Hybrid Quantum Energy Landscape Computing

Lead Research Organisation: Durham University
Department Name: Physics


At its most fundamental level, computation relies on being able to use physical components to represent and manipulate abstract information. Representation of information can be accomplished in two ways:

(1) Digital computing, in which all information is represented in a discrete way, ones and zeros.
(2) Analog computing, in which some of the information is represented as continuous variables.

Classical computing is currently dominated by digital technology, e.g. desktops, laptops, and smart phones are all governed by digital technology. Within living memory, hybrid computation has dominated, calculations where performed by analog slide rules, supplemented by digital-like pen and paper calculations. Algorithms based on emulating natural (analog) processes are powerful computational tools. An example would be simulated annealing, where solutions to optimization problems are found by simulating a cooling process. A more sophisticated algorithm such as parallel tempering, which involves 'swapping' systems at different temperatures, is even more powerful than simulated annealing and has made it obsolete.

Quantum computing:
(1) Uses the quantum nature of the world we live in to produce more powerful computation.
(2) Has proven to be better at solving some problems than any non-quantum approach.
(3) Quantum computing devices are just getting to the stage of being useful. Therefore, the design of algorithms which can get the most performance out of small and imperfect devices is imperative.

Quantum annealing:
(1) Is a quantum analogue of simulated annealing, which uses quantum mechanics to aid calculations.
(2) Quantum annealing already has experimental implementations, which are commercially available, e.g. devices produced by D-Wave systems Inc. have been purchased for use by Google, NASA, and Lockheed Martin.
(3) Quantum annealers are especially suited to optimisation and machine learning problems, such as the travelling salesperson problem.

My project:
(1) I will develop protocols, which are hybrids between analog (like continuous-time quantum computation which harness fundamental laws of physics) and classical digital computation, to make computations more powerful.
(2) The algorithms that I will develop will run on hybrid part-classical, part-quantum hardware.
(3) I will also develop algorithms based on continuous-time quantum computing methods such as quantum random walks.
(4) Additionally, I will develop algorithms based on simulations of analog quantum systems. They can be run either on digital quantum computers, based on discrete 'gates', or on classical machines. I will develop techniques, which work on many quantum computing platforms and will be useful regardless of relative rates of development.

The project will take a three-pronged approach:
(1) I will construct more sophisticated hybrid algorithms, for instance, analogues of parallel tempering rather than simulated annealing.
(2) Then, I will provide proof-of-principle that these algorithms have an advantage over current methods.
(3) Finally, I will develop implementations on real devices and case studies for real-world industrial problems.

Planned Impact

This project will improve solution methods for a wide range of optimisation and machine learning problems through smarter algorithms.

Published work (see references in case for support) has already been done to show that the quantum optimization and machine learning methods I will develop are relevant to finance, microbiology, computer science, aerospace, communications, schedule optimisation, neural networks, and many other fields.

Impact on end users and technology developers:

1) Companies, researchers, and also government can benefit from better optimisation. For example, more efficient transport routes will guarantee energy savings, while more efficiently scheduling might optimise the use of valuable equipment.

2) By developing more efficient algorithms, this project can bridge the gap between quantum computing as an academic research topic and it becoming a commercially viable industrial tool. With the algorithms produced in this project, developers of hardware will thus be able to commercialise their hardware sooner.

3) This project will influence technology development as it makes the controls more compatible with algorithm design. D-Wave Systems Inc. have begun to incorporate some of the ideas on which this project is based. They are adding controls to their quantum annealing devices which are very similar to ones I proposed in a single authored paper [P.2, my publications]. This is a concrete demonstration of my ability to influence technology development.

Robustness of impact:

1) The project will have a positive impact regardless of the rate of advance in different quantum computing technologies, because my algorithms will run on both gate-based and continuous time platforms ranging from highly dissipative to fully coherent.

2) Classical quantum-inspired algorithms which I will develop are still useful even if experimental quantum computing fails to significantly outperform classical methods.

National impact:

1) This project allows the UK to play a leading role in quantum optimisation and machine learning through software and application development. This project is much less expensive than developing an experimental platform, thus providing excellent value-for-money.

2) UK industry and government will benefit from the results of improved quantum computing methods, and an excellent algorithmic research program will attract more applied quantum computing research to the UK.

3) I will train a PDRA (who is already an expert in operational research) in quantum optimization algorithms. This PDRA will act as an ambassador between technology developers and industry in the UK.


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Abel S (2021) Quantum computing for quantum tunneling in Physical Review D

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Callison A (2019) Finding spin glass ground states using quantum walks in New Journal of Physics

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Chancellor N (2020) Fluctuation-guided search in quantum annealing in Physical Review A

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Chancellor N (2021) Experimental test of search range in quantum annealing in Physical Review A

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Chancellor N (2019) Domain wall encoding of discrete variables for quantum annealing and QAOA in Quantum Science and Technology

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Chen J (2021) Performance of Domain-Wall Encoding for Quantum Annealing in IEEE Transactions on Quantum Engineering

Description I can now report that there is substantial progress on understanding how continuous-time quantum computing solves problems, and we have published results in this area (see previous), I would consider this goal to now have been met. This work has now been cited in a perspective paper by the top researchers in my field, who highlight two strands of research I pioneered as promising directions for the field. These are reverse annealing and the understanding gained from taking a quantum walk related perspective to quantum annealing. I have also developed a methodology for quantum use cases (and an example related to the problem of ambulance dispatch) which has been publicly released on a repository and is in the process of being submitted for publication. I have also developed new techniques for mapping problems to quantum annealers and unpublished research demonstrates a large performance gain.
Exploitation Route An improved understanding of the underlying mechanisms of quantum optimization could greatly improve the development of algorithms for quantum computing. Additionally, the case studies will help inform which problems are most appropriate for early quantum machines, and more importantly how this decision can be made by others. Most importantly, the understanding we have added has demonstrated that certain kinds of protocols are always helpful in solving problems, an insight which informs how they can be used. As discussed in narrative impacts, the reverse annealing techniques I helped to pioneer are already in use. I further suspect that when the work demonstrating improved mapping techniques is published it is likely to be adapted into quantum computing software, including those developed by industry.
Sectors Digital/Communication/Information Technologies (including Software),Other

Description I have built on the ideas of reverse annealing which has now been included as a protocol in the quantum annealing systems produced by D-Wave Systems Inc. (which sell for about 10 million US dollars) and were first published in a a single author paper by me which was written before my current grant was awarded. Since the project has started, I have done some proof-of-principle experiments to show that these techniques work, these findings were presented at AQC 2018 where I was an invited speaker, and were seen by representatives of D-Wave Systems Inc. my work on reverse annealing continues to influence quantum annealing protocols.
First Year Of Impact 2015
Sector Digital/Communication/Information Technologies (including Software)
Description CCP-QC: Collaborative Computational Project - Quantum Computing
Amount £163,421 (GBP)
Funding ID EP/T026715/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 05/2020 
End 05/2025
Description EPSRC Hub in Quantum Computing and Simulation
Amount £23,960,281 (GBP)
Funding ID EP/T001062/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 12/2019 
End 11/2024
Description First encounters with quantum computing: can games teach quantum reasoning?
Amount £19,836 (GBP)
Funding ID BB/T018666/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 01/2020 
End 03/2020
Title Fluctuation guided search in quantum annealing [dataset and code] 
Description data and code associated with https://arxiv.org/abs/2009.06335 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
Impact Open access data associated with the paper to allow potential re-analysis by others. No impacts yet, but recently published. 
URL http://collections.durham.ac.uk/files/r1c534fn95w
Title Performance of Domain-Wall Encoding for Quantum Annealing [dataset] 
Description Deposit contains dataset and Python code. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
Impact No notable impacts so far, but these data provide a valuable benchmarks between both encoding methods and quantum processors so impacts may occur in the future. 
URL http://collections.durham.ac.uk/files/r11j92g748d
Title Search range in experimental quantum annealing [dataset] 
Description This dataset contains experimental quantum annealing data from arXiv:2008.11054, Search Range in Experimental Quantum Annealing, by Nicholas Chancellor and Viv Kendon. It also contains the code used to produce and analyse the data. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
Impact This dataset allows the results to be reproducible and will allow tests of open quantum systems models when reanalyzed by my group and potentially others 
URL http://collections.durham.ac.uk/files/r2kp78gg42f
Description DLR 
Organisation German Aerospace Centre (DLR)
Country Germany 
Sector Public 
PI Contribution I have been working with a researcher from DLR to experimentally study a new method of encoding problems on quantum annealers, I have contributed my time and expertise.
Collaborator Contribution The DLR researcher has contributed his expertise relating to the problem and applying quantum annealing to real engineering problems as well as access to quantum annealing hardware. The value estimate is based on commercial rates to access quantum annealing hardware.
Impact A paper is forthcoming, but has not been published yet
Start Year 2020
Description Quantum Computing Inc. 
Organisation Quantum Computing Inc
Country United States 
Sector Private 
PI Contribution A company where I sit on the advisory board and engage in research with. There are currently discussions of a secondment in the future and them providing me with access to advanced quantum computing hardware. I have signed confidentiality agreements in my role on their advisory board.
Collaborator Contribution They have access to advanced quantum computing hardware which I should be able to use for research.
Impact None yet
Start Year 2020
Description University of Zagreb 
Organisation University of Zagreb
Country Croatia 
Sector Academic/University 
PI Contribution I am working with researchers from the University of Zagreb in Croatia to understand how quantum Boltzmann machines (a type of neural network) could be used to study strongly correlated condensed matter systems.
Collaborator Contribution My partners provide a use case for quantum computing, which is very important for the goals of my fellowship.
Impact This collaboration has just started, so there are no direct outputs yet, however we are planning on developing funding proposals and potentially a case study.
Start Year 2018
Description Interview by Sophia Chen in Gizmodo 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact I was contacted and interviewed by Sophia when a new architecture of quantum annealer was announced by D-Wave Systems Inc. I was interviewed due to my expertise in the field, it mentions me by name and quotes me.
Year(s) Of Engagement Activity 2020
URL https://gizmodo.com/d-wave-s-new-quantum-computer-is-inscrutable-and-open-f-1845212754