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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
10232000
Encyclopedia of computational chemistry
PR Schleyer
(No Title), 1998
5961998
Variational quantum approaches for computing vibrational energies of polyatomic molecules
JM Bowman, T Carrington, HD Meyer
Molecular Physics 106 (16-18), 2145-2182, 2008
4832008
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
4341993
The discrete variable representation of a triatomic Hamiltonian in bond length–bond angle coordinates
H Wei, T Carrington Jr
The Journal of chemical physics 97 (5), 3029-3037, 1992
3931992
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
3041986
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
2832006
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
2811988
Neural network potential energy surfaces for small molecules and reactions
S Manzhos, T Carrington Jr
Chemical Reviews 121 (16), 10187-10217, 2020
2502020
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
2421994
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
2242018
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
2152003
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
2142015
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
2142006
Vinylidene: Potential energy surface and unimolecular reaction dynamics
T Carrington, LM Hubbard, HF Schaefer, WH Miller
The Journal of chemical physics 80 (9), 4347-4354, 1984
2031984
Using neural networks to represent potential surfaces as sums of products
S Manzhos, T Carrington
The Journal of chemical physics 125 (19), 2006
2002006
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
1771984
A general framework for discrete variable representation basis sets
RG Littlejohn, M Cargo, T Carrington, KA Mitchell, B Poirier
The Journal of chemical physics 116 (20), 8691-8703, 2002
1722002
Vibrational energy levels of CH5+
XG Wang, T Carrington
The Journal of chemical physics 129 (23), 2008
1662008
New ideas for using contracted basis functions with a Lanczos eigensolver for computing vibrational spectra of molecules with four or more atoms
XG Wang, T Carrington Jr
The Journal of chemical physics 117 (15), 6923-6934, 2002
1592002
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