March 3, 2026Quantitative Economics2 citationsOpen Access

Dynamic programming in economics on a quantum annealer

JFJesús Fernández‐VillaverdeCenter for Economic and Policy Research IHIsaiah HullUniversity of North Carolina at Chapel Hill

Key Points

Recovery of value and policy functions improves economic modeling with dynamic programming techniques.
Quantum annealers generate global solutions in milliseconds, making them powerful for combinatorial optimization tasks.
Algorithms avoid scaling issues faced by traditional methods, providing practical applications on current quantum hardware.
The approach demonstrates applications on the real business cycle model, indicating the potential for broader economic insights.

Abstract

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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