Hybrid quantum annealing via molecular dynamics

A novel quantum–classical hybrid scheme is proposed to efficiently solve large-scale combinatorial optimization problems. The key concept is to introduce a Hamiltonian dynamics of the classical flux variables associated with the quantum spins of the transverse-field Ising model. Molecular dynamics of the classical fluxes can be used as a powerful preconditioner to sort out the frozen and ambivalent spins for quantum annealers. The performance and accuracy of our smooth hybridization in comparison to the standard classical algorithms (the tabu search and the simulated annealing) are demonstrated by employing the MAX-CUT and Ising spin-glass problems.

[1]  F. Barahona On the computational complexity of Ising spin glass models , 1982 .

[2]  M. Mézard,et al.  Spin Glass Theory And Beyond: An Introduction To The Replica Method And Its Applications , 1986 .

[3]  H. Nishimori,et al.  Quantum annealing in the transverse Ising model , 1998, cond-mat/9804280.

[4]  Thomas de Quincey [C] , 2000, The Works of Thomas De Quincey, Vol. 1: Writings, 1799–1820.

[5]  E. Farhi,et al.  A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem , 2001, Science.

[6]  A. ADoefaa,et al.  ? ? ? ? f ? ? ? ? ? , 2003 .

[7]  Seth Lloyd,et al.  Adiabatic quantum computation is equivalent to standard quantum computation , 2004, 45th Annual IEEE Symposium on Foundations of Computer Science.

[8]  Seth Lloyd,et al.  Adiabatic Quantum Computation is Equivalent to Standard Quantum Computation , 2007, SIAM J. Comput..

[9]  Double criticality of the SK-model at T = 0. , 2007 .

[10]  H. Nishimori,et al.  Mathematical foundation of quantum annealing , 2008, 0806.1859.

[11]  Seth Lloyd,et al.  Adiabatic Quantum Computation Is Equivalent to Standard Quantum Computation , 2008, SIAM Rev..

[12]  S. Boettcher Simulations of ground state fluctuations in mean-field Ising spin glasses , 2009, 0906.1292.

[13]  Jürg Hutter,et al.  Ab Initio Molecular Dynamics: Basic Theory and Advanced Methods , 2009 .

[14]  M. W. Johnson,et al.  Experimental demonstration of a robust and scalable flux qubit , 2009, 0909.4321.

[15]  M. W. Johnson,et al.  Quantum annealing with manufactured spins , 2011, Nature.

[16]  U. Vazirani,et al.  How "Quantum" is the D-Wave Machine? , 2014, 1401.7087.

[17]  Andrew Lucas,et al.  Ising formulations of many NP problems , 2013, Front. Physics.

[18]  Nicholas Chancellor,et al.  Modernizing quantum annealing using local searches , 2016, 1606.06833.

[19]  Aidan Roy,et al.  Fast clique minor generation in Chimera qubit connectivity graphs , 2015, Quantum Inf. Process..

[20]  Ken-ichi Kawarabayashi,et al.  A coherent Ising machine for 2000-node optimization problems , 2016, Science.

[21]  Steven P. Reinhardt,et al.  Partitioning Optimization Problems for Hybrid Classical/Quantum Execution TECHNICAL REPORT , 2017 .

[22]  Gili Rosenberg,et al.  Boosting quantum annealer performance via sample persistence , 2016, Quantum Inf. Process..

[23]  Helmut G. Katzgraber,et al.  Effective optimization using sample persistence: A case study on quantum annealers and various Monte Carlo optimization methods , 2017, Physical review. E.

[24]  John Preskill,et al.  Quantum Computing in the NISQ era and beyond , 2018, Quantum.

[25]  Daniel A. Lidar,et al.  Adiabatic quantum computation , 2016, 1611.04471.

[26]  Hiroki Takesue,et al.  Large-scale Coherent Ising Machine , 2019, Journal of the Physical Society of Japan.

[27]  Florian Neukart,et al.  A Hybrid Solution Method for the Capacitated Vehicle Routing Problem Using a Quantum Annealer , 2018, Front. ICT.

[28]  Masoud Mohseni,et al.  Quantum-Assisted Genetic Algorithm , 2019, ArXiv.

[29]  Hayato Goto,et al.  Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems , 2019, Science Advances.

[30]  Shinichiro Taguchi,et al.  Improving solutions by embedding larger subproblems in a D-Wave quantum annealer , 2019, Scientific Reports.

[31]  Helmut G. Katzgraber,et al.  Perspectives of quantum annealing: methods and implementations , 2019, Reports on progress in physics. Physical Society.

[32]  Fengqi You,et al.  Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems , 2019, Comput. Chem. Eng..

[33]  M. W. Johnson,et al.  Demonstration of a Nonstoquastic Hamiltonian in Coupled Superconducting Flux Qubits , 2019, Physical Review Applied.

[34]  Danna Zhou,et al.  d. , 1840, Microbial pathogenesis.

[35]  P. Alam ‘W’ , 2021, Composites Engineering.

[36]  P. Alam ‘U’ , 2021, Composites Engineering: An A–Z Guide.

[37]  P. Alam ‘G’ , 2021, Composites Engineering: An A–Z Guide.

[38]  P. Alam,et al.  H , 1887, High Explosives, Propellants, Pyrotechnics.

[39]  P. Alam ‘A’ , 2021, Composites Engineering: An A–Z Guide.

[40]  P. Alam ‘S’ , 2021, Composites Engineering: An A–Z Guide.