Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 33 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 24 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 74 tok/s Pro
Kimi K2 188 tok/s Pro
GPT OSS 120B 362 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

Optimized structure and vibrational properties by error affected potential energy surfaces (1306.4212v1)

Published 18 Jun 2013 in cond-mat.str-el, physics.chem-ph, physics.comp-ph, and quant-ph

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 the statistical uncertainty of the vibrational parameters by one order of magnitude. Preliminary results based on Variational Monte Carlo calculations on the water molecule demonstrate the possibility to evaluate geometrical parameters, harmonic and anharmonic coefficients at this level of theory with an affordable computational cost and a small stochastic uncertainty (<0.07% for geometries and <0.7% for vibrational properties).

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube