Global quantum optimization algorithm for combinatorial optimization problems in NISQ devices

A computer program product for employing quantum optimization algorithms for combinatorial optimization problems in noisy intermediate-scale quantum (NISQ) devices, the computer program product comprising one or more computer readable storage mediums having program code embodied therewith, the program code comprising programming instructions for:

• defining a non-linear objective function of a combinatorial optimization problem to be minimized, wherein an input to said objective function corresponds to circuit parameters, wherein an output of said objective function corresponds to an indicator value;
• initializing said circuit parameters of said objective function;
• employing a Gauss-Newton based quantum algorithm for local optimization to output said indicator value of said objective function based on said circuit parameters and to output a solution of said combinatorial optimization problem based on said circuit parameters;
• and
• employing Bayesian optimization for global optimization in response to said solution of said combinatorial optimization problem not reaching a correct solution, wherein said Bayesian optimization updates said circuit parameters to minimize said indicator value.

A system, comprising:

• a memory for storing a computer program for employing quantum optimization algorithms for combinatorial optimization problems in noisy intermediate-scale quantum (NISQ) devices;
• and
• a processor connected to said memory, wherein said processor is configured to execute program instructions of the computer program comprising:
• defining a non-linear objective function of a combinatorial optimization problem to be minimized, wherein an input to said objective function corresponds to circuit parameters, wherein an output of said objective function corresponds to an indicator value;
• initializing said circuit parameters of said objective function;
• employing a Gauss-Newton based quantum algorithm for local optimization to output said indicator value of said objective function based on said circuit parameters and to output a solution of said combinatorial optimization problem based on said circuit parameters;
• and
• employing Bayesian optimization for global optimization in response to said solution of said combinatorial optimization problem not reaching a correct solution, wherein said Bayesian optimization updates said circuit parameters to minimize said indicator value.