4.7 Article

Permutationally Invariant Polynomial Expansions with Unrestricted Complexity

Journal

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 17, Issue 9, Pages 5440-5455

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.1c00352

Keywords

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Funding

  1. U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences [DE-AC02-06CH11357]
  2. Argonne-Sandia Consortium on High-Pressure Combustion Chemistry [ANL FWP 59044]
  3. Exascale Computing Project (ECP) [17-SC-20-SC]

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A general strategy for constructing and validating permutationally invariant polynomial expansions for chemical systems is presented, demonstrating its application to gas-phase dynamics and kinetics. The strategy enforces permutational invariance in PIP expansions with millions of terms and permutationally distinct atom types, showing systematic convergence in training data quantity and expansion order. The quality of the PIP expansions is demonstrated through predicting errors in dynamics for both reactive and nonreactive applications.
A general strategy is presented for constructing and validating permutationally invariant polynomial (PIP) expansions for chemical systems of any stoichiometry. Demonstrations are made for three categories of gas-phase dynamics and kinetics: collisional energy-transfer trajectories for predicting pressure-dependent kinetics, three-body collisions for describing transient van der Waals adducts relevant to atmospheric chemistry, and nonthermal reactivity via quasiclassical trajectories. In total, 30 systems are considered with up to 15 atoms and 39 degrees of freedom. Permutational invariance is enforced in PIP expansions with as many as 13 million terms and 13 permutationally distinct atom types by taking advantage of petascale computational resources. The quality of the PIP expansions is demonstrated through the systematic convergence of in-sample and out-of-sample errors with respect to both the number of training data and the order of the expansion, and these errors are shown to predict errors in the dynamics for both reactive and nonreactive applications. The parallelized code distributed as part of this work enables the automation of PIP generation for complex systems with multiple channels and flexible user-defined symmetry constraints and for automatically removing unphysical unconnected terms from the basis set expansions, all of which are required for simulating complex reactive systems.

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