An efficient and accurate analytic gradient method is presented for Hartree–Fock and density functional calculations using multiresolution analysis in multiwavelet bases. The derivative is efficiently computed as an inner product between compressed forms of the density and the differentiated nuclear potential through the Hellmann–Feynman theorem. A smoothed nuclear potential is directly differentiated, and the smoothing parameter required for a given accuracy is empirically determined from calculations on six homonuclear diatomic molecules. The derivatives of N2 molecule are shown using multiresolution calculation for various accuracies with comparison to correlation consistent Gaussian-type basis sets. The optimized geometries of several molecules are presented using Hartree–Fock and density functional theory. A highly precise Hartree–Fock optimization for the H2O molecule produced six digits for the geometric parameters.

1.
R. J. Harrison, G. I. Fann, T. Yanai, Z. Gan, and G. Beylkin, J. Chem. Phys. (in press).
2.
S. Jaffard, Y. Meyer, and R. D. Ryan, Wavelets: Tools for Science and Technology (SIAM, Philadelphia, PA, 1989).
3.
G.
Beylkin
,
R.
Coifman
, and
V.
Rokhlin
,
Commun. Pure Appl. Math.
44
,
141
(
1991
).
4.
R. G. Parr and W. Yang, Density-Functional Theory of Atoms and Molecules (Oxford University Press, New York, 1989).
5.
T.
Yanai
,
G. I.
Fann
,
Z.
Gan
,
R. J.
Harrison
, and
G.
Beylkin
, J. Chem. Phys. (to be published).
6.
B.
Alpert
,
G.
Beylkin
,
D.
Gines
, and
L.
Vozovoi
,
J. Comput. Phys.
182
,
149
(
2002
).
7.
P.
Pulay
,
Mol. Phys.
17
,
197
(
1969
).
8.
P.
Pulay
,
G.
Fogarasi
,
F.
Pang
, and
J. E.
Boggs
,
J. Am. Chem. Soc.
101
,
2550
(
1979
).
9.
R.
Car
and
M.
Parrinello
,
Phys. Rev. Lett.
55
,
2471
(
1985
).
10.
J. S.
Tse
,
Annu. Rev. Phys. Chem.
53
,
249
(
2002
).
11.
M.
Dupuis
and
H. F.
King
,
J. Chem. Phys.
68
,
3998
(
1978
).
12.
B. Alpert, Ph.D. thesis, Yale University, 1990.
13.
B.
Alpert
,
SIAM J. Math. Anal.
24
,
246
(
1993
).
14.
B.
Alpert
,
G.
Beylkin
,
R. R.
Coifman
, and
V.
Rokhlin
,
SIAM J. Sci. Comput.
14
,
159
(
1993
).
15.
A.
Patera
,
J. Comput. Phys.
54
,
468
(
1984
).
16.
G.
Beylkin
and
R.
Cramer
,
SIAM J. Sci. Comput.
24
,
81
(
2002
).
17.
G.
Beylkin
and
M. J.
Mohlenkamp
,
Proc. Natl. Acad. Sci. U.S.A.
99
,
10246
(
2002
).
18.
R. M.
Dickson
and
A. D.
Becke
,
J. Chem. Phys.
99
,
3898
(
1993
).
19.
J. C.
Phillips
and
L.
Kleinman
,
Phys. Rev.
116
,
287
(
1959
).
20.
J.
Ihm
,
A.
Zunger
, and
M. L.
Cohen
,
J. Phys. C
12
,
4409
(
1979
).
21.
L.
Visscher
and
K. G.
Dyall
,
At. Data Nucl. Data Tables
67
,
207
(
1997
).
22.
Multiresolution adaptive numerical scientific simulation.
23.
The PYTHON programming language, an object-oriented scripting and rapid application development language. Web site: http://www.python.org/
24.
T. H.
Dunning
, Jr.
,
J. Chem. Phys.
90
,
1007
(
1989
).
25.
D. E.
Woon
and
T. H.
Dunning
, Jr.
,
J. Chem. Phys.
100
,
2975
(
1994
).
26.
R. A.
Kendall
,
T. H.
Dunning
, Jr.
, and
R. J.
Harrison
,
J. Chem. Phys.
96
,
6796
(
1992
).
27.
D. E.
Woon
and
T. H.
Dunning
, Jr.
,
J. Chem. Phys.
98
,
1358
(
1993
).
28.
R. J. Harrison, J. A. Nichols, T. P. Straatsma et al., NWCHEM, Version 4.1 (Pacific Northwest National Laboratory, Richland, WA, 2002).
29.
C. G.
Broyden
,
J. Inst. Math. Appl.
6
,
76
(
1970
).
30.
R.
Fletcher
,
Comput. J.
13
,
317
(
1970
).
31.
D.
Goldfarb
,
Math. Comput.
24
,
23
(
1970
).
32.
D. F.
Shanno
,
Math. Comput.
24
,
647
(
1970
).
33.
W. H.
Huo
,
J. Chem. Phys.
43
,
624
(
1965
).
34.
P. E.
Cade
,
K. D.
Sales
, and
A. C.
Wahl
,
J. Chem. Phys.
44
,
1973
(
1966
).
35.
P. E.
Cade
and
W. J.
Huo
,
J. Chem. Phys.
47
,
614
(
1967
).
36.
W.
Meyer
,
J. Chem. Phys.
58
,
1017
(
1973
).
37.
A.
Rauk
,
L. C.
Allen
, and
E.
Clementi
,
J. Chem. Phys.
52
,
4133
(
1970
).
38.
F. A.
Pahl
and
N. C.
Handy
,
Mol. Phys.
100
,
3199
(
2002
).
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