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Details of Grant 

EPSRC Reference: EP/V002732/1
Title: Noise-avoidance and Simulation in Quantum Information Technologies
Principal Investigator: Jennings, Dr D
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Physics and Astronomy
Organisation: University of Leeds
Scheme: New Investigator Award
Starts: 01 November 2020 Ends: 31 October 2023 Value (£): 401,471
EPSRC Research Topic Classifications:
Quantum Optics & Information
EPSRC Industrial Sector Classifications:
R&D
Related Grants:
Panel History:
Panel DatePanel NameOutcome
10 Jun 2020 EPSRC Physical Sciences - June 2020 Announced
Summary on Grant Application Form
Quantum Technologies offer advances that will impact the 21st Century in fundamental ways. The past 2 years have seen the emergence of a "quantum space race" with quantum computing entering a phase called the Noisy Intermediate-Scale Quantum (NISQ) era, with an explosion of interest from prominent industrial directions (e.g. Google & IBM) and countries around the world (USA: approx. $200 million/year & $1.2bn investment for quantum technologies. China: $1 billion for the Hefei labs). Work is progressing quickly, and in October a key milestone was claimed by Google: the first computation on a quantum device that dramatically outperformed the capabilities of the world's largest supercomputer. These advances are more than just improved hardware efficiency, instead a quantum computer corresponds to a fundamental re-thinking of what computing means. A claim is that a quantum computer will be to a supercomputer what a supercomputer is to an abacus, and as such its transformative potential could profoundly shape our world. There is a broad spectrum of applications of quantum technologies that could address some of our world's biggest problems. A prominent example is the Haber-Bosch process for fertiliser production which has an efficiency of only 60%, and responsible for about 3% of global energy consumption. Nature, however, achieves close to 100% efficiency for the same task. A core reason we cannot mimic Nature's method is that the molecule employed is beyond the simulation abilities of supercomputers. However this is precisely the kind of strongly interacting complex system that quantum computers can simulate exponentially faster. This is just one potential application but there are many others such as currently intractable chemistry simulations, novel drug-discovery in medicine, or the development of new superconducting materials.

A fundamental challenge now is how to design quantum devices for the NISQ era and optimally make use of such quantum systems in the face of noise & hardware limitations (e.g. limited connectivity of device components). This theory research programme will develop novel protocols for medium term quantum devices that exploit precious quantum resources in noisy environments as optimally as possible with the ability to naturally incorporate specific hardware limitations. The core methodology takes recent methods developed for the thermodynamics of quantum systems and applies them in novel ways to quantum technology goals. It will do this firstly by using harmonic analysis for the performance benchmarking of quantum devices. This is important as existing quantum computers are very noisy and a sharp diagnosis is essential. Secondly, it will use recent statistical mechanics tools to quantify fragile quantum components (called 'magic states') that are vital for full-scale quantum computing. This is important because current magic state demands are extremely high and so any advances in this line would greatly speed up progress to a full-scale quantum computer. The programme will also use a very recent variant of the 2nd Law of Thermodynamics to develop formulations of quantum error-correction (another key component of a robust quantum computer) that are explicitly tailored to experimental testing. Finally, it will use the insights gained in the early phase of the programme to develop new classical algorithms (for ordinary, non-quantum computers). These classical algorithms will contribute to our ability to simulate quantum systems (e.g. to estimate the computational regime where quantum computers become useful) and also connect with existing work on drug-discovery algorithms. It will do so by exploiting recent extensions of quantum statistical mechanics. The methodology is well-suited as it provides a modern parallel to the highly successful application of traditional statistical mechanics to classical computing (e.g. Monte Carlo methods) while also engaging hardware challenges.
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Organisation Website: http://www.leeds.ac.uk