Random point sources for quantum measurement and sensing

About the project

Quantum measurements often produce sparse, noisy observations from underlying sources or fields. This project develops mathematical methods for quantum measurement and sensing using random point sources, point processes and random measures, asking what source information can be recovered from realistic measurements and how noise and limited resolution affect that recovery.

Quantum measurements often provide indirect observations of an underlying source or field. Photon detections, interferometric measurements and spatial intensity data may be sparse, noisy and resolution limited, making recovery of the underlying physical structure an inverse problem.

This project will develop mathematical methods for quantum measurement and sensing based on random point sources, point processes and random measures. It will investigate how source configurations and their statistical properties are transformed by measurement, which features remain identifiable, and how uncertainty, correlations and non-Gaussian structure appear in observable data. Particular attention will be given to ambiguity, resolution, detector noise and restricted observation, leading to quantitative limits on source recovery, estimation and discrimination.

The project will use examples from quantum optics and quantum sensing, including photon counting, imaging and interferometric measurement, while remaining primarily mathematical and computational. It builds on Clark’s Random Point Sources: A Mathematical Theory of Point-Source Recovery (Springer, 2026), together with Field Theory for Point Processes (Birkhäuser) and Information and Inference for Point Processes (Springer).

The intended outcome is a rigorous theory of inverse problems for stochastic point sources under quantum measurement, with potential applications to quantum sensing, imaging, photodetection and measurement design.

Potential supervisors

• Potential supervisors: Lead supervisor DC Dr Daniel Clark FRAeS, FIET, CMath FIMA, CStat, SFHEA, SMIEEE Professor

Lead supervisor

• Lead supervisor: DC Dr Daniel Clark FRAeS, FIET, CMath FIMA, CStat, SFHEA, SMIEEE Professor

Dr Daniel Clark FRAeS, FIET, CMath FIMA, CStat, SFHEA, SMIEEE

• Dr Daniel Clark FRAeS, FIET, CMath FIMA, CStat, SFHEA, SMIEEE: Professor

Entry requirements

You must have an undergraduate degree (at least UK 2:1 honours degree) or its international equivalent .

Fees and funding

For candidates looking to complete a PhD or EngD full-time we offer an enhanced tax-free stipend of up to £30,000 per year, along with a substantial budget for research, travel, and centre activities.

CISDnS is committed to promoting equality, diversity and inclusivity. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break or are transitioning into a new role. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance.

We are pleased to announce that for 2027/28 entry, specific Centres for Doctoral Training (CDTs) at the University of Southampton have been selected to be part of a pilot programme of funding for UK doctoral candidates launched by the Department for Science, Innovation and Technology (DSIT) and UK Research and Innovation (UKRI). Now managed by the Department for Digital, Culture Media and Sport (DCMS), the funding is delivered through a strand of government’s new TechFirst skills programme. TechFirst will fund nationally, a stipend uplift for at least 500 domestic (UK only) doctoral students in priority technology areas over the next four years, strengthening the UK’s innovation pipeline and building a more inclusive, resilient and high-impact research ecosystem.

How to apply

Apply now

Please apply via the online portal and select:

Applications should include:

• Academic year: 2027/28
• If you will be full time or part time
• Faculty: Engineering and Physical Sciences
• Search for PhD Quantum Tech Eng
• Select either PhD or EngD – if you are unsure, select PhD
• Add the name of the supervisor in section 2 of the application.
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date

Faculty of Engineering and Physical Sciences

For questions about applying, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk) .

Project leader

For an initial conversation, email Dr Daniel Clark (daniel.clark@soton.ac.uk).

Research areas