Prog-QAOA: Framework for resource-efficient quantum optimization through classical programs

• URL: http://arxiv.org/abs/2209.03386v3
• Date: Mon, 29 Apr 2024 09:54:17 GMT
• Title: Prog-QAOA: Framework for resource-efficient quantum optimization through classical programs
• Authors: Bence Bakó, Adam Glos, Özlem Salehi, Zoltán Zimborás,
• Abstract summary: Current quantum optimization algorithms require representing the original problem as a binary optimization problem, which is then converted into an equivalent Ising model suitable for the quantum device. We propose to design classical programs for computing the objective function and certifying the constraints, and later compile them to quantum circuits. This results in a new variant of the Quantum Approximate Optimization Algorithm (QAOA), which we name the Prog-QAOA.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Current state-of-the-art quantum optimization algorithms require representing the original problem as a binary optimization problem, which is then converted into an equivalent Ising model suitable for the quantum device. Implementing each term of the Ising model separately often results in high redundancy, significantly increasing the resources required. Instead, we propose to design classical programs for computing the objective function and certifying the constraints, and later compile them to quantum circuits, eliminating the reliance on the binary optimization problem representation. This results in a new variant of the Quantum Approximate Optimization Algorithm (QAOA), which we name the Prog-QAOA. We exploit this idea for optimization tasks like the Travelling Salesman Problem and Max-$K$-Cut and obtain circuits that are near-optimal with respect to all relevant cost measures, e.g., number of qubits, gates, and circuit depth. While we demonstrate the power of Prog-QAOA only for a particular set of paradigmatic problems, our approach is conveniently applicable to generic optimization problems.

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