QuEST aims to bring together researchers from across Imperial College London to translate discoveries in Quantum science into transformative quantum technologies. 

In February 2023, we launched a call to provide funding for short-term (2–3 month) research projects. The aim of this funding call is to enable the development of new cross-disciplinary collaborations and research directions in Quantum Engineering Science and Technology at Imperial College London.

The projects below were selected to receive funding and will run between 1 April and 30 June 2023.


Accordion Widget

Quantum Annealing for Simulation Optimisation with Applications in Climate Systems and Wastewater-driven Energy Facilities

Project leads: Dr Po-Heng (Henry) Lee, Department of Civil and Environmental Engineering
Dr Mansour T.A. Sharabiani, School of Public Health

Many real-world systems - including climate systems and wastewater-to-energy production using anaerobic digesters in wastewater treatment (WWT) - are far too complex for closed-form mathematical expressions to adequately describe, necessitating time-consuming, computer simulations to analyse and predict their behaviour. Rather than limited - and incomplete - scenario analysis of classical simulated systems, we propose to take an optimisation approach (even if optimisation is not the primary objective), to identify the set of initial conditions and/or model parameter values that predict extreme outcomes (positive or negative) accurately. In this regard, we seek to apply quantum annealing algorithms for speeding up such computational-demanding tasks.

In previous research, we introduced QuAnCO (Quantum Annealing Continuous Optimisation), an adaptation of Trust Region Newton (TRN), which enables the use of Ising solvers such as D-Wave’s quantum annealers for solving the Trust Region (TR) subproblem. However, the original QuAnCO algorithm is limited to unconstrained, continuous optimisation of smooth - i.e., twice differentiable - objective functions. Our goal is to extend QuAnCO to solve optimisation problems with 1) equality and inequality constraints, 2) a mix of continuous and discrete parameters, and/or 3) objective functions which lack the second (or even the first) derivative(s). Such extensions would allow us to solve a wider range of optimisation problems, such as simulating the climate and WWT systems we proposed. This project could surpass the classical quality of sensitivity analyses and ultimately lead to more effective quantum solutions for renewable energy and environmental sustainability.

Learn more about the Quantum Annealing for Simulation Optimisation project.


Quantum Coherent Microwave‐to‐Optical Transduction

Project leads: Dr Michael Vanner, Department of Physics
Professor Malcolm Connolly, Department of Physics
Professor Mark Oxborrow, Department of Materials

Quantum computing and communication has enormous potential to improve how we process and transmit information. Such improvements will enable advanced calculations, such as stimulating new approaches to drug discovery, provide new forms of ultra‐secure communication that can form the backbone of future quantum networks, and enable breakthroughs in fundamental physics. One of the leading platforms for quantum computation, now also hotly pursued by high‐technology giants, employs microwave photons in superconducting circuits that need to be operated close to absolute zero in temperature. Networking these quantum processors over large distances, and scaling beyond current cryogenic capacity limitations, requires new methods to coherently connect these superconducting quantum nodes via room‐temperature optical fibre links.

This seed project will experimentally explore how to efficiently bridge the microwave and optical telecommunications domains via hybrid quantum system development. The project will be pursued by an interdisciplinary team spanning the Physics and Materials departments including Michael R. Vanner, PI of the Quantum Measurement Lab and an expert in quantum optics and quantum optomechanics, Malcolm R. Connolly, PI of a superconducting circuits team studying electron behaviour in nanomaterials, and Mark Oxborrow, PI of a team studying functional microwave materials. By combining their complementary skill sets, this QuEST collaboration aims to overcome existing challenges in this highly sought-after direction. 

Quantum Data Acquisition System

Project leads: Dr Ioannis Xiotidis, Department of Physics
Professor Wayne Luk, Department of Computing

Exploring in-depth the origins of the Universe and its mechanisms becomes increasingly more complicated and time-consuming. Existing and future particle physics experiments need to process large amounts of data obtained at rates which are unprecedented, leading to extensive computational operations and increasing carbon footprint. Reducing those factors, as well as performing efficient selection of the obtained data are the most important ingredients towards future discoveries. An upcoming technology that can be a decisive factor in reaching the required precision for discoveries in the most efficient way is quantum computers. However, quantum computers will not completely replace their classical counterparts as they are not necessarily outperforming classical computers in all challenges that are faced. For this reason, the Quantum Data Acquisition System (qDAQ) project is exploring hybrid hardware environments within the scope of high-energy physics experiments that will allow the coexistence of both technologies to maximize the gain.

As quantum computers are still experimental devices, developing a reliable method of retrieving and sending data to it, with the constraints that are present in high energy physics experiments (e.g. low latency, high bandwidth, algorithm implementations etc.), is a daunting task. Since the problems faced are complicated and multi-dimensional, building new cohorts across different fields of science is needed. For this reason, qDAQ is a multidisciplinary research group made up of researchers from the Physics and Computing departments of Imperial College.

The group currently consists of the following members:

Dr. Ioannis Xiotidis (Physics) - main Project Investigator with hardware and software experience in Data Acquisition Systems for leading experiments like ATLAS (CERN) and DUNE (Fermilab),

Prof. Wayne Luk (Computing) - main Project Investigator with experience in theory and practice of customising computations to meet application and implementation needs,

Prof. Alexander Tapper (Physics) - co-Project Investigator - particle physicist who led the real time data selection project for the international CMS collaboration at CERN,

Dr Patrick Dunne (Physics) - co-Project Investigator has extensive experience in High Energy Physics DAQ system implementations and hardware accelerating computing for big data problems,

Dr Andrew Rose (Physics) - co-Project Investigator - particle physicist by training; digital-electronics, firmware and high-performance-software engineer by profession.

Simon Williams (Physics) - Research Assistant funded by QuEST with experience in quantum simulation, addressing problems in particle theory and phenomenology,

Zhiqiang Que (Computing) - Research Assistant funded by QuEST with experience in the theory and practice of FPGA acceleration of demanding applications.