CHAMP
Cornell-Holland Ab-initio Materials Package
If you wish to use this program, please contact one of the principal authors: Cyrus Umrigar (cyrus@tc.cornell.edu, +1-607-254-8710) Claudia Filippi (filippi@lorentz.leidenuniv.nl, +31-71-5275520)
CHAMP is presently a suite of programs with the following three basic capabilities:
- Optimization of many-body wave functions by variance minimization (FIT)
- Optimization of many-body wave functions by any linear combination of energy and variance minimization (VMC)
- Metropolis or Variational Monte Carlo (VMC)
- Diffusion Monte Carlo (DMC)
In each case, the very best quantum Monte carlo algorithms have been used. A great deal of attention has been paid to the implementation of highly efficient algorithms, a variety of sophisticated wave functions, and tools to optimize them, with particular emphasis on all-electron and pseudopotential finite systems. For such systems, the code can also compute forces on the nuclei, a necessary precursor of molecular dynamics calculations. There are both serial and parallel (MPI) versions of the codes.
Particularly noteworthy features of CHAMP are:
Recent applications of the code CHAMP
Particularly noteworthy features of CHAMP are:
Efficient wave function optimization by variance minimization
- Optimized trial wave functions for quantum Monte Carlo calculations,
C.J. Umrigar, K.G. Wilson and J.W. Wilkins, Phys. Rev. Lett.,60, 1719 (1988). - A method for determining many-body wave functions,
C.J. Umrigar, K.G. Wilson and J.W. Wilkins,
in Computer simulation studies in condensed matter physics: recent developments,
ed. by D.P. Landau, K.K. Mon and H.B. Schuttler (Springer-Verlag 1988). - Two Aspects of Quantum Monte Carlo: Determination of Accurate Wavefunctions and Determination of Potential Energy Surfaces of Molecules,
C.J. Umrigar, Int. J. Quant. Chem. Symp., 23, 217 (1989).
Even more efficient wave function optimization by energy/variance minimization
- Alleviation of the Fermion-Sign Problem by Optimization of Many-Body Wave Functions,
C. J. Umrigar, J. Toulouse, C. Filippi, S. Sorella and R. G. Hennig,
Phys. Rev. Lett. 98, 110201 (2007). [pdf] - Optimization of quantum Monte Carlo wave functions by energy minimization,
J. Toulouse, C. J. Umrigar,
J. Chem. Phys.Phys. 126, 084102 (2007). [pdf] - Energy and Variance Optimization of Many-Body Wave Functions
C. J. Umrigar and Claudia Filippi,
Phys. Rev. Lett. 94, 150201 (2005). [pdf]
Effective-fluctuation-potential method to optimize the determinantal part
- Variational Monte Carlo in Solids,
S. Fahy, in Quantum Monte Carlo Methods in Physics and Chemistry,
ed. by M.P. Nightingale and C.J. Umrigar. NATO ASI Series, Vol. C-525 (Kluwer Academic Publishers, Boston, 1999). - Optimal orbitals from energy fluctuations in correlated wave functions,
C. Filippi and S. Fahy, J. Chem. Phys. 112, 3523 (2000). - Optimization of CI coefficients in multi-determinant Jastrow-Slater wave functions
F. Schautz and S. Fahy, J. Chem. Phys. 116, 3533 (2002).
Sophisticated Jastrow factors, including e-n, e-e and e-e-n correlations (e=electron, n=nucleus)
- Multiconfiguration wave functions for Quantum Monte Carlo calculations of first-row diatomic molecules
Claudia Filippi and C.J. Umrigar, J. Chem. Phys. 105, 213 (1996).
The most recent form has not been published but notes can be obtained from Cyrus Umrigar.
Accelerated Metropolis method
- Accelerated Metropolis Method,
C.J. Umrigar, Phys. Rev. Lett. 71, 408 (1993). - Variational Monte Carlo Basics and Applications to Atoms and Molecules,
C.J. Umrigar, in Quantum Monte Carlo Methods in Physics and Chemistry, ed. by M.P. Nightingale and C.J. Umrigar. NATO ASI Series, Series C, Mathematical and Physical Sciences, Vol. C-525, (Kluwer Academic Publishers, Boston, 1999).
Very efficient diffusion Monte Carlo algorithm
It takes into account the singularities in the local energy and velocity at nodes of the wave function and at particle coincidences.
- A Diffusion Monte Carlo Algorithm with Very Small Time-Step Errors,
C.J. Umrigar, M.P. Nightingale and K.J. Runge, J. Chem. Phys., 99, 2865 (1993).
The algorithm has since then been extended to use pseudopotentials and employ single-electron moves.
Calculation of numerical forces on nuclei for finite systems
It employs correlated sampling along with a space-warp coordinate transformation that improves the efficiency.
- Two Aspects of Quantum Monte Carlo: Determination of Accurate Wavefunctions and Potential Energy Surfaces of Molecules,
C.J. Umrigar, Int. J. Quant. Chem. Symp., 23, 217 (1989). - Correlated sampling in quantum Monte Carlo: A route to forces,
C. Filippi and C. J. Umrigar, Phys. Rev. B., 61, R16291, (2000). - Interatomic forces and correlated sampling in quantum Monte Carlo,
C. Filippi and C. J. Umrigar, in Recent Advances in Quantum Monte Carlo Methods, Part II, pgs. 12-29, edited by W.A.Lester, Jr., S.M. Rothstein, and S. Tanaka (World Scientific, Singapore, 2002).