Near-optimal circuit design for variational quantum optimization | QSD2023

Quantum Science Days is an annual, international, and virtual scientific conference organized by QWorld (Association) to provide opportunities to the quantum community to present and discuss their research results at all levels (from short projects to thesis work to research publications), and to get to know each other. The third edition (QSD2023) included 7 invited speakers, 10 thematic talks on “Building an Open Quantum Ecosystem”, 31 contributed talks, an industrial demo session by Classiq, and a career talk on quantum. QSD2023 was sponsored by Unitary Fund & Classiq and supported by Latvian Quantum Initiative.

Near-optimal circuit design for variational quantum optimization
Speaker: Özlem Salehi
Abstract: Quantum Approximate Optimization Algorithm (QAOA) is one of the leading quantum optimization algorithms and a candidate for showing near-term quantum advantage. In this talk, I will first talk about the state-of-the-art method for implementing QAOA, which often results in redundancy and increased usage of resources. Next, I will introduce Functional QAOA, an alternative approach for implementing QAOA which results in near-optimal circuits with respect to all relevant cost measures (e.g., number of qubits, gates, circuit depth) for optimization tasks like Travelling Salesman Problem and Max-K-Cut.
References:
B Bakó, A Glos, Ö Salehi, Z Zimborás, “Near-optimal circuit design for variational quantum optimization.”, arXiv preprint arXiv:2209.03386, 2022
E. Farhi, J. Goldstone, and S. Gutmann, “A quantum approximate optimization algorithm,” Tech. Rep. MIT-CTP/4610, 2014.
S. Hadfield, Z. Wang, B. O’Gorman, E. G. Rieffel, D. Venturelli, and R. Biswas, “From the quantum approximate optimization algorithm to a quantum alternating operator ansatz,” Algorithms, vol. 12, no. 2, p. 34, 2019.
A. Glos, A. Krawiec, and Z. Zimbor´as, “Space-efficient binary optimization for variational quantum computing,” npj Quantum Information, vol. 8, no. 1, pp. 1–8, 2022.

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25:39 QUBO formulation for TSP repeats same constraints, indexes should be swapped