carlo

A quantum Monte Carlo study of the atomization energies for the G2 set of molecules is presented. Basis size dependence of diffusion Monte Carlo atomization energies is studied with a single determinant Slater-Jastrow trial wavefunction formed from Hartree-Fock orbitals. With the largest basis set, the mean absolute deviation from experimental atomization energies for the G2 set is 3.0 kcal/mol. Optimizing the orbitals within variational Monte Carlo improves the agreement between diffusion Monte Carlo and experiment, reducing the mean absolute deviation to 2.1 kcal/mol. Moving beyond a single determinant Slater-Jastrow trial wavefunction, diffusion Monte Carlo with a small complete active space Slater-Jastrow trial wavefunction results in near chemical accuracy. In this case, the mean absolute deviation from experimental atomization energies is 1.2 kcal/mol. It is shown from calculations on systems containing phosphorus that the accuracy can be further improved by employing a larger active space.Comment: 6 pages, 5 figure

Alleviation of the Fermion-sign problem by optimization of many-body wave functions

We present a simple, robust and highly efficient method for optimizing all parameters of many-body wave functions in quantum Monte Carlo calculations, applicable to continuum systems and lattice models. Based on a strong zero-variance principle, diagonalization of the Hamiltonian matrix in the space spanned by the wav e function and its derivatives determines the optimal parameters. It systematically reduces the fixed-node error, as demonstrated by the calculation of the binding energy of the small but challenging C$_2$ molecule to the experimental accuracy of 0.02 eV

Neurotrophic effects of growth/differentiation factor 5 in a neuronal cell line

The neurotrophin growth/differentiation factor 5 (GDF5) is studied as a potential therapeutic agent for Parkinson's disease as it is believed to play a role in the development and maintenance of the nigrostriatal system. Progress in understanding the effects of GDF5 on dopaminergic neurones has been hindered by the use of mixed cell populations derived from primary cultures or in vivo experiments, making it difficult to differentiate between direct and indirect effects of GDF5 treatment on neurones. In an attempt to establish an useful model to study the direct neuronal influence of GDF5, we have characterised the effects of GDF5 on a human neuronal cell line, SH-SY5Y. Our results show that GDF5 has the capability to promote neuronal but not dopaminergic differentiation. We also show that it promotes neuronal survival in vitro following a 6-hydroxydopamine insult. Our results show that application of GDF5 to SH-SY5Y cultures induces the SMAD pathway which could potentially be implicated in the intracellular transmission of GDF5 s neurotrophic effects. Overall, our study shows that the SH-SY5Y neuroblastoma cell line provides an excellent neuronal model to study the neurotrophic effects of GDF5