[31/03/2022] Elham Kashefi, Professor of Quantum Computing at the School of Informatics at the University of Edinburgh and senior science lead on the UK Quantum Computing and Simulation Hub is part of the consortium that aims to build a system capable of controlling hundreds of qubits simultaneously across different types of quantum hardware. The project paves the way for quantum computers to reach their full potential and is expected to transform industries such as materials development, drug discovery, and finance. Image The consortium is led by Riverlane, which is building the operating system for error corrected quantum computers and funded by Innovate UK. The £6.8M project will apply machine learning techniques to find fast, automated, and scalable ways to calibrate quantum computers. For quantum computers to be used practically, a large number quantum bits (qubits), need to be controlled with absolute precision and without errors. This is an extremely difficult task due to the fragility of qubits. Even the smallest changes in the environment can cause qubits to collapse and lose information. As a result, quantum computers require constant supervision by highly skilled physicists. Calibration is currently inefficient and time consuming. The cost, time, and effort involved in this process are currently a major bottleneck to progressing quantum computing technology. Deltaflow Control, a powerful control system being developed by Riverlane, will manipulate hundreds of qubits simultaneously and will be portable across multiple types of quantum hardware. Artificial Intelligence specialists Mind Foundry will apply machine learning techniques to find optimal ways to calibrate qubits. Auto-calibration will enable faster, more predictable measurements. Users can focus on running useful experiments and get more out of their qubits, instead of spending time and energy on setting qubits up and keeping them from collapsing. The consortium includes world-leading quantum hardware suppliers Oxford Ionics and SEEQC each representing different types of quantum hardware: trapped ion and superconducting qubits. The National Physical Laboratory (NPL) and the University of Edinburgh will set the standards for measurement, ensuring validity and precision. In order to demonstrate that the automated calibration framework can be applied to wider quantum technologies, NPL will also adapt it for NPL’s single electron pump systems, which are used for the generation of accurate quantized electric currents. Over the last decade verification has been developed as a framework to certify a correct outcome in a passive way. In this project we have the ambition and the opportunity to dig deeper not only to perform the health checks at the application layer, but also to mitigate noise at the lowest hardware layer to cure outcome based on the results of the test obtained through verification in a dynamic way. This way we will bridge between today's available NISQ devices and the future emerging fault tolerant computers while exploiting each physical qubit's computational capacities in the most optimal way. Elham KashefiProfessor of Quantum Computing, School of Informatics, the University of Edinburgh The Quantum Informatics group, led by Prof Elham Kashefi, is the largest research group in the UK focusing on quantum software. The group specialise in the structure, behaviour, and interactions of quantum technology. Their expertise in control systems and algorithms help businesses to express, verify, and secure quantum computing applications. Their software capability expands quantum simulation, algorithms, optimisation, machine learning, cyber security, programming languages, benchmarking, testing, and verification techniques. The group plays a leading role in the UK Quantum Computing programme and is strongly integrated into UK national programmes through the QT Hubs, Innovate UK, and EPSRC, as well as EU and US funded flagship projects. Related links Informatics research group - Quantum Informatics Quantum Computing and Simulation Hub This article was published on 2024-03-18
