New Permutationally Invariant Polynomial Potential Energy Surfaces for H

Saikiran Kotaru, Chen Qu, Paul L Houston, Qi Yu, Riccardo Conte, Apurba Nandi, Joel M Bowman

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Article in The journal of physical chemistry. A, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Saikiran KotaruDepartment of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States.ORCID 0000-0003-0778-404X

Chen QuIndependent Researcher, Toronto, Ontario M9B0E3, Canada.ORCID 0000-0001-8889-4851

Paul L HoustonDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.ORCID 0000-0003-2566-9539

Qi YuDepartment of Chemistry, Fudan University, Shanghai200438, P. R. China.

Riccardo ConteDipartimento di Chimica, Università Degli Studi di Milano, via Golgi 19, 20133 Milano, Italy.ORCID 0000-0003-3026-3875

Apurba NandiDepartment of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg City, Luxembourg.ORCID 0000-0002-6191-5584

Joel M BowmanDepartment of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States.ORCID 0000-0001-9692-2672

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the central importance of the protonated water dimer to the study of the hydrated proton, we report new fits to the previous CCSD(T) data set of Huang, Braams, and Bowman (HBB) that are more precise and, unlike HBB, provide fast gradients. The new fits, like the HBB one, are based on linear regression with permutationally invariant polynomials (PIPs). The fast gradients are provided via reverse differentiation. They cost roughly just three times the cost for an energy call and are roughly 20 times faster than the HBB numerical gradients. The two new PESs are fits to the original HBB data sets up to roughly 60,000 and to 110,000 cm

Identifiers

PMID41499588

DOI10.1021/acs.jpca.5c07198

PMCPMC12833855

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