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This paper advances quantum combinatorial optimization by extending the Decoded Quantum Interferometry framework to various algebraic geometry codes, including Hermitian and Suzuki codes. By leveraging these diverse curve families, the proposed COFI method aims to reduce quantum resource requirements or handle more constraints compared to previous one-point Hermitian approaches. The work represents a significant theoretical step in optimizing quantum algorithms for decoding problems within finite fields.
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COFI-DQI: Curve-based Optimal Function Intersection via Decoded Quantum Interferometry

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.31484v1 Announce Type: cross Abstract: In 2025, Jordan et al. introduced Decoded Quantum Interferometry (DQI), a quantum algorithm for combinatorial optimization based on decoding. They considered Reed-Solomon decoding and its associated optimization problem, called Optimal Polynomial Intersection (OPI), which may be viewed as a polynomial regression problem over a finite field. DQI exhibits provable speedups on certain problem instances and establishes a connection between decoding problems and optimization tasks. Leveraging the well-understood dual structure and decoding theory of algebraic geometry codes from other curve families, we introduce COFI: Curve-based Optimal Function Intersection. By considering two-point Hermitian codes, Suzuki codes, and extended norm-trace codes, we broaden the range of algebraic geometry codes used in DQI and identify families that offer further improvements over one-point Hermitian codes in the Hermitian Optimal Polynomial Intersection framework considered by Jordan and Gu. Depending on the family and parameter regime, these curves can reduce quantum resource requirements or increase the number of constraints that can be considered.

Abstract:In 2025, Jordan et al. introduced Decoded Quantum Interferometry (DQI), a quantum algorithm for combinatorial optimization based on decoding. They considered Reed-Solomon decoding and its associated optimization problem, called Optimal Polynomial Intersection (OPI), which may be viewed as a polynomial regression problem over a finite field. DQI exhibits provable speedups on certain problem instances and establishes a connection between decoding problems and optimization tasks. Leveraging the well-understood dual structure and decoding theory of algebraic geometry codes from other curve families, we introduce COFI: Curve-based Optimal Function Intersection. By considering two-point Hermitian codes, Suzuki codes, and extended norm-trace codes, we broaden the range of algebraic geometry codes used in DQI and identify families that offer further improvements over one-point Hermitian codes in the Hermitian Optimal Polynomial Intersection framework considered by Jordan and Gu. Depending on the family and parameter regime, these curves can reduce quantum resource requirements or increase the number of constraints that can be considered.

Information Theory (cs.IT); Quantum Physics (quant-ph)

arXiv:2609.31484 [cs.IT]

(or arXiv:2609.31484v1 [cs.IT] for this version)

https://doi.org/10.48550/arXiv.2609.31484 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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