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Article
Peer-Review Record

Quantum–Classical Optimization for Efficient Genomic Data Transmission

Mathematics 2025, 13(17), 2792; https://doi.org/10.3390/math13172792
by Ismael Soto 1,*, Verónica García 2 and Pablo Palacios Játiva 3
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Mathematics 2025, 13(17), 2792; https://doi.org/10.3390/math13172792
Submission received: 26 July 2025 / Revised: 24 August 2025 / Accepted: 28 August 2025 / Published: 30 August 2025

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript proposes a hybrid classical–quantum architecture for genomic data transmission and integrates Grover’s algorithm to accelerate Reed–Solomon (RS) decoding. However, I think the use of Grover’s algorithm is not justified in the context of small, fixed-size RS codes such as RS(4,2).   Grover’s theoretical speedup (from O(N) to O(√N)) is only meaningful for large search spaces. In this paper, the RS code size is too small for any quantum advantage to be realized.

Moreover, the authors do not provide: - Practical list sizes, - Oracle construction details, - Runtime comparisons with classical algorithms, or - Any hardware feasibility analysis. Given that classical decoders are faster and more efficient for such small codes, the claimed benefit of Grover’s algorithm is unconvincing. Unless larger RS codes or real quantum implementation details are added, this part of the method should be reconsidered or significantly reframed.  

Recommendation: Major Revision

Author Response

Thanks to the reviewers for their comments, which have been addressed in the attached document.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

In this manuscript ‘Quantum-Classical Optimization for Efficient Genomic Data Transmission’, the authors propose a hybrid computational architecture for efficient and robust digital transmission inspired by helical genetic structures. This work can be seen as an application of a quantum-assisted method to the genomic data transmission. 

In details, the proposed system integrates advanced modulation schemes. Through mathematical modelling and simulation, the authors demonstrate that the number of helical transmissions required for genome-scale data can be drastically reduce up to 95% when using parallel strands and high-order modulation. They also compare classical genetic algorithms and Grover’s quantum search algorithm. These results contribute to the field of operations research and supply chain communication.

I believe the detailed formulas and simulations are correct in general, and I will approve its acceptance after the authors consider my points below:  

1) Does the simulation you mentioned is quantum or quantum-classical simulation?

2) Quantum Fourier transformation is a key in your theory when encoding, and you introduce it in part 2.3. Given that the future practical quantum computer may be qutrit or qudit systems, taking advantages of qubits systems, I want to introduce the high-dimensional quantum Fourier transformation algorithm that has higher efficiency and accuracy than the general two dimensional one.

3) You mentioned quantum quantum-assisted search and decoding. Does the search and encoding systems or processes are open systems or closed system? A work of quantum simulation for open systems [r1] can be applied to quantum-assisted search and decoding by quantum ancillary system. This can be introduced in the in the introduction part to attract a wider range of readers from the frontier area of open/dissipative/non-Hermitian physics:

[r1] Chao Zheng. Universal quantum simulation of single‐qubit nonunitary operators using duality quantum algorithm. Scientific Reports, 2021, 11: 3960.

4) In line 149, you ‘entanglement-assisted’. Please check the grammar of this sentence. If it related an entanglement-assisted quantum encoding, a relevant work [r2, Science China Physics, Mechanics & Astronomy, 2014, 57(7): 1238-1243] to apply EPR entanglement to quantum dialogue encoding should better be introduced.

Author Response

Thanks to the reviewers for their comments, which have been addressed in the attached document.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Dear authors,

Thank you for the revised manuscript. Overall, it looks good to me. My previous major comments on Grover's algorithm have been partially addressed in the current version. I would suggest including an explicit formula or a scaling plot for the number of operations required for both the classical and quantum methods after Example 1. This will help readers understand the exact point at which the quantum algorithm can outperform the classical one, and it will strengthen the manuscript.

Best regards,
Reviewer

Author Response

We thank the reviewer for your comments, which have been addressed in the attached document.

Author Response File: Author Response.pdf

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