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DEFENSE OF FUNCTIONAL FUNCTIONS IN QUANTUM APPROXIMATION OPTIMIZATION
DEFENSE OF FUNCTIONAL FUNCTIONS IN QUANTUM APPROXIMATION OPTIMIZATION
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机译：量子逼近优化中的函数泛函
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摘要
Techniques are provided for performing a deformation of cost functions in quantum approximation optimization. The techniques involve assigning a cost function associated with a combinatorial optimization problem to an optimization problem over feasible quantum states. A quantum Hamilton function is set up for the effort function, and a set of test states is generated by a physical time evolution of the quantum hardware into which control pulses are interspersed. Aspects include measuring a quantum cost function for the test states, determining a test state leading to optimal values and deforming a Hamilton function, and using the optimal state as the next starting state for a next optimization on a deformed Hamilton function until an optimizer with respect to a desired one Hamilton function is determined.
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