Quantum feedback algorithms for DNA assembly using FALQON variants
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2026
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866912923400536064 |
|---|---|
| author | Prado, Pedro M. Rattighieri, Lucas A. M. Carmo, Rafael Simões do Franco, Giovanni S. Pexe, Guilherme E. L. Drinko, Alexandre Dorlass, Erick G. de Almeida, Tatiana F. Fanchini, Felipe F. |
| author_facet | Prado, Pedro M. Rattighieri, Lucas A. M. Carmo, Rafael Simões do Franco, Giovanni S. Pexe, Guilherme E. L. Drinko, Alexandre Dorlass, Erick G. de Almeida, Tatiana F. Fanchini, Felipe F. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_21080 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Quantum feedback algorithms for DNA assembly using FALQON variants Prado, Pedro M. Rattighieri, Lucas A. M. Carmo, Rafael Simões do Franco, Giovanni S. Pexe, Guilherme E. L. Drinko, Alexandre Dorlass, Erick G. de Almeida, Tatiana F. Fanchini, Felipe F. Quantum Physics 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. |
| title | Quantum feedback algorithms for DNA assembly using FALQON variants |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2602.21080 |