QuOpaL Begins

A new project on Quantum Optimisation and Machine Learning is now underway. Based at the University of Oxford, it's a joint endeavour between the University, Nokia and Lockheed Martin. The aim of the project is to understand the potential for quantum technology to enhance optimisation and machine learning tasks - these are some of the hardest and most important applications in computer science today.

Welcome to Stefan Zohren!

We're pleased to annouce that Dr Stefan Zohren will be joining the project. Stefan's background includes research in both mathematical statistics/probability and in theoretical physics. He'll join the group led by Prof. Simon Benjamin, part of the Oxford Quantum community which includes over 200 scientists. Stefan will also engage with the Machine Learning Research group led by Prof. Steve Roberts.


Nokia Technologies develops and licenses cutting-edge innovations that are powering the next revolution in computing and mobility: the “programmable world” where intelligent connections bring millions of everyday objects online and create exciting new possibilities. [...more]


The University has an internationally leading role in the worldwide effort to translate quantum science into quantum technology, and QuOpaL will form a vital new component in that effort. The project leader is Simon Benjamin, Professor of Quantum Technologies. [...more]

Lockheed Martin

For full details on Lockheed Martin's involvement, please check back to this site soon. Lockheed Martin's assets include a D-Wave 512-qubit device which can be made available to the project.

Project Details

Image © VLADGRIN/shutterstock

Machine learning refers to a variety of applications where computers figure out 'for themselves' how to perform data analysis, modelling and inference: tasks range from image and speech recognition through to language translation and even genome analysis. Optimisation involves finding the best solution to a problem from a set of alternatives. Generally these areas are regarded as hard for conventional computers, but they are also extremely important: advances in machine learning and optimisation could greatly increase the range of things that computers can do for us. For example, it may allow computers to be smarter at helping people and companies to manage the ever increasing torrent of information flowing from online systems of all kinds (e.g. smartphones). It is believed that harnessing quantum effects can lead to machines that are fundamentally better at machine learning and optimisation, thus unlocking this potential.

Quantum information processing is a field of research and development that hopes to harness the deepest phenomena in physics in order to create whole new kinds of technology. Various approaches are being taken, all of which are of interest to the QuOpaL project. One particularly interesting approach is adiabatic quantum optimisation (and the closely related phenomenon of quantum annealing). Here, a system is initialised to a simple state and then the conditions are slowly ('adiabatically') changed to reach a complex final state that describes the solution to a computational problem of interest. Many believe that this approach is the best way to start using quantum effects for accelerated machine learning -- whether or not this is true is a key topic of interest to the QuOpaL project!

More details

Nokia Technologies: Through Nokia Technologies, Nokia will invest in the further development of its industry-leading innovation portfolio. This will include expanding our successful IP licensing program, helping other companies and organizations benefit from our breakthrough innovations, and exploring new technologies for use in potential future products and services.

Oxford University: The University has one of the world's largest communities of quantum science researchers, currently spanning 6 departments, about 40 research teams and over 200 individuals. The University's research ranges from theory to experiment, and from the foundational to the very applied, forming an exceptionally vibrant research environment.


Contact Us

We are based in Oxford's Materials Department at OX1 3PH. To find out more about the project click the envelope button below.