Exploring New Algorithms for Molecular Vibrational Spectroscopy Using Physics-Informed Program Synthesis
Inductive program synthesis (PS) has recently begun to emerge as a useful new approach to automatically generate algorithms in quantum chemistry, as demonstrated in recent applications to the vibrational Schrödinger equation for simple model systems with one or two degrees-of-freedom. Here, we repo...
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          | Published in | Journal of chemical theory and computation Vol. 21; no. 1; pp. 307 - 320 | 
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| Main Authors | , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        United States
          American Chemical Society
    
        14.01.2025
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 1549-9618 1549-9626 1549-9626  | 
| DOI | 10.1021/acs.jctc.4c01312 | 
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| Summary: | Inductive program synthesis (PS) has recently begun to emerge as a useful new approach to automatically generate algorithms in quantum chemistry, as demonstrated in recent applications to the vibrational Schrödinger equation for simple model systems with one or two degrees-of-freedom. Here, we report a new physics-informed approach to inductive PS that is more conducive to the generation of discrete variable representation 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 synthesized algorithmic predictions with. Algorithms with a tridiagonal matrix structure are generated via a variational-based stochastic optimization procedure. Crucially, through an extensive testing procedure, we demonstrate that variationally synthesized algorithms perform just as well as those generated using a target function. Assuming a direct product representation of normal coordinates, these algorithms are applied to three triatomic 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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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23  | 
| ISSN: | 1549-9618 1549-9626 1549-9626  | 
| DOI: | 10.1021/acs.jctc.4c01312 |