Sensitivity of semiclassical vibrational spectroscopy to potential energy surface accuracy: A test on formaldehyde

Conte, Riccardo; Botti, Giacomo; Ceotto, Michele

doi:10.1016/j.vibspec.2019.103015

Cited by 9 publications

(9 citation statements)

References 57 publications

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“…For this reason ab initio SC calculations are basically restricted to the DFT level of theory, which can limit the accuracy of results in certain instances but provides often quite satisfactorily estimates. 32 …”

Section: Introductionmentioning

confidence: 99%

Semiclassical Vibrational Spectroscopy of Biological Molecules Using Force Fields

Gabas

Conte

Ceotto

2020

J. Chem. Theory Comput.

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Semiclassical spectroscopy is a practical way to get an accurately approximate quantum description of spectral features starting from ab initio molecular dynamics simulations. The computational bottleneck for the method is represented by the cost of ab initio potential, gradient, and Hessian matrix estimates. This drawback is particularly severe for biological systems due to their unique complexity and large dimensionality. The main goal of this manuscript is to demonstrate that quantum dynamics and spectroscopy, at the level of semiclassical approximation, are doable even for sizable biological systems. To this end, we investigate the possibility of performing semiclassical spectroscopy simulations when ab initio calculations are replaced by computationally cheaper force field evaluations. Both polarizable (AMOEBABIO18) and nonpolarizable (AMBER14SB) force fields are tested. Calculations of some particular vibrational frequencies of four nucleosides, i.e., uridine, thymidine, deoxyguanosine, and adenosine, show that ab initio simulations are accurate and widely applicable. Conversely, simulations based on AMBER14SB are limited to harmonic approximations, but those relying on AMOEBABIO18 yield acceptable semiclassical values if the investigated conformation has been included in the force field parametrization. The main conclusion is that AMOEBABIO18 may provide a viable route to assist semiclassical spectroscopy in the study of large biological molecules for which an ab initio approach is not computationally affordable.

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Section: Introductionmentioning

confidence: 99%

Semiclassical Vibrational Spectroscopy of Biological Molecules Using Force Fields

Gabas

Conte

Ceotto

2020

J. Chem. Theory Comput.

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“…using an ab initio molecular dynamics approach. 93 We take the water molecule as a benchmark for checking the accuracy of our nuclear densities and get familiar with this quantum mechanical nuclear representation. We observe the quantum harmonic description to be quite accurate in this case and similar to the semiclassical and exact anharmonic ones, by reproducing all main quantum features.…”

Section: Discussionmentioning

confidence: 99%

Representing Molecular Ground and Excited Vibrational Eigenstates with Nuclear Densities obtained from Semiclassical Initial Value Representation Molecular Dynamics

Aieta,

Bertaina,

Micciarelli

et al. 2020

Preprint

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We present in detail and validate an effective Monte Carlo approach for the calculation of the nuclear vibrational densities via integration of molecular eigenfunctions that we have preliminary employed to calculate the densities of the ground and the excited OH stretch vibrational states in protonated glycine molecule [C. Aieta et. al. Nat Commun 11, 4348 (2020)]. Here, we first validate and discuss in detail the features of the method on a benchmark water molecule. Then, we apply it to calculate on-the-fly the ab initio anharmonic nuclear densities in correspondence of the fundamental transitions of NH and CH stretches in protonated glycine. We show how we can gain both qualitative and quantitative physical insight by inspection of different one-nucleus densities and assign a character to spectroscopic absorption peaks using the expansion of vibrational states in terms of harmonic basis functions. The visualization of the nuclear vibrations in a purely quantum picture allows us to observe and quantify the effects of anharmonicity on the molecular structure, and to exploit the effect of IR excitations on specific bonds or functional groups, beyond the harmonic approximation. We also calculate the quantum probability distribution of bond-lengths, angles and dihedrals of the molecule. Notably, we observe how in the case of one type of fundamental NH stretching the typical harmonic nodal pattern is absent in the anharmonic distribution.

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“…Conversely, only at a lower degree the inaccuracy can be related to the semiclassical approximation or the quality of the potential energy surface fitting, as previously shown on other systems. 81 Unfortunately, a DC-SCIVR simulation at MP2/aug-cc-pVTZ level of ab initio theory is out of reach at time of writing due to its computational burden.…”

Section: B the Ch 4 Moleculementioning

confidence: 99%

Machine Learning for Vibrational Spectroscopy via Divide-and-Conquer Semiclassical Initial Value Representation Molecular Dynamics with Application to N-Methylacetamide

Gandolfi¹,

Rognoni²,

Aieta³

et al. 2021

Preprint

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A machine learning algorithm for partitioning the nuclear vibrational space into subspaces is introduced. The subdivision criterion is based on Liouville's theorem, i.e. best preservation of the unitary of the reduced dimensionality Jacobian determinant within each subspace along a probe full-dimensional classical trajectory. The algorithm is based on the idea of evolutionary selection and it is implemented through a probability graph representation of the vibrational space partitioning. We interface this customized version of genetic algorithms with our divide-and-conquer semiclassical initial value representation method for calculation of molecular power spectra. First, we benchmark the algorithm by calculating the vibrational power spectra of two model systems, for which the exact subspace division is known. Then, we apply it to the calculation of the power spectrum of methane. Exact calculations and full-dimensional semiclassical spectra of this small molecule are available and provide an additional test of the accuracy of the new approach. Finally, the algorithm is applied to the divide-and-conquer semiclassical calculation of the power spectrum of 12-atom trans-N-Methylacetamide.

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Sensitivity of semiclassical vibrational spectroscopy to potential energy surface accuracy: A test on formaldehyde

Cited by 9 publications

References 57 publications

Semiclassical Vibrational Spectroscopy of Biological Molecules Using Force Fields

Semiclassical Vibrational Spectroscopy of Biological Molecules Using Force Fields

Representing Molecular Ground and Excited Vibrational Eigenstates with Nuclear Densities obtained from Semiclassical Initial Value Representation Molecular Dynamics

Machine Learning for Vibrational Spectroscopy via Divide-and-Conquer Semiclassical Initial Value Representation Molecular Dynamics with Application to N-Methylacetamide

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