arXiv:2602.21080

Quantum feedback algorithms for DNA assembly using FALQON variants

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

quant-phSubmitted Feb 24, 2026• Announced Feb 25, 2026• 1 citation

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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.

Comments: 10 pages, 2 figures

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