Scalable Quantum State Preparation for Encoding Genomic Data with Matrix Product States

Fuente: arXiv
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Bibliographic Details
Main Authors: Creevey, Floyd M., Hassan, Hitham T., McCafferty, James, Hollenberg, Lloyd C. L., Strelchuk, Sergii
Format: Preprint
Published: 2025
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author Creevey, Floyd M.
Hassan, Hitham T.
McCafferty, James
Hollenberg, Lloyd C. L.
Strelchuk, Sergii
author_facet Creevey, Floyd M.
Hassan, Hitham T.
McCafferty, James
Hollenberg, Lloyd C. L.
Strelchuk, Sergii
contents As quantum computing hardware advances, the need for algorithms that facilitate the loading of classical data into the quantum states of these devices has become increasingly important. This study presents a method for producing scalable quantum circuits to encode genomic data using the Matrix Product State (MPS) formalism. The method is illustrated by encoding the genome of the bacteriophage $ΦX174$ into a 15-qubit state, and analysing the trade-offs between MPS bond dimension, reconstruction error, and the resulting circuit complexity. This study proposes methods for optimising encoding circuits with standard benchmark datasets for the emerging field of quantum bioinformatics. The results for circuit generation and simulation on HPC and on current quantum hardware demonstrate the viability and utility of the encoding.
format Preprint
id arxiv_https___arxiv_org_abs_2508_06184
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Scalable Quantum State Preparation for Encoding Genomic Data with Matrix Product States
Creevey, Floyd M.
Hassan, Hitham T.
McCafferty, James
Hollenberg, Lloyd C. L.
Strelchuk, Sergii
Quantum Physics
As quantum computing hardware advances, the need for algorithms that facilitate the loading of classical data into the quantum states of these devices has become increasingly important. This study presents a method for producing scalable quantum circuits to encode genomic data using the Matrix Product State (MPS) formalism. The method is illustrated by encoding the genome of the bacteriophage $ΦX174$ into a 15-qubit state, and analysing the trade-offs between MPS bond dimension, reconstruction error, and the resulting circuit complexity. This study proposes methods for optimising encoding circuits with standard benchmark datasets for the emerging field of quantum bioinformatics. The results for circuit generation and simulation on HPC and on current quantum hardware demonstrate the viability and utility of the encoding.
title Scalable Quantum State Preparation for Encoding Genomic Data with Matrix Product States
topic Quantum Physics
url https://arxiv.org/abs/2508.06184