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Two-parameter counter-diabatic driving in quantum annealing

Luise Prielinger, Andreas Hartmann, Yu Yamashiro, Kohji Nishimura, Wolfgang Lechner, Hidetoshi Nishimori

2021Physical Review Research37 citationsDOIOpen Access PDF

Abstract

We introduce a two-parameter approximate counter-diabatic term into the Hamiltonian of the transversefield Ising model for quantum annealing to accelerate convergence to the solution, generalizing an existing single-parameter approach. The protocol is equivalent to unconventional diabatic control of the longitudinal and transverse fields in the transverse-field Ising model and thus makes it more feasible for experimental realization than an introduction of new terms such as nonstoquastic catalysts toward the same goal of performance enhancement. We test the idea for the p-spin model with p = 3, which has a first-order quantum phase transition, and show that our two-parameter approach leads to significantly larger ground-state fidelity and lower residual energy than those by traditional quantum annealing and by the single-parameter method. We also find a scaling advantage in terms of the time-to-solution as a function of the system size in a certain range of parameters as compared to the traditional methods in the sense that an exponential time complexity is reduced to another exponential complexity with a smaller coefficient. Although the present method may not always lead to a drastic exponential speedup in difficult optimization problems, it is useful because of its versatility and applicability for any problem after a simple algebraic manipulation, in contrast to some other powerful prescriptions for acceleration such as nonstoquastic catalysts in which one should carefully study in advance if it works in a given problem and should identify a proper way to meticulously control the system parameters to achieve the goal, which is generally highly nontrivial.

Topics & Concepts

Quantum annealingSpeedupIsing modelExponential functionHamiltonian (control theory)QuantumStatistical physicsScalingDiabaticMathematicsApplied mathematicsComputer scienceQuantum computerAdiabatic processAdiabatic quantum computationQuantum mechanicsLattice (music)ResidualQuantum systemQuantum decoherenceSimulated annealingIterated functionMathematical optimizationAlgorithmRealization (probability)Markov chainDetailed balanceControl theory (sociology)Convergence (economics)Quantum algorithmQuantum Computing Algorithms and ArchitectureQuantum Information and CryptographyQuantum many-body systems