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Table · dataset · 2025

Data for Exploring new algorithms for molecular vibrational spectroscopy using physics-informed program synthesis

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Inductive program synthesis (PS) has recently begun to emerge as a useful new approach to automatically generating algorithms in quantum chemistry, as demonstrated in recent applications to the vibrational Schrodinger equation for simple model systems with one or two degrees-of-freedom.

Description

Here, we report a new physics-informed approach to inductive PS that is more conducive to generating discrete variable representation (DVR) algorithms for real molecular systems.

The new framework ensures separability of the kinetic and potential operators and does not require an exact solution to compare synthesised algorithmic predictions with. Algorithms with a tri-diagonal matrix structure are generated via a variational based stochastic optimisation procedure. Crucially, through an extensive testing procedure we demonstrate that variationally synthesised algorithms perform just as well as those generated using a target function.

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Assuming a direct product representation of normal coordinates, these algorithms are applied to three tri-atomic molecules. In total, we identify a set of seven PS algorithms that accurately reproduce the vibrational spectra of H2O, NO2, and SO2, as predicted by Colbert-Miller and sine-DVR algorithms.

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Computational chemistry 80%
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