Quantum computers have the potential to shake up finance, cybersecurity and other sectors. But investors hoping to profit from the new technology must be patient – and separate reality from hype.
In 2017, Chinese scientist Juan Yin and her team conducted a unique experiment. Using quantum technology, they linked two photons on a satellite called Micius, then dispatched them to different locations on Earth, thousands of miles apart.
Even across this vast distance, the two photons maintained their connection: when one was observed, the other immediately changed its properties, as if the particles were magically communicating. In scientific parlance, they were entangled.1
Welcome to the weird world of quantum mechanics, where up is down, here is there and the usual laws of physics no longer apply. In the early 20th century, Albert Einstein dismissed entanglement as “spooky action at a distance”, but it is now being observed in laboratories across the world.2 Quantum theory appears to explain the inner workings of the universe, however counterintuitive it may seem in the context of our everyday lives.
Today, the bizarre characteristics of the quantum realm are being harnessed for innovative technologies. Companies are racing to develop quantum computers made up of strings of entangled quantum bits, or qubits, that promise to increase computing speeds exponentially. These machines could theoretically revolutionise any sector that relies on rapid processing power.
A great deal of uncertainty surrounds the efficacy of the technology, and big technical challenges must be addressed before it becomes a practical tool. But experts argue that if these obstacles are overcome, quantum methods could be used to improve medical treatments, optimise energy and financial networks, and even tackle global problems such as climate change.
To understand how quantum computing works, you need to get your head around one of the spookiest aspects of quantum physics: the notion that reality behaves differently depending on whether it is being observed.
Reality behaves differently depending on whether it is being observed
Austrian physicist Erwin Schrödinger illustrated this concept with a famous thought experiment. Imagine a cat is kept in a box where a quantum phenomenon has a 50:50 chance of occurring, thereby triggering the release of poison. The point is not simply that we don’t know whether the cat is alive or dead until we open the box; according to the rules of quantum mechanics, the cat is both alive and dead at the same time, until it resolves into one of the two possibilities once it is observed. This is known as superposition.
Thankfully, no real cats have been harmed in quantum experiments – but the superposition effect has been recorded at a micro scale in laboratories, where light particles behave differently if they are being measured.
Superposition can be used to create a quantum computer. Traditional computers are made up of long chains of bits, which can be described in a binary way: 1 or 0. By contrast, quantum bits can be in various superpositions of 1 and 0 states, only resolving definitively into one or the other once a measurement is taken. This means quantum computers can work through huge numbers of potential solutions to a problem simultaneously.
What’s more, qubits can be entangled in pairs, like the photons in the satellite experiment in China. Thanks to the combined power of superposition and entanglement, a quantum computer could reach processing speeds only a planet-sized classical computer could match.
Building a quantum computer
We are some way from seeing quantum computers in our offices or homes, however. One issue is decoherence – qubits can be knocked out of superposition by miniature vibrations or tiny shifts in temperature.
A quantum computer needs to be kept very well isolated from the environment
“Quantum information is very delicate, and a quantum computer needs to be kept very well isolated from the environment,” says Adrian Kent, professor of quantum physics at the University of Cambridge. “The individual quantum circuits need to be kept isolated from each other so that they don't interfere. And a programmable quantum computer needs to allow you to control quantum interactions quite precisely, so that you can create the right circuit for the given program.”
US and Chinese technology companies with the resources to assemble and maintain these temperamental machines are leading the way, along with some large universities. The likes of Alibaba, Google and IBM have developed working quantum computers, although the most advanced only have around 50-100 qubits, some way short of the 1000-plus qubit machines that would be of any use in the real world (see Figure 1).
Figure 1: Quantum progress: quantum computers over time3
Source: Science, May 6, 2021
The fierce nature of the race has led to media hype, and there has been the occasional climbdown by the companies involved. Despite these controversies, tech companies are targeting rapid improvements. Google recently demonstrated its quantum computer can be used to simulate chemical reactions,4 while IBM says it will build a 1000-qubit machine by 2023; both companies believe a million-qubit machine is feasible by the end of the decade.5
Whether or not this timeline is realistic, the technical difficulties involved in operating full-scale quantum computers mean they will probably be used for specific problems classical computers tend to struggle with. These include modelling large systems and performing complex mathematical calculations, such as the factorisation of prime numbers.
Finance is a good candidate for quantum improvements. Markets are just the kind of complex, unpredictable systems quantum computers should be able to model more accurately than their classical equivalents. And companies are not waiting for the advent of full-scale quantum computers to investigate quantum solutions.
Large financial institutions are teaming up with tech firms to try out quantum algorithms
Large financial institutions are teaming up with tech firms to try out quantum algorithms using intermediate, error-prone (or “noisy”) quantum machines, made available using software accessible over the cloud. Using these methods as a stepping stone, experts have determined quantum tools could be used for a variety of financial tasks.
Quantum computers should speed up the machine-learning algorithms used by hedge funds, for example, and lay the ground for quicker, more efficient trading strategies. Quantum solutions might also be useful in Monte Carlo simulations, the complex calculations used to price derivatives options and measure risk. Research shows quantum-powered methods can speed up option pricing from an overnight process to an instantaneous one and allow organisations to stress test and immediately adjust portfolios based on a real-time picture of their risk exposures.
Quantum algorithms could also be applied in asset management to optimise portfolios and boost returns – but a key question is when quantum methods will deliver real-world results.
A recent study from Boston Consulting Group estimates Monte Carlo-based modelling applications will be widely available within five to ten years, with powerful quantum algorithms being used for portfolio optimisation within the next decade.6 Other estimates suggest the practical uses of quantum methods in finance will arrive sooner – Zapata, a US quantum start-up, believes quantum-powered credit scoring will be available within 18 months.7
There is another, more pressing reason why financial institutions are investigating quantum computing: security. Modern cryptographic protocols rely on factorising large numbers back into their constituent prime numbers, a calculation too difficult for even superfast classical computers to perform. Using a process known as Shor’s algorithm, quantum computers could theoretically crack these codes and punch holes in cybersecurity defences.
Governments are investing heavily in quantum computing technology, with a special focus on quantum cybersecurity
Metaculus, a forecasting platform that aggregates expert predictions of future events, has a running estimate on the date when Shor’s algorithm will be used to factor one of the large RSA numbers used in current cryptography.8 As of May 2021, the median prediction for the date was 2048 – a long way away, but soon enough that we should start worrying about the safety of data, according to experts in the field.
Given the threat to state secrets and financial stability, it is no wonder governments are investing heavily in quantum computing technology, with a special focus on quantum cybersecurity.
Current state-sponsored research centres on “post-quantum” cryptography, the attempt to design cryptosystems that use processes other than factorisation and will therefore be resistant to quantum hackers. The US National Institute of Standards and Technology (NIST) is currently running an international contest to find the most effective post-quantum encryption system and is expected to decide on new standards in 2022.
According to recent analysis from Berenberg, quantum computing is unlikely to move the dial on revenues for the large, diversified tech companies building the most advanced machines. Nevertheless, governments and private organisations will need to start securing their systems against quantum computers long before they become widely available, creating a fast-growing quantum cybersecurity industry in the interim.
Berenberg forecasts quantum cybersecurity will be worth $32.5 billion by 2028 (compared with $5 billion for quantum computing proper).9 This is not simply a matter of upgrading IT infrastructure: as the Internet of Things spreads and our physical world becomes more connected, manufacturers will have to future-proof their products against the quantum threat.
Quantum methods should also find applications in the pharmaceuticals industry
Quantum methods should also find applications in the pharmaceuticals industry, promising to cut costs and improve the effectiveness of new treatments. Because quantum mechanics align with the deep workings of nature, quantum systems are much better equipped than classical ones to simulate its effects, aiding drug discovery.
Quantum computers with a relatively modest number of qubits could replicate molecules such as penicillin and simulate their interactions; to do the same thing, a classical computer would need more bits than there are atoms in the known universe (see Figure 2).
“Quantum mechanics is at the heart of the complexity of the problem of drug discovery, because the underlying biomechanical processes take place on the molecular scale, which is where quantum interactions rule,” says Lene Oddershede, professor of physics at the Niels Bohr Institute, University of Copenhagen, and senior vice president at the Novo Nordisk Foundation.
Figure 2: Modelling molecules: To model a complex molecule, a classical computer would need more bits than there are atoms in the known universe
Source: Cambridge Quantum Computing
Other potential uses of quantum optimisation and chemical modelling encompass the renewable energy sector. Oddershede believes governments should be looking at quantum solutions to improve the efficiency of national energy grids – the kind of large, data-spewing systems quantum computers will be able to manage more efficiently than today’s supercomputers, which have gargantuan carbon footprints.
Governments and companies across a swathe of sectors are looking to become early adopters of quantum technology
Given the range of its possible applications, it is no wonder companies across a swathe of sectors are looking to become early adopters of quantum technology, despite the question marks over its efficacy in the present. The timescales are relative – while a quantum-powered smartphone or desktop PC may be a remote prospect, those in charge of cybersecurity for large organisations will need to start thinking about quantum-proofing their systems sooner rather than later.