Quantum feedback algorithms for DNA assembly using FALQON variants

• URL: http://arxiv.org/abs/2602.21080v1
• Date: Tue, 24 Feb 2026 16:44:24 GMT
• Title: Quantum feedback algorithms for DNA assembly using FALQON variants
• Authors: Pedro M. Prado, Lucas A. M. Rattighieri, Rafael Simões do Carmo, Giovanni S. Franco, Guilherme E. L. Pexe, Alexandre Drinko, Erick G. Dorlass, Tatiana F. de Almeida, Felipe F. Fanchini,
• Abstract summary: We analyze long-read DNA fragments from SARS-CoV-2 and human DNA using standard FALQON, second-order FALQON (SO-FALQON), and time-rescaled FALQON (TR-FALQON)<n> Numerical results show that both variants improve convergence to the ground state and increase success probabilities at reduced circuit depths.
• Score: 31.458406135473805
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Reconstructing DNA sequences without a reference, known as de novo assembly, is a complex computational task involving the alignment of overlapping fragments. To address this problem, a usual strategy is to map the assembly to a Quadratic Unconstrained Binary Optimization (QUBO) formulation, which can be solved by different quantum algorithms. In this work, we focus on three versions of the Feedback-based Algorithm, a protocol that eliminates classical optimization loops via measurement feedback. We analyze long-read DNA fragments from SARS-CoV-2 and human mitochondrial DNA using standard FALQON, second-order FALQON (SO-FALQON), and time-rescaled FALQON (TR-FALQON). Numerical results show that both variants improve convergence to the ground state and increase success probabilities at reduced circuit depths. These findings indicate that enhanced feedback-driven dynamics are effective for solving combinatorial problems on near-term quantum hardware.

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