Our Expertise
Our research is organised around two major pillars: Hardware & Experimental and Theory & Algorithms, supported by growth/fabrication infrastructure and application/use-case development.
On
Experimental Research & Hardware
We leverage world-class capabilities in semiconductor and photonic hardware:
- Semiconductor quantum nano-photonics and integration (for example led by Prof. Luke Wilson)
- Crystal growth, molecular beam epitaxy, epitaxy of novel semiconductors and quantum material systems (led by Dr Jon Heffernan)
- Nanostructures and 2D materials for quantum photonics (Prof. Alexander Tartakovskii)
- Single-photon avalanche diodes and quantum detector technologies (Dr Chee Hing Tan)
- Fabrication, lithography, patterning, device physics, photonic structures for scalable quantum hardware.
- Growth/fabrication infrastructure: e.g., the “National Epitaxy Facility” (under supervision of Jon Heffernan) and nanofabrication labs in Sheffield.
Theory & Algorithms
On the theory, software and algorithmic front we cover:
- Quantum computing, quantum machine learning (Prof. Oleksandr Kyriienko – Director of SQC)
- Quantum communication, metrology and imaging (Prof. Pieter Kok)
- Quantum error-correction, quantum algorithms for differential equations, scientific computing workflows (Dr Yingkai Ouyang)
- Practical use-cases: sensing/imaging, communications, data-driven quantum machine-learning, hybrid quantum–classical systems.
Infrastructure & Growth Capabilities
- Growth facility: crystal growth, MBE, MOVPE for semiconductor/photonic quantum materials.
- Nanofabrication, lithography, patterning: device fabrication for photonic integrated circuits, micro/nano-optics, quantum sensors and detectors.
- Photonic integration and packaging: ability to move from device to system.
- Collaborating with internal UoS engineering, electronics and photonics groups for system integration and scale-up.
Application Domains & Use-Cases
- Quantum photonics for imaging, sensing, communications.
- Quantum computing and algorithms for simulation, optimisation, machine learning.
- Material-driven quantum technologies: spin-photon interfaces, single‐photon sources/detectors, integrated photonic quantum circuits.
- Industry-driven use-cases: aerospace, defence, energy, pharmaceuticals, communications, advanced manufacturing.