Large-scale semidefinite programs in electronic structure calculation

It has been a long-time dream in electronic structure theory in physical chemistry/chemical physics to compute ground state energies of atomic and molecular systems by employing a variational approach in which the two-body reduced density matrix (RDM) is the unknown variable. Realization of the RDM approach has benefited greatly from recent developments in semidefinite programming (SDP). We present the actual state of this new application of SDP as well as the formulation of these SDPs, which can be arbitrarily large. Numerical results using parallel computation on high performance computers are given. The RDM method has several advantages including robustness and provision of high accuracy compared to traditional electronic structure methods, although its computational time and memory consumption are still extremely large.

[1]  Masakazu Kojima,et al.  SDPARA: SemiDefinite Programming Algorithm paRAllel version , 2003, Parallel Comput..

[2]  H. Nakatsuji Equation for the direct determination of the density matrix , 1976 .

[3]  T. H. Dunning Gaussian Basis Functions for Use in Molecular Calculations. III. Contraction of (10s6p) Atomic Basis Sets for the First‐Row Atoms , 1970 .

[4]  P. Jeffrey Hay,et al.  Gaussian Basis Sets for Molecular Calculations , 1977 .

[5]  L. Cohen,et al.  Hierarchy equations for reduced density matrices , 1976 .

[6]  R. Saigal,et al.  Handbook of semidefinite programming : theory, algorithms, and applications , 2000 .

[7]  David A Mazziotti,et al.  Realization of quantum chemistry without wave functions through first-order semidefinite programming. , 2004, Physical review letters.

[8]  Zhengji Zhao The reduced density matrix method for electronic structure calculations: Application of semidefinite programming to N-fermion systems , 2005 .

[9]  I. Mayer The Electron Correlation , 2003 .

[10]  Strength of the G-matrix condition in the reduced-density-matrix variational principle , 1974 .

[11]  On Calculating Approximate and Exact Density Matrices , 2000 .

[12]  H. Schaefer Methods of Electronic Structure Theory , 1977 .

[13]  伏見 康治,et al.  Some formal properties of the density matrix , 1940 .

[14]  The variational calculation of reduced density matrices , 1975 .

[15]  J. Percus,et al.  Reduction of the N‐Particle Variational Problem , 1964 .

[16]  D. Mazziotti Variational minimization of atomic and molecular ground-state energies via the two-particle reduced density matrix , 2002 .

[17]  Effectiveness of Symmetry and the Pauli Condition on the 1 Matrix in the Reduced-Density-Matrix Variational Principle , 1972 .

[18]  D. Mazziotti Cumulants and the Contracted Schrödinger Equation , 2000 .

[19]  C. Valdemoro,et al.  Self‐consistent approximate solution of the second‐order contracted Schröudinger equation , 1994 .

[20]  Richard M. Karp,et al.  On Linear Characterizations of Combinatorial Optimization Problems , 1982, SIAM J. Comput..

[21]  P. Löwdin Quantum Theory of Many-Particle Systems. I. Physical Interpretations by Means of Density Matrices, Natural Spin-Orbitals, and Convergence Problems in the Method of Configurational Interaction , 1955 .

[22]  Per-Olov Löwdin,et al.  QUANTUM THEORY OF MANY-PARTICLE SYSTEMS. , 1969 .

[23]  C. Garrod,et al.  The variational approach to the two−body density matrix , 1975 .

[24]  The variational approach to the density matrix for light nuclei , 1975 .

[25]  H. Nakatsuji,et al.  DIRECT DETERMINATION OF THE QUANTUM-MECHANICAL DENSITY MATRIX USING THE DENSITY EQUATION. II. , 1997 .

[26]  J. Pople,et al.  Self‐Consistent Molecular‐Orbital Methods. I. Use of Gaussian Expansions of Slater‐Type Atomic Orbitals , 1969 .

[27]  Kim-Chuan Toh,et al.  Solving Large Scale Semidefinite Programs via an Iterative Solver on the Augmented Systems , 2003, SIAM J. Optim..

[28]  D. Mazziotti Contracted Schrödinger equation: Determining quantum energies and two-particle density matrices without wave functions , 1998 .

[29]  Jack Dongarra,et al.  ScaLAPACK user's guide , 1997 .

[30]  David A. Mazziotti,et al.  Solution of the 1,3-contracted Schrödinger equation through positivity conditions on the two-particle reduced density matrix , 2002 .

[31]  Renato D. C. Monteiro,et al.  First- and second-order methods for semidefinite programming , 2003, Math. Program..

[32]  A. J. Coleman THE STRUCTURE OF FERMION DENSITY MATRICES , 1963 .

[33]  E. Davidson Linear inequalities for density matrices: III , 2003 .

[34]  Mark S. Gordon,et al.  General atomic and molecular electronic structure system , 1993, J. Comput. Chem..

[35]  The lower bound method for reduced density matrices , 2000 .

[36]  M. Overton,et al.  The reduced density matrix method for electronic structure calculations and the role of three-index representability conditions. , 2004, The Journal of chemical physics.

[37]  H. Nakatsuji,et al.  DIRECT DETERMINATION OF THE DENSITY MATRIX USING THE DENSITY EQUATION : POTENTIAL ENERGY CURVES OF HF, CH4, BH3, NH3, AND H2O , 1999 .

[38]  C. Valdemoro,et al.  Critical Questions Concerning Iterative Solution of the Contracted Schrödinger Equation , 2000 .

[39]  E. Brändas,et al.  Fundamental World of Quantum Chemistry , 2003 .

[40]  A. Szabó,et al.  Modern quantum chemistry : introduction to advanced electronic structure theory , 1982 .

[41]  Michel Deza,et al.  Geometry of cuts and metrics , 2009, Algorithms and combinatorics.

[42]  Jos F. Sturm,et al.  A Matlab toolbox for optimization over symmetric cones , 1999 .

[43]  Henry Wolkowicz,et al.  Handbook of Semidefinite Programming , 2000 .

[44]  Masakazu Kojima,et al.  SDPA (SemiDefinite Programming Algorithm) User's Manual Version 6.2.0 , 1995 .

[45]  Koji Yasuda Direct determination of the quantum-mechanical density matrix: Parquet theory , 1999 .

[46]  J. Pople,et al.  Self‐Consistent Molecular Orbital Methods. IV. Use of Gaussian Expansions of Slater‐Type Orbitals. Extension to Second‐Row Molecules , 1970 .

[47]  K. Fujisawa,et al.  Variational calculations of fermion second-order reduced density matrices by semidefinite programming algorithm , 2001 .

[48]  H. Nakatsuji,et al.  Density matrix variational theory: Strength of Weinhold-Wilson inequalities , 2003 .

[49]  E. Davidson Linear Inequalities for Density Matrices , 1969 .

[50]  A. J. Coleman RDMs: How did we get here? , 2000 .

[51]  David A. Mazziotti,et al.  Uncertainty relations and reduced density matrices: Mapping many-body quantum mechanics onto four particles , 2001 .

[52]  H. Nakatsuji,et al.  Density matrix variational theory: Application to the potential energy surfaces and strongly correlated systems , 2002 .

[53]  Madhu V. Nayakkankuppam,et al.  Optimization Over Symmetric Cones , 1999 .

[54]  A density matrix variational calculation for atomic Be , 1976 .

[55]  K.C. Toh,et al.  On the implementation of SDPT3 (version 3.1) - a MATLAB software package for semidefinite-quadratic-linear programming , 2004, 2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508).

[56]  H. Nakatsuji Density Equation Theory in Chemical Physics , 2000 .

[57]  Valdemoro Approximating the second-order reduced density matrix in terms of the first-order one. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[58]  D. Mazziotti First-order semidefinite programming for the direct determination of two-electron reduced density matrices with application to many-electron atoms and molecules. , 2004, The Journal of chemical physics.