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

TL;DR

This paper introduces a scalable quantum circuit method for encoding genomic data using Matrix Product States, demonstrating its effectiveness on benchmark datasets and current quantum hardware.

Contribution

It presents a novel scalable quantum encoding method for genomic data using MPS, optimizing circuit complexity and demonstrating practical viability.

Findings

Successful encoding of bacteriophage genome into 15-qubit state

Trade-offs identified between MPS bond dimension, error, and circuit complexity

Method validated on HPC and current quantum hardware

Abstract

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 $\Phi X174$ 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.