Outputs (30)

Integrating quantum algorithms into classical frameworks: a predictor–corrector approach using HHL (2025)
Journal Article
Rathore, O., Basden, A., Chancellor, N., & Kusumaatmaja, H. (2025). Integrating quantum algorithms into classical frameworks: a predictor–corrector approach using HHL. Quantum Science and Technology, 10(2), Article 025041. https://doi.org/10.1088/2058-9565/adbb14

The application of quantum algorithms to classical problems is generally accompanied by significant bottlenecks when transferring data between quantum and classical states, often negating any intrinsic quantum advantage. Here we address this challeng... Read More about Integrating quantum algorithms into classical frameworks: a predictor–corrector approach using HHL.

Load balancing for high performance computing using quantum annealing (2025)
Journal Article
Rathore, O., Basden, A., Chancellor, N., & Kusumaatmaja, H. (2025). Load balancing for high performance computing using quantum annealing. Physical Review Research, 7(1), Article 013067. https://doi.org/10.1103/PhysRevResearch.7.013067

With the advent of exascale computing, effective load balancing in massively parallel software applications is critically important for leveraging the full potential of high-performance computing systems. Load balancing is the distribution of computa... Read More about Load balancing for high performance computing using quantum annealing.

Quantum optimization with linear Ising penalty functions for customer data science (2024)
Journal Article
Mirkarimi, P., Shukla, I., Hoyle, D. C., Williams, R., & Chancellor, N. (2024). Quantum optimization with linear Ising penalty functions for customer data science. Physical Review Research, 6(4), Article 043241. https://doi.org/10.1103/physrevresearch.6.043241

Constrained combinatorial optimization problems, which are ubiquitous in industry, can be solved by quantum algorithms such as quantum annealing (QA) and the quantum approximate optimization algorithm (QAOA). In these quantum algorithms, constraints... Read More about Quantum optimization with linear Ising penalty functions for customer data science.

Experimental demonstration of improved quantum optimization with linear Ising penalties (2024)
Journal Article
Mirkarimi, P., Hoyle, D. C., Williams, R., & Chancellor, N. (2024). Experimental demonstration of improved quantum optimization with linear Ising penalties. New Journal of Physics, 26(10), Article 103005. https://doi.org/10.1088/1367-2630/ad7e4a

The standard approach to encoding constraints in quantum optimization is the quadratic penalty method. Quadratic penalties introduce additional couplings and energy scales, which can be detrimental to the performance of a quantum optimizer. In quantu... Read More about Experimental demonstration of improved quantum optimization with linear Ising penalties.

Cycle discrete-time quantum walks on a noisy quantum computer (2024)
Journal Article
Wadhia, V., Chancellor, N., & Kendon, V. (2024). Cycle discrete-time quantum walks on a noisy quantum computer. The European Physical Journal D, 78(3), Article 29. https://doi.org/10.1140/epjd/s10053-023-00795-2

The rapid development of quantum computing has led to increasing interest in quantum algorithms for a variety of different applications. Quantum walks have also experienced a surge in interest due to their potential use in quantum algorithms. Using t... Read More about Cycle discrete-time quantum walks on a noisy quantum computer.

A thermodynamic approach to optimization in complex quantum systems (2024)
Journal Article
Imparato, A., Chancellor, N., & De Chiara, G. (2024). A thermodynamic approach to optimization in complex quantum systems. Quantum Science and Technology, 9(2), Article 025011. https://doi.org/10.1088/2058-9565/ad26b3

We consider the problem of finding the energy minimum of a complex quantum Hamiltonian by employing a non-Markovian bath prepared in a low energy state. The energy minimization problem is thus turned into a thermodynamic cooling protocol in which we... Read More about A thermodynamic approach to optimization in complex quantum systems.

Graphical structures for design and verification of quantum error correction (2023)
Journal Article
Chancellor, N., Kissinger, A., Zohren, S., Roffe, J., & Horsman, D. (2023). Graphical structures for design and verification of quantum error correction. Quantum Science and Technology, 8(4), Article 045028. https://doi.org/10.1088/2058-9565/acf157

We introduce a high-level graphical framework for designing and analysing quantum error correcting codes, centred on what we term the coherent parity check (CPC). The graphical formulation is based on the diagrammatic tools of the ZX-calculus of quan... Read More about Graphical structures for design and verification of quantum error correction.

Using copies can improve precision in continuous-time quantum computing (2023)
Journal Article
Bennett, J., Callison, A., O’Leary, T., West, M., Chancellor, N., & Kendon, V. (2023). Using copies can improve precision in continuous-time quantum computing. Quantum Science and Technology, 8(3), Article 035031. https://doi.org/10.1088/2058-9565/acdcb5

In the quantum optimisation setting, we build on a scheme introduced by Young et al (2013 Phys. Rev. A 88 062314), where physical qubits in multiple copies of a problem encoded into an Ising spin Hamiltonian are linked together to increase the logica... Read More about Using copies can improve precision in continuous-time quantum computing.

Comparing the hardness of MAX 2-SAT problem instances for quantum and classical algorithms (2023)
Journal Article
Mirkarimi, P., Callison, A., Light, L., Chancellor, N., & Kendon, V. (2023). Comparing the hardness of MAX 2-SAT problem instances for quantum and classical algorithms. Physical Review Research, 5(2), https://doi.org/10.1103/physrevresearch.5.023151

An algorithm for a particular problem may find some instances of the problem easier and others harder to solve, even for a fixed input size. We numerically analyze the relative hardness of MAX 2-SAT problem instances for various continuous-time quant... Read More about Comparing the hardness of MAX 2-SAT problem instances for quantum and classical algorithms.

NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems (2023)
Journal Article
Au-Yeung, R., Chancellor, N., & Halffmann, P. (2023). NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems. Quantum Science and Technology, 2, Article 1128576. https://doi.org/10.3389/frqst.2023.1128576

In the last decade, public and industrial research funding has moved quantum computing from the early promises of Shor’s algorithm through experiments to the era of noisy intermediate scale quantum devices (NISQ) for solving real-world problems. It i... Read More about NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems.