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quant-ph2025

Genetically Engineered Quantum Circuits for Financial Market Indicators

Floyd M. Creevey, Lloyd C. L. Hollenberg

Quantum computing holds immense potential for transforming financial analysis and decision-making. Realising this potential necessitates the efficient encoding and processing of fi…

quant-ph2025

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

Floyd M. Creevey, Hitham T. Hassan, James McCafferty +2

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 impor…

quant-ph2025

Implementation of a quantum sequence alignment algorithm for quantum bioinformatics

Floyd M. Creevey, Mingrui Jing, Lloyd C. L. Hollenberg

This paper presents the implementation of a quantum sequence alignment (QSA) algorithm on biological data in environments simulating noisy intermediate-scale quantum (NISQ) compute…

quant-ph2023

Kernel Alignment for Quantum Support Vector Machines Using Genetic Algorithms

Floyd M. Creevey, Jamie A. Heredge, Martin E. Sevior +1

The data encoding circuits used in quantum support vector machine (QSVM) kernels play a crucial role in their classification accuracy. However, manually designing these circuits po…

quant-ph2023

Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning

Maxwell T. West, Azar C. Nakhl, Jamie Heredge +4

Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realisation for practical applications re…