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T Carrington
T Carrington
Verified email at queensu.ca
Title
Cited by
Cited by
Year
Discrete‐variable representations and their utilization
JC Light, T Carrington Jr
Advances in Chemical Physics 114, 263-310, 2000
10082000
Variational quantum approaches for computing vibrational energies of polyatomic molecules
JM Bowman, T Carrington, HD Meyer
Molecular Physics 106 (16-18), 2145-2182, 2008
4742008
Encyclopedia of computational chemistry
PR Schleyer
(No Title), 1998
4671998
A general discrete variable method to calculate vibrational energy levels of three‐and four‐atom molecules
MJ Bramley, T Carrington Jr
The Journal of chemical physics 99 (11), 8519-8541, 1993
4371993
The discrete variable representation of a triatomic Hamiltonian in bond length–bond angle coordinates
H Wei, T Carrington
The Journal of chemical physics 97 (5), 3029-3037, 1992
3921992
Reaction surface description of intramolecular hydrogen atom transfer in malonaldehyde
T Carrington Jr, WH Miller
The Journal of chemical physics 84 (8), 4364-4370, 1986
3101986
Fermi resonances and local modes in water, hydrogen sulfide, and hydrogen selenide
L Halonen, T Carrington Jr
The Journal of chemical physics 88 (7), 4171-4185, 1988
2761988
A random-sampling high dimensional model representation neural network for building potential energy surfaces
S Manzhos, T Carrington
The Journal of chemical physics 125 (8), 2006
2682006
Efficient calculation of highly excited vibrational energy levels of floppy molecules: The band origins of H+3 up to 35 000 cm−1
MJ Bramley, JW Tromp, T Carrington Jr, GC Corey
The Journal of chemical physics 100 (9), 6175-6194, 1994
2431994
Neural network potential energy surfaces for small molecules and reactions
S Manzhos, T Carrington Jr
Chemical Reviews 121 (16), 10187-10217, 2020
2202020
Neural networks vs Gaussian process regression for representing potential energy surfaces: A comparative study of fit quality and vibrational spectrum accuracy
A Kamath, RA Vargas-Hernández, RV Krems, T Carrington, S Manzhos
The Journal of chemical physics 148 (24), 2018
2142018
Neural network‐based approaches for building high dimensional and quantum dynamics‐friendly potential energy surfaces
Sergei Manzhos, Richard Dawes, Tucker Carrington
International Journal of Quantum Chemistry 115 (16), 1012-1020, 2015
2112015
A contracted basis-Lanczos calculation of vibrational levels of methane: Solving the Schrödinger equation in nine dimensions
XG Wang, T Carrington Jr
The Journal of chemical physics 119 (1), 101-117, 2003
2112003
A nested molecule-independent neural network approach for high-quality potential fits
S Manzhos, X Wang, R Dawes, T Carrington
The Journal of Physical Chemistry A 110 (16), 5295-5304, 2006
2072006
Vinylidene: Potential energy surface and unimolecular reaction dynamics
T Carrington Jr, LM Hubbard, HF Schaefer III, WH Miller
The Journal of chemical physics 80 (9), 4347-4354, 1984
2011984
Using neural networks to represent potential surfaces as sums of products
S Manzhos, T Carrington
The Journal of chemical physics 125 (19), 2006
1932006
Reaction surface Hamiltonian for the dynamics of reactions in polyatomic systems
T Carrington Jr, WH Miller
The Journal of chemical physics 81 (9), 3942-3950, 1984
1791984
A general framework for discrete variable representation basis sets
RG Littlejohn, M Cargo, T Carrington Jr, KA Mitchell, B Poirier
The Journal of chemical physics 116 (20), 8691-8703, 2002
1702002
Vibrational energy levels of CH5+
XG Wang, T Carrington
The Journal of chemical physics 129 (23), 2008
1632008
The structure of Nb3O and Nb3O+ determined by pulsed field ionization–zero electron kinetic energy photoelectron spectroscopy and density functional theory
DS Yang, MZ Zgierski, DM Rayner, PA Hackett, A Martinez, DR Salahub, ...
The Journal of chemical physics 103 (13), 5335-5342, 1995
1581995
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