Preparation of many-body states for quantum simulation.

While quantum computers are capable of simulating many quantum systems efficiently, the simulation algorithms must begin with the preparation of an appropriate initial state. We present a method for generating physically relevant quantum states on a lattice in real space. In particular, the present algorithm is able to prepare general pure and mixed many-particle states of any number of particles. It relies on a procedure for converting from a second-quantized state to its first-quantized counterpart. The algorithm is efficient in that it operates in time that is polynomial in all the essential descriptors of the system, the number of particles, the resolution of the lattice, and the inverse of the maximum final error. This scaling holds under the assumption that the wave function to be prepared is bounded or its indefinite integral is known and that the Fock operator of the system is efficiently simulatable.

[1]  I. Chuang,et al.  Quantum Computation and Quantum Information: Introduction to the Tenth Anniversary Edition , 2010 .

[2]  Alán Aspuru-Guzik,et al.  Quantum algorithm for obtaining the energy spectrum of molecular systems. , 2008, Physical chemistry chemical physics : PCCP.

[3]  I. Kassal,et al.  Polynomial-time quantum algorithm for the simulation of chemical dynamics , 2008, Proceedings of the National Academy of Sciences.

[4]  Amnon Ta-Shma,et al.  Adiabatic Quantum State Generation , 2007, SIAM J. Comput..

[5]  C. Mawson,et al.  37 , 2006, Tao te Ching.

[6]  M. Head‐Gordon,et al.  Simulated Quantum Computation of Molecular Energies , 2005, Science.

[7]  R. Cleve,et al.  Efficient Quantum Algorithms for Simulating Sparse Hamiltonians , 2005, quant-ph/0508139.

[8]  V. Bergholm,et al.  Quantum circuits with uniformly controlled one-qubit gates (7 pages) , 2004, quant-ph/0410066.

[9]  Andrei N. Soklakov,et al.  Efficient state preparation for a register of quantum bits , 2004, quant-ph/0408045.

[10]  Mikko Möttönen,et al.  Transformation of quantum states using uniformly controlled rotations , 2004, Quantum Inf. Comput..

[11]  E. Novak Quantum Complexity of Integration , 2000, Journal of Complexity.

[12]  G. Brassard,et al.  Quantum Amplitude Amplification and Estimation , 2000, quant-ph/0005055.

[13]  R. Feynman Simulating physics with computers , 1999 .

[14]  D. DiVincenzo,et al.  Problem of equilibration and the computation of correlation functions on a quantum computer , 1998, quant-ph/9810063.

[15]  S. Lloyd,et al.  Quantum Algorithm Providing Exponential Speed Increase for Finding Eigenvalues and Eigenvectors , 1998, quant-ph/9807070.

[16]  J. Borwein,et al.  Pi and the AGM: A Study in Analytic Number Theory and Computational Complexity , 1998 .

[17]  Daniel A. Lidar,et al.  Calculating the thermal rate constant with exponential speedup on a quantum computer , 1998, quant-ph/9807009.

[18]  Christof Zalka Simulating quantum systems on a quantum computer , 1996, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[19]  R. Cleve,et al.  Quantum algorithms revisited , 1997, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[20]  Ronald L. Wasserstein,et al.  Monte Carlo: Concepts, Algorithms, and Applications , 1997 .

[21]  Richard A. Friesner,et al.  Ab initio quantum chemical calculation of electron transfer matrix elements for large molecules , 1997 .

[22]  D. Abrams,et al.  Simulation of Many-Body Fermi Systems on a Universal Quantum Computer , 1997, quant-ph/9703054.

[23]  Seth Lloyd,et al.  Universal Quantum Simulators , 1996, Science.

[24]  L. Ballentine,et al.  Quantum Theory: Concepts and Methods , 1994 .

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

[26]  P. Bunker,et al.  Molecular symmetry and spectroscopy , 1979 .

[27]  F. Cotton Chemical Applications of Group Theory , 1971 .