QIL 2019 consisted of five working groups lead by representatives from Microsoft, Siemens, GSK, and Jisc.
The group, successfully led by Microsoft representatives, Chris Grenade and Francis Tibble, explored ways to teach quantum computing through the recently developed quantum-focused programming language, Q#. Academics, Tony Short and Paul Skrzypczyk, joined the conversation sharing invaluable ideas and perspective from their experience as University of Bristol lecturers. On the first day of QIL, the group discussed how existing educational tools can be improved and compiled a list of potential topics for new quantum katas. On the second day this list was refined, and the topics of Non-local games and Hamiltonian simulation were selected for further investigation. Options to involve QE CDT students in the development of the katas and to trial them amongst University of Bristol students were also discussed. The group wouldn’t have happened without the overseas support of Mariia Mykhailova who suggested the topic of discussion.
The Siemens group focused on quantum algorithms and touched upon three main problems: scheduling problem, image segmentation and general machine learning.
The scheduling problem involved the issue of efficiently allocating resources or people for a particular task, e.g. fair assignment of nurses to different shifts in a hospital. The main take away message was to apply QSDP (Quantum Speed-ups for Semidefinite Programming) to the problem, to use a QAOA (Quantum Approximate Optimization Algorithm) instead of adiabatic methods and to retrieve partial information instead of reading out.
Image segmentation related to identifying a pattern in an image and highlighting it, e.g. identify a vessel from a X-ray image. The main outcomes were to focus on specific architecture / hardware in order to get an advantage and to tailor VQE (Variational-Quantum-Eigensolver) to the problem in case.
And finally, the group had a general discussion on machine learning. Apart from elucidating some general issues on the topic, it was brought up the idea of adding a random quantum convolution layer in the neural network, which could bring about some overall improvement.
The Jisc workstream was focussed on practical steps that might help researchers to engage with the National Dark Fibre Facility (Aurora 3, formerly the National Dark Fibre Infrastructure Service), facilitating industry engagement, and more generally demystifying and charting a path towards the “quantum Internet”. This group included representatives from Gemalto, Airbus, NPL and Fraunhofer CAP. The group identified three key themes:
• Industry are hesitant to invest in new technologies such as Quantum Key Distribution (QKD) without having a clear understanding of the value proposition;
• academics working in quantum applications need more information on the infrastructure available to support their research. At the same time, the NDFF team and Jisc need to know how the NDFF can best evolve to meet anticipated future needs from academia and industry;
• policymakers, business and institutional leaders need to understand what quantum technologies will mean for them, and when, in order to plan investments and other initiatives – beyond the hyperbole that tends to accompany media coverage.
Each of these was explored in some detail and the group presented its findings in the closing QIL plenary. These also resulted in three future projects: Supporting industry engagement with NDFF, characterising the NDFF for quantum applications and writing a white paper “Towards the Quantum Internet”.
The quantum imaging group was led by GSK, and the aim of the group was to identify key gaps in imaging technologies used within drug discovery that might be tackled by applications in quantum imaging and metrology. This resulted in several research projects which will be carried out by Bristol University in collaboration with GSK. Applications of the proposed projects range from improving and expanding the sensitivity of Raman spectroscopy for detecting drugs in cells and tissues, to improving performance and sample viability in fluorescence and absorption microscopy.
At this year's event a new group format was trialled, which was not led by a company focusing on existing industrial problems. Instead, the group consisted of academic and industrial representatives with interest in quantum simulations, with a view to forming a startup company. On Day 1, the group discussed which problems are computational bottlenecks for classical chemistry and how quantum simulation techniques might be applied to improve results. Solutions proposed included protein folding for applications such as treatment of Alzheimer’s disease, and simulation of molecular dynamics for drug discovery.
On Day 2, the group turned their attention instead to the process of starting and running a business. The discussion ranged from raising funds, customer identification, to developing a minimal viable product, all within the context of the quantum simulation services decided upon during Day 1.