Dynamic Programming in Economics on a Quantum Annealer
We introduce novel algorithms for solving dynamic programming problems in economics on a quantum annealer, a specialized quantum computer used for combinatorial optimization. Quantum annealers begin in a superposition of all states and generate candidate global solutions in milliseconds, regardless of problem size. In contrast to existing methods, those developed in this paper 1) recover value and policy functions, 2) avoid fundamental scaling bottlenecks, and 3) are already implementable for small (but non-trivial) problems on current hardware. We demonstrate the method by solving the real business cycle model on a quantum annealer.
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