Quantum computing may still be regarded by many IT leaders as a very niche technology, but broader business use cases may be just a few years away.
While only a handful of companies have machines with logical qubits today, delegates at the Commercialising Quantum Computing conference in London were told that a machine with 100 logical qubits would offer quantum advantage in material science by 2028.
This means that, by then, a sufficiently powerful and stable quantum computer would start delivering business value better than what would be possible using high performance computing.
AI and quantum computing
Mark Jackson, senior quantum evangelist at Quantinuum, said the company was already using generative quantum artificial intelligence (AI). In a fireside chat at the conference, Jackson spoke about the interaction between quantum computing and AI.
It is largely acknowledged that a quantum computer is not good at providing a precise answer, such as if applied to big data analysis. But, according to Jackson, it shines when used for machine learning, which can be applied to identify a correct answer. Quantum-enhanced machine learning can process large datasets far quicker than conventional computers, especially when applied to detecting patterns.
“Quantum computers can detect patterns that would be missed by other conventional computing methods,” said Jackson.
This ability to detect patterns in massive datasets could revolutionise cyber security. Becky Pickard, managing director of global cyber operations at Barclays, pointed out during a panel discussion that a lot of progress has been made with machine learning and how to apply it on a day-to-day basis: “We’re working with massive volumes of data – 12Tbytes – on a daily basis.”
She suggested that quantum machine learning could help. From an optimisation perspective, she is keen to see the development of quantum computing applied in a way that reshapes cyber defence.
Financial services
HSBC is one of the organisations that has been working on quantum computing for several years.
Discussing the return on investment opportunity, and how quantum computing can be used to build more optimised financial models, Phil Intallura, global head of quantum technologies at HSBC, said: “When you breakdown the opportunities, financial services is one of the biggest beneficiaries.”
As Intallura points out, banks are always looking for a better financial model: “There’s one thing that catalyses commercial organisations more than anything else, and that’s confidence. If you can show a solution using quantum technology that can get a better output based than using a supercomputers, [business decision-makers] will give you much more runway than you need.”
Another application area is the ability to generate a true random number, which can feed into financial model simulations.
In March, a team of researchers from JPMorganChase, Quantinuum, Argonne National Laboratory, Oak Ridge National Laboratory, and the University of Texas at Austin published a paper in Nature discussing a technique known as Random Circuit Sampling (RCS).
RCS is used to perform a certified-randomness-expansion protocol, which outputs more randomness than it takes as input. It is a task that is often used to demonstrate quantum supremacy since it cannot be achieved on a classical computer.
Speaking of the usefulness of a quantum number generator at HSBC, Intallura said: “Using quantum random numbers as your entropy source to classical simulation does not change any of the underlying model practices in classical models. You’re just injecting a different source of entropy than what we would [normally] use.”
Quantum computing and cryptography
For Intallura, regulatory pressure and the need to ensure financial transactions are secure is helping to inform quantum computing plans at financial institutions.
The US National Institute of Standards and Technology has ratified a number of post-quantum cryptography (PQC) standards. Banks face pressure from regulators to replace RSA-2048 encryption by 2035 and migrate fully over to quantum safe encryption standards to protect banking transactions.
But, as Mark Carney, lead of quantum cyber security research at Santander Global, noted, post-quantum cryptography needs both software and hardware acceleration.
“We want to be able to have PQC at speed in our devices and on our payment cards,” he said. “We want to give our customers the very best cryptography that we possibly can – not just for regulatory purposes, but also because it gives a sense of assurance.”
Among the promises of quantum computing is that it can be applied to solve complex optimisation problems. As and when they become commercially viable, such systems will need to work alongside traditional enterprise IT.
This is something that Gerard Mullery, interim CEO of Oxford Quantum Circuits, recognised during his presentation at the event. Mullery sees a need for quantum computing to be embedded in enterprise workflows.
“As AI agents autonomously orchestrate enterprise workflows, quantum compute platforms must be designed to integrate with them,” he added.
What is clear from the experts who spoke at the Commercialising Quantum Computing conference is that a useful machine is perhaps only a few years away. This will have enough logical qubits to solve real-world problems.
As such devices evolve, it is likely more organisations will draw on quantum computing for certain combinatorial optimisation problems, which will need to integrate with classical computing in the datacentre. As quantum computing becomes more accessible, there will also be a need to bolster cryptography with PQC.
This post is exclusively published on eduexpertisehub.com
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