Breakthrough promises secure quantum computing at home
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THE PROCESS ALLOWS A REMOTE USER (RIGHT) TO ACCESS A QUANTUM COMPUTER IN THE CLOUD (LEFT) WITH COMPLETE SECURITY. BY HELENE HAINZER. COPYRIGHT OXFORD UNIVERSITY PHYSICS.
view moreCREDIT: BY HELENE HAINZER. COPYRIGHT OXFORD UNIVERSITY PHYSICS.
The full power of next-generation quantum computing could soon be harnessed by millions of individuals and companies, thanks to a breakthrough by scientists at Oxford University Physics guaranteeing security and privacy. This advance promises to unlock the transformative potential of cloud-based quantum computing and is detailed in a new study published in the influential U.S. scientific journal Physical Review Letters.
Quantum computing is developing rapidly, paving the way for new applications which could transform services in many areas like healthcare and financial services. It works in a fundamentally different way to conventional computing and is potentially far more powerful. However, it currently requires controlled conditions to remain stable and there are concerns around data authenticity and the effectiveness of current security and encryption systems.
Several leading providers of cloud-based services, like Google, Amazon, and IBM, already separately offer some elements of quantum computing. Safeguarding the privacy and security of customer data is a vital precursor to scaling up and expending its use, and for the development of new applications as the technology advances. The new study by researchers at Oxford University Physics addresses these challenges.
“We have shown for the first time that quantum computing in the cloud can be accessed in a scalable, practical way which will also give people complete security and privacy of data, plus the ability to verify its authenticity,” said Professor David Lucas, who co-heads the Oxford University Physics research team and is lead scientist at the UK Quantum Computing and Simulation Hub, led from Oxford University Physics.
“Using blind quantum computing, clients can access remote quantum computers to process confidential data with secret algorithms and even verify the results are correct, without revealing any useful information. Realising this concept is a big step forward in both quantum computing and keeping our information safe online’’ said study lead Dr Peter Drmota, of Oxford University Physics.
The researchers created a system comprising a fibre network link between a quantum computing server and a simple device detecting photons, or particles of light, at an independent computer remotely accessing its cloud services. This allows so-called blind quantum computing over a network. Every computation incurs a correction which must be applied to all that follow and needs real-time information to comply with the algorithm. The researchers used a unique combination of quantum memory and photons to achieve this.
“Never in history have the issues surrounding privacy of data and code been more urgently debated than in the present era of cloud computing and artificial intelligence,” said Professor David Lucas. “As quantum computers become more capable, people will seek to use them with complete security and privacy over networks, and our new results mark a step change in capability in this respect.”
The results could ultimately lead to commercial development of devices to plug into laptops, to safeguard data when people are using quantum cloud computing services.
Researchers exploring quantum computing and technologies at Oxford University Physics have access to the state-of-the-art Beecroft laboratory facility, specially constructed to create stable and secure conditions including eliminating vibration.
Funding for the research came from the UK Quantum Computing and Simulation (QCS) Hub, with scientists from the UK National Quantum Computing Centre, the Paris-Sorbonne University, the University of Edinburgh, and the University of Maryland, collaborating on the work.
Read further detail on the study here:
The study ‘Verifiable blind quantum computing with trapped ions and single photons’ has been published in Physical Review Letters: http://doi.org/10.1103/PhysRevLett.132.150604
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Experiments on quantum computing in the Beecroft facility, Oxford University Physics.
Photo credit: David Nadlinger, Oxford University Physics.
NOTES TO EDITORS
About Oxford University Physics
Oxford University Physics is one of the largest physics departments in the world, top-ranked in the UK and among the lead research universities globally in all key areas of physics. Its mission is to apply the transformative power of physics to the foremost scientific problems and educate the next generation of physicists as well as to promote innovation and public engagement with physics.
Oxford University Physics leads ground-breaking scientific research across a wide spectrum of challenges: from quantum computing, quantum materials and quantum matter to space missions and observation; from climate science to the development of next-generation technologies for renewable energy; and from designing experiments to understand the nature of existence to revolutionising medicine and healthcare through biophysics.
Oxford University Physics has spun out 18 companies since launching the University’s first commercial venture in 1959 and works with enterprise across most areas of its leading scientific research.
About Oxford University
Oxford University has been placed number 1 in the Times Higher Education World University Rankings for the eighth year running, and number 3 in the QS World Rankings 2024. At the heart of this success are the twin-pillars of our ground-breaking research and innovation and our distinctive educational offer.
Oxford is world-famous for research and teaching excellence and home to some of the most talented people from across the globe. Our work helps the lives of millions, solving real-world problems through a huge network of partnerships and collaborations. The breadth and interdisciplinary nature of our research alongside our personalised approach to teaching sparks imaginative and inventive insights and solutions.
Through its research commercialisation arm, Oxford University Innovation, Oxford is the highest university patent filer in the UK and is ranked first in the UK for university spinouts, having created more than 300 new companies since 1988. Over a third of these companies have been created in the past five years. The university is a catalyst for prosperity in Oxfordshire and the United Kingdom, contributing £15.7 billion to the UK economy in 2018/19, and supports more than 28,000 full time jobs.
About the Quantum Computing and Simulation (QCS) Hub
The Quantum Computing & Simulation Hub (QCS) is a collaboration of 17 universities, supported by a wide range of commercial and governmental organisations, with the University of Oxford as its lead partner. It is one of four quantum technologies hubs in the UK National Quantum Technologies Programme, a £1 billion dynamic collaboration between industry, academia and government.
JOURNAL
Physical Review Letters
ARTICLE TITLE
Verifiable blind quantum computing with trapped ions and single photons’
Harnessing quantum technology for industry: Cutting-edge simulations for Industry 4.0
Hannover Messe
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WOLFGANG MAASS (LEFT), DOCTORAL RESEARCH STUDENT HANNAH STEIN AND RESEARCHER ANKIT AGRAWAL (RIGHT) ARE WORKING WITH PARTNERS FROM INDUSTRY AND ACADEMIA TO HARNESS THE POWER OF QUANTUM COMPUTATIONAL METHODS FOR THE METALWORKING INDUSTRY
view moreCREDIT: CREDIT: OLIVER DIETZE
High-quality, defect-free and perfectly dimensioned metal components. Quantum computing power looks set to optimize production processes in the metalworking industry. A team led by Professor of Business Informatics Wolfgang Maaß of Saarland University and the German Research Center for Artificial Intelligence (DFKI) is working with commercial and academic partners in the 'Quasim' project to develop novel quantum-based simulations that simply could not be performed on today's conventional computing architectures due to computing time and storage limits. The team will be demonstrating how these simulations can be used to boost quality, productivity and cost-efficiency at this year's Hannover Messe on 22-26 April (Hall 2, Stand B10).
Aero engines have to reliably deliver high levels of thrust even under adverse conditions, so precision is of paramount concern in the manufacture of modern aircraft turbines. In turbofan engines, the fan that draws air into the turbine has multiple blades with complex curved geometries. These metal blades are made by a precision milling process that requires a careful machining strategy. Precision milling is only possible if the relative motion of the tool and the workpiece is very tightly controlled. Failure to do so can mean that the blade starts to vibrate causing the surface of the blade to hit the milling head in an uncontrolled manner and damaging the blade. For a component that becomes essentially unusable even if very slightly out-of-spec, this can be a very expensive mishap. 'This kind of production error can be extremely costly for manufacturers of high-precision aero engine components,' said Wolfgang Maaß, professor of business informatics at Saarland University and head of the Smart Service Engineering research area at the German Research Center for Artificial Intelligence (DFKI).
But the situation is similar for many other companies, large and small, that manufacture metal components – including those produced by laser cutting. The extreme heat that is generated during the cutting process can cause the metal to expand in places where it should not. Or in conventional cutting operations, off-cuts can get caught in the machine, which then comes to a halt. The result is increased rejection rates and lengthy machine downtimes, costing the manufacturing company material, time and money. 'The metalworking industry is a major economic sector in Germany and the EU, and safety and quality standards are high. Production processes in the metalworking sector sometimes have rejection rates of about 1%, which doesn't sound like much, but overall, it can have a significant impact on competitiveness,' explained Wolfgang Maaß.
A reduction in rejection rate can be achieved by digital simulations that make use of artificial intelligence. By creating a digital twin of the workpiece, everything that happens to a real component can be simulated in a virtual environment – from planning and production through to quality assurance. In theory, every aspect of the production chain can be precisely optimized, whether it is the perfect spindle speed for milling or the ideal power density delivered by the laser. But there's a catch. The gigantic volume of data required to produce these high-resolution simulations simply cannot be handled with conventional computer systems. Quantum computers, which could deliver the level of computing power needed, are not yet available. The result: 'Simulations are currently rarely used in practical applications. In part, because sufficient computing power is just not available, and partly because specialized data and information are needed, which in turn requires detailed expertise in computational simulations,' explained Hannah Stein from Maaß' research team. At present, metalworking companies have to content themselves with lower resolution digital twins and they rely heavily on the practical expertise and experience of their production engineers.
And there is still some way to go before quantum computers deliver the sort of warp-speed computing needed to handle massive data volumes. The research partners in the Quasim project are however firmly rooted in reality. The consortium of industrial and academic partners is working on short-and long-term solutions that harness the power of quantum systems to deliver enhanced simulations for use in manufacturing scenarios. 'Our initial studies have shown that by exploiting the principles underlying quantum mechanical systems and using quantum-based machine learning strategies, we can solve algorithmic problems significantly faster,' said project coordinator Wolfgang Maaß. 'Although today's quantum computers are still in their infancy, the underlying technology can already be deployed in areas where conventional computers would be working at their limits, requiring immense amounts of time to complete a calculation.'
The researchers are using a variety of quantum computing methods to explore ways of making complex simulations faster and suitable for practical applications. The work involves applying quantum computing technologies to conventional simulation methods based on mathematical models from physics and materials science. The research team is also investigating quantum-based machine learning methods. By comparing these new approaches with conventional methodologies, and assessing the efficacy of the various solutions, the team is developing innovative solutions that could find practical application in the near future. The results are already being integrated into existing simulation methods. 'We are currently developing the first prototypes. So far, the most promising results have been achieved using hybrid models that combine conventional simulation methodologies with quantum technology and machine learning,' said doctoral researcher Hannah Stein.
As the researchers use production data from real manufacturing lines, aero engine manufacturers may soon be using quantum computer-based simulations to predict blade vibrations during milling. By working with an accurate digital twin, they can precisely set machining parameters, such as milling speed, enabling them to eradicate machining inaccuracies and significantly reduce rejection rates. Improved simulations also mean that laser cutters can deliver the right amount of power during an optimized machining sequence producing undamaged, perfectly dimensioned metal components. At this year's Hannover Messe, the business informatics specialists from Saarbrücken will be showcasing milling and laser cutting prototypes that demonstrate how conventional manufacturing can be enhanced by quantum-based simulations by delivering shorter material processing times and improved product quality.
The Quasim project ('QC-Enhanced Service Ecosystem for Simulation in Manufacturing') is a consortium comprising Wolfgang Maaß' research group at Saarland University and the German Research Center for Artificial Intelligence (DFKI), Professor Frank-Wilhelm Mauch's group at Forschungszentrum Jülich and Saarland University, the Fraunhofer Institute for Production Technology (IPT), the machine tool manufacturing company TRUMPF, the software component provider ModuleWorks and the associated project partners Ford and the aero engine manufacturer MTU Aero Engines. Total project funding of over €5 million has been provided by the Federal Ministry for Economic Affairs and Climate Action (BMWK) and the German Aerospace Centre (DLR).
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