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. Spooky indeed.
Entering the quantum era
Before they fully grasped the implications of quantum physics, scientists used its principles to design technologies such as lasers and semiconductors, ushering in the information age. Today, the bizarre characteristics of the quantum realm are being harnessed more directly, opening new possibilities.
Governments and technology companies are racing to develop quantum computers
Governments and technology 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, including finance, while posing a serious threat to existing cybersecurity systems. Quantum algorithms have the potential to model chemical processes with unprecedented accuracy, yielding new discoveries in pharmaceuticals and biotech.
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.
“There is enormous potential for quantum simulation – and quantum computing, once we have it – to enable us to better understand the details of the world around us, to make better drugs, to improve society,” says Lene Oddershede, professor of physics at the Niels Bohr Institute, University of Copenhagen, and senior vice president at the Novo Nordisk Foundation.
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.
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.
In quantum mechanics you do not know the state of a system before you have made a measurement
“One of the fundamental statements of quantum mechanics is that you do not know the state of a system before you have made a measurement,” Oddershede explains. “Until the box is opened, the cat is in a superposition of two distinct states, dead and alive. You cannot know the state before you do the measurement, and when you do the measurement, you have determined whether the cat is dead or alive.”
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.
Scientists and philosophers struggle to explain how this effect tallies with the laws of classical physics. According to one view, everything in the universe has a hidden shadow, an unobservable layer of reality where the numbers add up. Other experts have suggested we are living in many parallel universes simultaneously (when I look in the box and see a dead cat, there is another “me” in a different universe who sees the cat contentedly purring).3
What we do know is that we can use superposition to build a new type of 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. In effect, their quantum states are linked: a qubit and its entangled partner will always take the same form when observed. Thanks to the combined power of superposition and entanglement, a quantum computer could reach processing speeds only a planet-sized classical computer could match.
Figure 1: The quantum bit4
Source: Volkswagen, November 5, 2019
This is all the more significant given classical computers are not improving as rapidly as they once were. Moore’s Law – the theory that the number of transistors on a computer chip doubles every two years – is breaking down as it becomes ever more difficult (and expensive) for technology firms to cram nanometre-long transistors onto microchips.
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, making quantum computers extremely challenging to build.
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 2).
Figure 2: Quantum progress: quantum computers over time5
Source: Science, May 6, 2021
Most of the larger tech companies are aiming to build what are known as “universal” quantum computers based on quantum logic gates, which should eventually be able to handle a range of different applications, along with a stack of software to run on them. Others, including Canadian firm D-Wave, are building more specialised machines known as annealers, designed specifically for optimisation problems, which involve finding the most efficient solution from a range of options.
All these firms are vying to achieve what’s known as “quantum supremacy”
In a competitive field, all these firms are vying to achieve what’s known as quantum supremacy: proof their quantum computer can complete a task that would be impossible for a classical one. In 2019, Google proclaimed it had achieved quantum supremacy on an obscure calculation with its 53-qubit machine (IBM fired back, arguing Google had not benchmarked its test against the best modern supercomputers, which could complete the same task more accurately given a little more time).6 In December 2020, a team of Chinese academics published a paper demonstrating their computer had achieved supremacy in a narrow, photon-based experiment – an impressive feat, albeit one with no obvious practical applications.7
“People have probably seen headlines about Google, and more recently Chinese researchers, achieving so-called quantum supremacy. Those are really impressive technical achievements, but it's important to understand what they mean,” says Kent.
“These groups built relatively small quantum devices, using different technologies, which can do something that would be effectively impossible to simulate on any standard computer. There’s a little room for debate even about those claims but, taking them at face value, it doesn’t mean you can run any program, or even necessarily a single useful program, on the quantum computer.”
The fierce nature of the race has led to media hype and occasional climbdowns by the companies involved
The fierce nature of the race has led to media hype, and there has been the occasional climbdown by the companies involved. In early 2021, Microsoft was forced to retract a paper claiming it had discovered a way to build quantum computers using a new group of particles less prone to decoherence, admitting it had made mistakes in its research.8 D-Wave has been criticised for exaggerating the amount of quantum mechanics actually involved in its annealing devices and testing them against inferior classical computers.9
Despite these controversies, tech companies are targeting rapid improvements. Google recently demonstrated its quantum computer can be used to simulate chemical reactions,10 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.11
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. However, even limited to these areas, a quantum breakthrough could have significant implications for a wide variety of sectors.
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. Willis Towers Watson is working with Microsoft on new quantum-powered risk management protocols, while JPMorgan has partnerships with both IBM and Honeywell to take advantage of two different quantum technologies (the former uses superconducting loops in its computers, while the latter has a different kind of architecture based on trapped ions).
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. Spain’s Caixa Bank says it has proved a hybrid classical-quantum computing model – which combines quantum computing and conventional computing in different phases of the calculation process – can be used to precisely segment customers based on their risk profiles.12
Quantum risk management
Other firms are investigating quantum solutions to speed up 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.
Many financial institutions are investigating quantum algorithms for quantifying and pricing risk in financial markets
“Many financial institutions are investigating quantum algorithms for quantifying and pricing risk in financial markets,” says Matthias Rosenkranz, scientific project manager at start-up Cambridge Quantum Computing. “The main workhorse is a quantum algorithm called Amplitude Estimation, which improves Monte Carlo simulations. This algorithm promises to estimate risk or instrument prices using fewer samples compared to a standard Monte Carlo simulation. This can translate to faster execution of Monte Carlo-based pricing engines or higher accuracy for a given time budget.”
Goldman Sachs and IBM, which have a quantum computing partnership, recently published the results of a study that showed a quantum computer with 7,500 qubits could price derivatives faster and more accurately than classical computers (see Figure 3).13
Figure 3: Quantum-driven risk calculation offers improvements over traditional Monte Carlo methods
Note: While the existing small, error-prone quantum computers do not outperform classical computers when gauging portfolio risk, quantum computers with more qubits could perform the same calculations quicker and more accurately than the most sophisticated classical algorithms. Source: IBM, 2019
Other companies are investigating the use of quantum algorithms in asset management to optimise portfolios and boost returns. Using historical trading data, Spanish start-up Multiverse Computing and Spanish bank BBVA used a quantum annealer to determine the optimum portfolio composition out of 10,382 possibilities, more than the number of atoms in the known universe. (Simply put, annealing works by using quantum properties to find the lowest energy state of a system, thereby flagging up the simplest way or organising or navigating it.) The simulated portfolio delivered returns of between 20 and 80 per cent over a four-year period, depending on the amount of volatility investors were willing to accept, compared with a return of 19 per cent on the part of BBVA’s human traders and their classical computer models.14
When will quantum methods deliver real-world results in finance beyond such simulations?
The key question is when quantum methods will deliver real-world results in finance beyond such simulations. Rosenkranz says it is difficult to estimate with any degree of certainty.
“It has been suggested that certain applications such as quantum-assisted portfolio optimisation may provide an advantage within five years. However, such estimates hinge on overcoming two main challenges. First, quantum computing hardware needs to reduce the levels of noise we find in today’s devices. Second, we need to develop better software and algorithms that can leverage today’s devices to accelerate the quantum advantage,” he says.
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 (see Figure 4).15 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.16
Some large investment banks are hiring quantum physics graduates to build expertise internally, but for the most part financial institutions prefer to work with specialists who have direct access to the hardware. IBM’s Quantum Network is popular in finance, counting Goldman, Wells Fargo and Barclays among its customers. This may be because of its accessibility and user-friendly software tools: IBM allows companies to build virtual quantum circuits and test them out on real quantum computers using a simulator. (You can try building a simple quantum circuit using IBM’s interface here.)
Figure 4: Estimated timeline for quantum applications in finance
Note: Quantum advantage over classical computing is uncertain in many areas listed. Business impact assumes that quantum advantage is realised in each area and is not risk-adjusted. QFT = quantum Fourier transform. QAOA = quantum approximate optimisation algorithm. Source: QC Ware, BCG, November 2020
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.
Quantum computers could theoretically crack these codes and punch holes in cybersecurity defences
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.17 As of May 2021, the median prediction for the date was 2048 – a long way away, but soon enough that companies and governments should start worrying about the safety of their data, according to experts in the field.
“A lot depends on how highly you value privacy, how long you need to maintain it, and how big a disaster it would be if your cryptosystem were hacked. Bear in mind that if we take the median estimate as representing a 50 per cent chance, then shorter timescales still have a significant chance,” says Kent.
“Some government secrets are meant to be kept secure for 50 years or longer, and a one per cent chance they could be broken sooner might be unacceptable. People responsible for keeping those secure should be, and I’m sure are, very, very concerned about the possibility adversaries will store the encrypted data now and be able to decrypt it later when they have a large quantum computer. They probably shouldn’t be using any cryptosystem that relies on factorisation for its security,” Kent adds.
A related problem is that quantum computers pose a threat to the blockchain technology underpinning cryptocurrencies such as bitcoin. They could rapidly crack the one-way mathematical functions used to generate the digital signatures that authenticate users and validate the digital ledger of previous transactions.
Quantum computers could accelerate bitcoin mining
In addition, quantum computers could accelerate bitcoin mining, the process used to add new blocks to the chain using random numerical searches. Because of the limitations of classical computers, mining is a laborious and energy-intensive process that naturally slows down the rate new blocks are added to the global ledger; this ensures the new additions can be properly recorded and checked. But a quantum computer could complete these searches in an instant, monopolising the mining process and potentially subverting the system for nefarious ends.
“Within ten years, quantum computers will be able to calculate the one-way functions, including blockchains, that are used to secure the internet and financial transactions. Widely deployed one-way encryption will instantly become obsolete,” according to a Nature paper by a team of researchers led by Alexander Lvovsky, professor of physics at the University of Oxford.18
“Quantum computers will find solutions quickly, potentially enabling the few users who have them to censor transactions and to monopolize the addition of blocks to the bitcoin ledger… These parties could sabotage transactions, prevent their own from being recorded or double-spend,” Lvovsky and his colleagues added.
The quantum sword, the quantum shield
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. In a speech in April 2021, the head of the UK intelligence service, GCHQ, warned the government needed to spend more on improving its quantum capabilities to keep pace with China.19
China has invested more than $1 billion in a quantum research institute in Hebei province and is leading the way on patents for commercial quantum applications. The US, meanwhile, has ploughed $1.2 billion into quantum technology as part of the National Quantum Initiative Act, passed by Congress in 2018.20
One line of 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. (Some companies already offer off-the-shelf quantum-based cybersecurity products, based on quantum algorithms generated on small, noisy quantum devices. However, governments recommend large organisations wait until new standards are agreed, to avoid having to invest twice in new security upgrades.)21
As for bitcoin, Lvovsky and colleagues argue the currency could be secured using quantum communication, which harnesses the mysterious properties of quantum physics to flag network breaches. Because of the principle that an observation changes the state of a quantum object, eavesdroppers on a quantum communications system can be immediately detected.
Quantum communications do not require full-scale quantum computers to work
Quantum communications do not require full-scale quantum computers to work and the technology is already available, although there are limitations on distance when using fibre-optic cables. China’s Micius satellite could represent a solution – scientists have used it to relay quantum keys, setting up a quantum-encrypted video call between Beijing and Vienna.22
Quantum technology is even being used to explore the possibility of entirely new kinds of currencies, whose security is guaranteed by quantum physics. Kent is working on a theoretical framework known as “S-money”, which is both secure and potentially much faster and more flexible than existing financial technology.
“It's specifically designed for settings where time is critical, and so you want a recipient to be able to verify the money without having to send signals around the network to cross-check. A key realisation here was that the very concept of what money is or does needs to be extended to make it as useful as possible in settings like this, the global financial network being an example,” he says.
S-money consists of secure virtual tokens that materialise at given points in a network in response to real-time data flows, as opposed to existing physical or digital currencies that need to travel on definite paths through space. In fact, S-money could conceivably be used for commerce on a galactic scale with no time lags – although, like so much else in quantum tech, interstellar trade is a theoretical prospect at this point.
This is not to say there are no implications for investors in the here and now. 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 $5 billion for quantum computing proper).23 This is not simply a matter of upgrading IT infrastructure: as the Internet of Things spreads and our physical world becomes more connected, manufacturers will have to future-proof their products against the quantum threat.
Take autonomous and internet-connected vehicles: Berenberg observes “auto models being designed today could still be operating on the roads well beyond the expected timeline for the development of a quantum computer powerful enough to present a threat to current encryption methods”.24
Figure 5: Estimated growth of post-quantum cybersecurity market ($ millions)
Note: QKD = Quantum key distribution, QSC = quantum-safe cryptography, PQC = post-quantum cryptography, HSM = hardware security module. Source: Berenberg, 2018
Investors will also need to ensure the companies they hold in their portfolios are resilient against the quantum cyber threat. Today, a data breach occurs once every 39 seconds in the US, affecting nearly one in three Americans, with the mean cost of each data breach to businesses around $3.9 million.25
When user data is compromised, companies can be subject to regulatory fines and class-action lawsuits worth hundreds of millions. The financial costs of security breaches are only likely to escalate in a world where all cryptographic protocols are vulnerable to quantum attack.
As for the beneficiaries of the quantum cyber trend, much will depend on the outcome of NIST’s competition over the next 18 months. The winning post-quantum method will probably become the global standard, opening up government and private contracts for quantum cybersecurity companies to run the relevant algorithms. Based on its shortlist, NIST looks to be favouring so-called lattice systems, which generate public and private keys based on coordinates in mathematical grids, although an alternative method based on error-correcting codes, developed by London-based quantum cryptography firm Post Quantum, is among those being tested in the final stages of the competition.26
Many quantum cybersecurity companies, Post Quantum included, are small start-ups. But there are some listed exceptions, including Canada’s 01 Communique, which recently agreed a deal with PwC to secure its China-based operations with quantum-powered cryptography.27
Data management, drug discovery and systems optimisation
Another investment route into the industry is to invest on the “picks and shovels” side. The manufacturers of dilution refrigerators, photonic systems, vacuum technology and other high-tech gizmos are likely to see increased demand over the next decade as larger, more sophisticated quantum computers are constructed. Honeywell, Oxford Instruments and Keysight Technologies are among the companies that specialise in quantum computer components.
Over the longer term, the advent of quantum computing should increase the value of large datasets by speeding up the machine-learning algorithms that analyse and make sense of them. This would benefit companies already adept at managing data, along with firms supplying them with hardware.
Quantum computing is yet another set of tools which makes data more useful
“Quantum computing is yet another set of tools which makes data more useful – both existing historical datasets and data-gathering infrastructure. If you know you will get better, more precise, faster answers from looking at your data, you will value the historic data more. This benefits data-rich companies with strong existing datasets,” says Giles Parkinson, global equities portfolio manager at Aviva Investors.
“There will also be more investment in gathering new data, benefiting manufacturers of sensors, memory and connectivity chips that provide the nuts and bolts of data collection and transmission to the point where it’s analysed for answers. This is already the case – quantum computing just extends this ‘data utility’ megatrend further into the future,” Parkinson adds.
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 6).
Figure 6: Modelling molecules: To model a complex molecule, a classical computer would need more bits than there are atoms in the known universe
Note: To accurately simulate a molecule and model its chemical reactions, you would need a traditional computer of impossible size - for complex molecules, such a machine would require more bits than there are atoms in the known universe. A quantum computer with a relatively small number of qubits could perform the same calculation with ease. Source: Cambridge Quantum Computing
“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 Professor Oddershede at Novo Nordisk.
“Because of the quantum nature of these building blocks, there is an advantage to using quantum simulation in drug exploration. Quantum simulators can be used because they are quantum in nature and can mimic the system being investigated. When we have a full-blown quantum computer, just the computational power it will provide is going to revolutionise drug discovery,” she adds.
In the meantime, US biotech multinational Biogen has partnered with Canada-based quantum computing specialist 1Qbit to develop a molecule comparison tool, using the small, noisy quantum devices already available. It says this gives it a competitive advantage in the early stages of drug discovery, by improving accuracy and cutting costs in what is a notoriously error-prone and expensive process.28 Biogen is not the only company experimenting with quantum: almost one third of all life sciences companies globally have started evaluating quantum methods for drug discovery, according to McKinsey.29
“We’re already benefiting from scientific breakthroughs that enable better analysis, diagnostics, modelling and design of both the mechanics of diseases and possible cures,” says Matt Kirby, global equities portfolio manager at Aviva Investors. “Cryogenic electron microscopy, more affordable gene sequencing, gene and cell therapies are all part of this change. In-silico, or computer-aided, drug discovery and modelling of drug interactions with the human body is another one of these progress vectors. It looks like quantum computing will aid that further.”
Tools and service providers are likely to benefit from an acceleration in the productivity of R&D in pharmaceuticals and biotech
The whole ecosystem of tools and service providers in this area – including contract manufacturers of novel biological drugs, suppliers of diagnostic and analytical tools, and clinical research organisations – are likely to benefit from an acceleration in the productivity of R&D in pharmaceuticals and biotech.
Quantum tools are also being used to model electrochemical materials, such as those found in batteries. Carmaker Volkswagen has developed algorithms capable of simulating some of the key molecules used in battery production on the existing quantum computers offered by Google and D-Wave, raising the possibility of better-performing batteries (and higher-performance electric vehicles) once a whole battery can be modelled on a more sophisticated piece of hardware.
Such are the myriad possibilities of quantum computing, first movers are beginning to find applications across very different parts of their businesses. As well as its battery experiments, VW is working with D-Wave’s quantum annealing technology on a traffic optimisation project. By crunching data from vehicles in Beijing, the two companies were able to cut journey times between the airport and the city centre.30 VW used this proof-of-concept experiment to develop an app that is being used in a real-world pilot project to improve traffic congestion in Lisbon, providing data to bus drivers they can use to amend their journeys in real time.
Similar methods are now being used to improve supply chain logistics and streamline production inside factories. Japanese manufacturer Denso is applying a hybrid classical-quantum process to reduce gridlock on its factory floors, for example.31
Energy efficiency and climate change
Perhaps more significant are the potential uses of quantum optimisation and chemical modelling in the renewable energy sector, which could eventually make quantum computers a vital tool in the battle against climate change. In July 2020, Microsoft said it was using quantum algorithms to devise new carbon fixation methods, with a view to creating technology to remove carbon dioxide from the atmosphere.32
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 (the world’s current largest supercomputer guzzles 17.8 megawatts of power, enough to supply electricity to 13,500 American households).33 Microsoft has made steps forward in this area, too: the company is working with the Dubai Water and Electricity Authority to implement quantum algorithms to optimise the energy mix based on the city’s real-time consumption needs.34
“The energy sector generates enormous amounts of data. Imagine the energy grid of Europe; calculating where energy is needed, and how to get energy to that place, requires processing enormous amounts of data. Once we have a quantum computer, that process is going to be revolutionised,” says Oddershede. “Solely for security reasons, every country should have large efforts on the quantum computation front, but also for the benefits related to climate change and renewable energy.”
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 governments and 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. 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.
In this respect, quantum computing is no different from any other disruptive technological advance. Think of the hype surrounding the internet in the mid-1990s, which prompted scepticism as to its true value over the longer term. As Microsoft founder Bill Gates sagely warned in his book The Road Ahead (1996): “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.”35