Optimized Structure and Vibrational Properties by ... - ACS Publications

Sep 19, 2012 - Dipartimento di Matematica Pura ed Applicata, Università degli Studi dell′Aquila, Via Vetoio 2, 67100 L′Aquila, Italy. §. Diparti...
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Optimized Structure and Vibrational Properties by Error Affected Potential Energy Surfaces Andrea Zen,† Delyan Zhelyazov,‡,∥ and Leonardo Guidoni*,§ †

Dipartimento di Fisica, La SapienzaUniversità di Roma, P.le Aldo Moro 2, 00185 Roma, Italy Dipartimento di Matematica Pura ed Applicata, Università degli Studi dell′Aquila, Via Vetoio 2, 67100 L′Aquila, Italy § Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell′Aquila, Via Vetoio 2, 67100 L′Aquila, Italy ‡

ABSTRACT: The precise theoretical determination of the geometrical parameters of molecules at the minima of their potential energy surface and of the corresponding vibrational properties are of fundamental importance for the interpretation of vibrational spectroscopy experiments. Quantum Monte Carlo techniques are correlated electronic structure methods promising for large molecules, which are intrinsically affected by stochastic errors on both energy and force calculations, making the mentioned calculations more challenging with respect to other more traditional quantum chemistry tools. To circumvent this drawback in the present work, we formulate the general problem of evaluating the molecular equilibrium structures, the harmonic frequencies, and the anharmonic coefficients of an error affected potential energy surface. The proposed approach, based on a multidimensional fitting procedure, is illustrated together with a critical evaluation of systematic and statistical errors. We observe that the use of forces instead of energies in the fitting procedure reduces the statistical uncertainty of the vibrational parameters by 1 order of magnitude. Preliminary results based on variational Monte Carlo calculations on the water molecule demonstrate the possibility to evaluate geometrical parameters and harmonic and anharmonic coefficients at this level of theory with an affordable computational cost and a small stochastic uncertainty (