Collaborative R&D

Building the UK’s quantum computing capabilities

The NQCC is working with partners across industry, government and the research community to solve technology challenges and realise the benefits of quantum computers for social and economic development. Through our SparQ programme we engage with research institutions, companies, and government organisations to explore the potential of emerging quantum computers for tackling real-world applications.

Proof of Concept projects in Quantum Computing 2024-25

Understanding the role of mid-circuit measurement in quantum algorithms for Computational Fluid Dynamics (CFD) simulations, towards demonstrating quantum advantage in aerodynamics

This project will assess the feasibility of quantum simulations of airfoil designs and vehicle aerodynamics on near-term quantum hardware. The work conducted in this partnership aims to deliver a roadmap towards powerful Computational Fluid Dynamics (CFD) simulations on quantum hardware for the aerospace industry.

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Proof of Concept Application of Quantum Optimisation in Planning of In-Field Sensor Networks for supporting Disaster Response Operations

The project is focused on exploring the optimal location and configuration of radio communication and sensing devices across an area of land to maximise usability, connectivity and sensor coverage.

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Investigating the application of Quantum Machine Learning (“QML”) to improve the early detection of cancer via the use of AI classification methods for liquid biopsies

The project is focused on the exploration of Quantum Machine Learning (QML) methods to improve and create novel faster and cheaper cancer diagnosis using liquid biopsies. The project aims to demonstrate a real world first step in clinical pathways towards exploring novel QML applications for multimodal approaches in healthcare.

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From batteries to windfarms: Quantum optimisation solutions for the renewable sector

This project aims to answer the question of whether quantum computers will be able to help with the emerging computational challenges of the renewable sector.

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QuantiCo – Quantum Computing for Corrosion

The project’s aim is to develop and implement the state-of-the-art molecular embedding methodologies, essential to explaining corrosion chemistry, critical to aerospace and energy sectors. The overall goal is to be able to determine accurate molecular energies, thereby predicting precise kinetic parameters for finite element models to explain the challenging ‘Oxygen reduction reaction’ on ‘Aluminium alloy’ surfaces, benefiting both industrial applications and academic research.

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Quantum Machine Learning for Fraud Detection in Credit Card Transactions

This project aims to investigate the use of Quantum Computing for enhancing anomaly detection in financial transactions, focusing on fraud detection and anti-money laundering. By leveraging quantum computing’s ability to analyse complex datasets and identify subtle patterns, the study aims to reduce false positives, improve operational efficiency, and provide robust solutions for regulatory compliance and market stability in the financial sector.

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Quantum Resource Estimation as a Pipeline for Polymer Simulation (QREPPS)

In this work programme, the consortium aims to use quantum resource estimation as a tool for assessing Quantum Phase Estimation (QPE) as a viable method for calculating ground-state energies of classically intractable polymers with high commercial value in the fields of energy, transport, and defence on early-stage fault-tolerant systems.

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Space-Hardened Quantum Error Correction for Orbital Computing

The project aims to develop Quantum Error Correction (QEC) methods specifically tailored for orbital computing. The project will focus on understanding and mitigating the impact of space radiation on entire quantum computing systems.

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Closure Optimisation for Road Network Maintenance

The project aims to leverage quantum computing to minimise disruptions caused by maintenance activities in transport networks. The study will focus on optimising the scheduling of maintenance actions to reduce the overall number of closures and/or the cost while increasing the work completed during each closure.

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Quantum Approach for Scalable Dynamic Flexible Job Shop Scheduling Platform

This project aims to leverage quantum computing to enhance efficient resource utilisation in manufacturing. It will focus on optimising the allocation of personnel, machinery, and materials across multiple projects, with the goal of reducing costs, energy consumption and carbon emissions.

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Quantum simulations for enhanced NMR in next-generation batteries

This study aims to provide guidance to the quantum resources required to perform NMR simulations for practical models of batteries on future quantum computers.

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Omics Insights with Quantum (OmIQ)

This collaboration aims to study the feasibility of employing quantum computing to better perform multimodal cancer data analysis.

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Highlight Call on Quantum Computing:

Proof of Concept projects 2022-23

Near-term quantum computing techniques to address operational healthcare use-cases

The project focussed on improving the efficiency of a variety of operational challenges in NHS healthcare provision.

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Data-driven reactivity prediction using computed quantum features for drug discovery

The project investigated a general approach where rich quantum-derived features can be used for downstream modelling without a significant understanding of reaction mechanisms.

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Quantum Monte Carlo radiation transport simulation

The project investigated the advantage offered by QC to make the runtime of Monte Carlo methods competitive with deterministic methods.

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Federated quantum machine learning for genomics data

The project investigated an FL solution implementation suitable for the NISQ hardware solutions with a particular focus on genomics datasets.

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Highlight Call on Quantum Computing:

Proof of Concept projects 2021-22

Automated control software to tune, stabilise and optimise qubits

The project investigated possible routes for creating an automated control software system to tune, stabilise and optimise qubits.

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Towards a quantum materials genome programme

The project paved the way for an accessible database of quantum tools for modelling key materials.

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Integrated photonics for ion trap quantum computing

The project explored the potential of thin-film lithium niobate as a future-proof material for photonics infrastructure in trapped-ion QC.

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Photonic quantum time-bin processing for image recognition

The project aimed to use software simulation of ORCA’s hardware environment to model image recognition problems on an ORCA PT-series system.

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Commercialising Quantum Technologies:

Feasibility Studies Call 2021-22

Realistic machine learning based ultra-fast simulator for semiconductor spin qubit devices

The project aimed to deliver an ultrafast simulator for semiconductor spin-qubit devices based on developments in classical M/L, quantum S/W and H/W.

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M-PIT: Miniature packaged ion traps

The project investigated to develop a high-performance, miniature and self-contained ion-trap system.

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INTERCOM: A high-performance ion-photon interface for multi-core trapped-ion QC

The project explored a device to enable quantum information to be transferred through photonic links between remote ion traps providing a scalable architecture.

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