Permutation invariant polynomial neural network approach to fitting potential energy surfaces. IV. Coupled diabatic potential energy matrices

Permutationally Invariant Potential Energy Surfaces

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Ab Initio Potential Energy Surfaces and Quantum Dynamics for Polyatomic Bimolecular Reactions

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Signatures of a Conical Intersection in Adiabatic Dissociation on the Ground Electronic State

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Neural network based coupled diabatic potential energy surfaces for reactive scattering

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Encoding of vinylidene isomerization in its anion photoelectron spectrum

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Single- and multireference electronic structure calculations for constructing potential energy surfaces

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Potential energy surfaces from high fidelity fitting ofab initiopoints: the permutation invariant polynomial - neural network approach

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A new approach for the development of diabatic potential energy surfaces: Hybrid block-diagonalization and diabatization by ansatz

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On the incorporation of the geometric phase in general single potential energy surface dynamics: A removable approximation to ab initio data

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Communication: Fitting potential energy surfaces with fundamental invariant neural network

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On the elimination of the electronic structure bottleneck in on the fly nonadiabatic dynamics for small to moderate sized (10-15 atom) molecules using fit diabatic representations based solely on ab initio electronic structure data: The photodissociation of phenol

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Perspective: Machine learning potentials for atomistic simulations

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Recent Progress in Surface Hopping: 2011–2015

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Nonadiabatic Tunneling in Photodissociation of Phenol

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Accurate nonadiabatic dynamics

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The Requisite Electronic Structure Theory To Describe Photoexcited Nonadiabatic Dynamics: Nonadiabatic Derivative Couplings and Diabatic Electronic Couplings

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From ab Initio Potential Energy Surfaces to State-Resolved Reactivities: X + H2O ↔ HX + OH [X = F, Cl, and O(3P)] Reactions

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Automated construction of potential energy surfaces

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Extremely short-lived reaction resonances in Cl + HD (v = 1) -> DCl + H due to chemical bond softening

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Neural network-based approaches for building high dimensional and quantum dynamics-friendly potential energy surfaces

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Permutation invariant polynomial neural network approach to fitting potential energy surfaces. III. Molecule-surface interactions

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Diabatization based on the dipole and quadrupole: The DQ method

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Full-Dimensional Quantum Dynamics of Vibrationally Mediated Photodissociation of NH3 and ND3 on Coupled Ab Initio Potential Energy Surfaces: Absorption Spectra and NH2(Ã2A1)/NH2(X̃2B1) Branching Ratios

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Full-Dimensional Quantum State-to-State Nonadiabatic Dynamics for Photodissociation of Ammonia in its A-Band

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Full-dimensional potentials and state couplings and multidimensional tunneling calculations for the photodissociation of phenol

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Permutation invariant polynomial neural network approach to fitting potential energy surfaces. II. Four-atom systems

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Permutation invariant polynomial neural network approach to fitting potential energy surfaces

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Interpolation of multi-sheeted multi-dimensional potential-energy surfaces via a linear optimization procedure

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Construction of Diabatic Hamiltonian Matrix from ab Initio Calculated Molecular Symmetry Adapted Nonadiabatic Coupling Terms and Nuclear Dynamics for the Excited States of Na3 Cluster

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Geometric Phase Effects in Dynamics Near Conical Intersections: Symmetry Breaking and Spatial Localization

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Computational determination of the à state absorption spectrum of NH3 and of ND3 using a new quasi-diabatic representation of the X̃ and à states and full six-dimensional quantum dynamics

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State-to-state photodissociation dynamics of triatomic molecules: H2O in the B band

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First principles determination of the NH2/ND2(Ã,X̃) branching ratios for photodissociation of NH3/ND3 via full-dimensional quantum dynamics based on a new quasi-diabatic representation of coupled ab initio potential energy surfaces

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Quasi-diabatic representations of adiabatic potential energy surfaces coupled by conical intersections including bond breaking: A more general construction procedure and an analysis of the diabatic representation

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A new method to generate spin-orbit coupled potential energy surfaces: Effective relativistic coupling by asymptotic representation

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On the representation of coupled adiabatic potential energy surfaces using quasi-diabatic Hamiltonians: A distributed origins expansion approach

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Nonadiabatic Quantum Chemistry—Past, Present, and Future

(2011) David R. Yarkony   CHEMICAL REVIEWS

Communication: State-to-state differential cross sections for H2O(B̃) photodissociation

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Atom-centered symmetry functions for constructing high-dimensional neural network potentials

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Toward eliminating the electronic structure bottleneck in nonadiabatic dynamics on the fly: An algorithm to fit nonlocal, quasidiabatic, coupled electronic state Hamiltonians based on ab initio electronic structure data

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Permutationally invariant potential energy surfaces in high dimensionality

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Permutationally Invariant Polynomial Basis for Molecular Energy Surface Fitting via Monomial Symmetrization

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Constructing diabatic states from adiabatic states: Extending generalized Mulliken–Hush to multiple charge centers with Boys localization

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HN2(2A‘) Electronic Manifold. II.AbInitioBased Double-Sheeted DMBE Potential Energy Surface via a Global Diabatization Angle

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