Size of Industry

$1,765,000,000

What is it?

An ordinary computer chip uses bits. These are like tiny switches, that can either be in the off position – represented by a zero – or in the on position – represented by a one. Every app you use, website you visit and photograph you take is ultimately made up of millions of these bits in some combination of ones and zeroes.

This works great for most things, but it doesn’t reflect the way the universe actually works. In nature, things aren’t just on or off. They’re uncertain. And even our best supercomputers aren’t very good at dealing with uncertainty. That’s a problem.

That's because, over the last century, physicists have discovered when you go down to a really small scale, weird things start to happen. They’ve developed a whole new field of science to try and explain them. It’s called quantum mechanics.

Quantum mechanics is the foundation of physics, which underlies chemistry, which is the foundation of biology. So for scientists to accurately simulate any of those things, they need a better way of making calculations that can handle uncertainty. Enter, quantum computers.

HOW does it work?

Instead of bits, quantum computers use qubits. Rather than just being on or off, qubits can also be in what’s called ‘superposition’ – where they’re both on and off at the same time, or somewhere on a spectrum between the two.

Take a coin. If you flip it, it can either be heads or tails. But if you spin it – it’s got a chance of landing on heads, and a chance of landing on tails. Until you measure it, by stopping the coin, it can be either. Superposition is like a spinning coin, and it’s one of the things that makes quantum computers so powerful. A qubit allows for uncertainty.

What is quantum computing? How does it work? How will it change the world? 

If you ask a normal computer to figure its way out of a maze, it will try every single branch in turn, ruling them all out individually until it finds the right one. A quantum computer can go down every path of the maze at once. It can hold uncertainty in its head.

It’s a bit like keeping a finger in the pages of a choose your own adventure book. If your character dies, you can immediately choose a different path, instead of having to return to the start of the book.

The other thing that qubits can do is called entanglement. Normally, if you flip two coins, the result of one coin toss has no bearing on the result of the other one. They’re independent. In entanglement, two particles are linked together, even if they’re physically separate. If one comes up heads, the other one will also be heads.

It sounds like magic, and physicists still don’t fully understand how or why it works. But in the realm of quantum computing, it means that you can move information around, even if it contains uncertainty. You can take that spinning coin and use it to perform complex calculations. And if you can string together multiple qubits, you can tackle problems that would take our best computers millions of years to solve.

Use Case

How it’s using quantum computing: To presidential candidate Andrew Yang, Google’s quantum milestone meant that “no code is uncrackable.” He was referring to a much-discussed notion that the unprecedented factorization power of quantum computers would severely undermine common internet encryption systems.

But Google’s device (like all current QC devices) is far too error-prone to pose the immediate cybersecurity threat that Yang implied. In fact, according to theoretical computer scientist Scott Aaronson, such a machine won’t exist for quite a while. But the looming danger is serious. And the years-long push toward quantum-resistant algorithms — like the National Institute of Standards and Technology’s ongoing competition to build such models — illustrates how seriously the security community takes the threat.

One of just 26 so-called post-quantum algorithms to make the NIST’s “semifinals” comes from, appropriately enough, British-based cybersecurity leader Post-Quantum. Experts say the careful and deliberate process exemplified by the NIST’s project is precisely what quantum-focused security needs. As Dr. Deborah Franke of the National Security Agency told Nextgov, "There are two ways you could make a mistake with quantum-resistant encryption: One is you could jump to the algorithm too soon, and the other is you jump to the algorithm too late.”

How it’s using quantum computing: “The real excitement about quantum is that the universe fundamentally works in a quantum way, so you will be able to understand nature better,” Google’s Pichai told MIT Technology Review in the wake of his company’s recent announcement. “It’s early days, but where quantum mechanics shines is the ability to simulate molecules, molecular processes, and I think that is where it will be the strongest. Drug discovery is a great example.”

One company focusing computational heft on molecular simulation, specifically protein behavior, is Toronto-based biotech startup ProteinQure. Flush with $4 million in recent seed funding, it partners with quantum-computing leaders (IBM, Microsoft and Rigetti Computing) and pharma research outfits (SRI International, AstraZeneca) to explore QC’s potential in modeling protein.

That’s the deeply complex but high-yield route of drug development in which proteins are engineered for targeted medical purposes. Although it’s vastly more precise than the old-school trial-and-error method of running chemical experiments, it’s infinitely more challenging from a computational standpoint. As Boston Consulting Group noted, merely modeling a penicillin molecule would require an impossibly large classical computer with 10-to-the-86th-power bits. For advanced quantum computers, though, that same process could be a snap — and could lead to the discovery of new drugs for serious maladies like cancer, Alzheimer’s and heart disease.

Cambridge, Mass.-based Biogen is another notable company exploring quantum computing’s capacity for drug development. Focused on neurological disease research, the biotech firm announced a 2017 partnership with quantum startup 1QBit and Accenture.

How it’s using quantum computing: QCs’ potential to simulate quantum mechanics could be equally transformative in other chemistry-related realms beyond drug development. The auto industry, for example, wants to harness the technology to build better car batteries.

In 2018, German car manufacturer Daimler AG (the parent company of Mercedes-Benz) announced two distinct partnerships with quantum-computing powerhouses Google and IBM. Electric vehicles are “mainly based on a well-functioning cell chemistry of the batteries,” the company wrote in its magazine at the time. Quantum computing, it added, inspires “justified hope” for “initial results” in areas like cellular simulation and the aging of battery cells. Improved batteries for electric vehicles could help increase adoption of those vehicles.

Daimler is also looking into how QC could potentially supercharge AI, plus manage an autonomous-vehicle-choked traffic future and accelerate its logistics. It follows in the footsteps of another major Teutonic transportation brand: Volkswagen. In 2017, the automaker announced a partnership with Google focused on similar initiatives. It also teamed up with D-Wave Systems, in 2018.

How it’s using quantum computing: Volkswagen’s exploration of optimization brings up a point worth emphasizing: Despite some common framing, the main breakthrough of quantum computing isn’t just the speed at which it will solve challenges, but the kinds of challenges it will solve.

The “traveling salesman” problem, for instance, is one of the most famous in computation. It aims to determine the shortest possible route between multiple cities, hitting each city once and returning to the starting point. Known as an optimization problem, it’s incredibly difficult for a classical computer to tackle. For fully realized QCs, though, it could be a cakewalk.

D-Wave and VW have already run pilot programs on a number of traffic- and travel-related optimization challenges, including streamlining traffic flows in Beijing, Barcelona and, just this month, Lisbon. For the latter, a fleet of buses traveled along distinct routes that were tailored to real-time traffic conditions through a quantum algorithm, which VW continues to tweak after each trial run. According to D-Wave CEO Vern Brownell, the company’s pilot “brings us closer than ever to realizing true, practical quantum computing.”

How it’s using quantum computing: The list of partners that comprise Microsoft’s so-called Quantum Network includes a slew of research universities and quantum-focused technical outfits, but precious few business affiliates. However, two of the five — NatWest and Willis Towers Watson — are banking interests. Similarly, at IBM’s Q Network, JPMorgan Chase stands out amid a sea of tech-focused members as well as government and higher-ed research institutions.

That hugely profitable financial services companies would want to leverage paradigm-shifting technology is hardly a shocker, but quantum and financial modeling are a truly natural match thanks to structural similarities. As a group of European researchers wrote last year, “[T]he entire financial market can be modeled as a quantum process, where quantities that are important to finance, such as the covariance matrix, emerge naturally.”

A lot of recent research has focused specifically on quantum’s potential to dramatically speed up the so-called Monte Carlo model, which essentially gauges the probability of various outcomes and their corresponding risks. A 2019 paper co-written by IBM researchers and members of JPMorgan’s Quantitative Research team included a methodology to price option contracts using a quantum computer.

Its seemingly clear risk-assessment application aside, quantum in finance could have a broad future. “If we had [a commercial quantum computer] today, what would we do?" Nikitas Stamatopoulos, a co-author of the price-options paper, wondered. "The answer today is not very clear."

How it’s using quantum computing: The world has a fertilizer problem that extends beyond an overabundance of poop. Much of the planet’s fertilizer is made by heating and pressurizing atmospheric nitrogen into ammonia, a process pioneered in the early 1900s by German chemist Fritz Haber.

The so-called Haber process, though revolutionary, proved quite energy-consumptive: some three percent of annual global energy output goes into running Haber, which accounts for more than one percent of greenhouse gas emissions. More maddening, some bacteria perform that process naturally — we simply have no idea how and therefore can’t leverage it.

With an adequate quantum computer, however, we could probably figure out how — and, in doing so, significantly conserve energy. In 2017, researchers from Microsoft isolated the cofactor molecule that’s necessary to simulate. And they’ll do that just as soon as the quantum hardware has a sufficient qubit count and noise stabilization. Google’s CEO recently told MIT he thinks the quantum improvement of Haber is roughly a decade away.

How it’s using quantum computing: Recent research into whether quantum computing might vastly improve weather prediction has determined… it’s a topic worth researching! And while we still have little understanding of that relationship, many in the QC field view it as a notable use case.

Ray Johnson, the former CTO at Lockheed Martin and now an independent director at quantum startup Rigetti Computing, is among those who’ve indicated that quantum computing’s method of simultaneous (rather than sequential) calculation will likely be successful in “analyzing the very, very complex system of variables that is weather.” Futurist Bernard Marr has echoed the sentiment.

While we currently use some of the world’s most powerful supercomputers to model high-resolution weather forecasts, accurate numerical weather prediction is notoriously difficult. In fact, it probably hasn’t been that long since you cursed an off-the-mark meteorologist.

How it’s using quantum computing: Quantum computing and artificial intelligence may prove to be mutual back-scratchers. As VentureBeat recently explained, advances in deep learning will likely increase our understanding of quantum mechanics while at the same time fully realized quantum computers could far surpass conventional ones in data pattern recognition. Regarding the latter, IBM’s quantum research team recently found that entangling qubits on the quantum computer that ran a data-classification experiment cut the error rate in half compared to unentangled qubits.

“What this suggests,” an essay in the MIT Technology Review noted, “is that as quantum computers get better at harnessing qubits and at entangling them, they’ll also get better at tackling machine-learning problems.”

IBM’s research came in the wake of another promising machine-learning classification algorithm: a quantum-classical hybrid run on a 19-qubit machine built by Rigetti Computing.

“Harnessing [quantum computers’ statistical distribution] has the potential to accelerate or otherwise improve machine learning relative to purely classical performance,” Rigetti researchers wrote. The hybridization of classical compute and quantum processors overcame “a key challenge” in realizing that aim, they explained.

Both are important steps toward the ultimate goal of significantly accelerating AI through quantum computing. Which might mean virtual assistants that understand you the first time. Or non-player-controlled video game characters that behave hyper-realistically. The potential advancements are numerous.

“I think AI can accelerate quantum computing," Google's Pichai said, "and quantum computing can accelerate AI.”

Market

Quantum Computing Market worth $1,765 million by 2026 - Exclusive Report by MarketsandMarkets™

According to the new market research report "Quantum Computing Market with COVID-19 impact by Offering (Systems and Services), Deployment (On Premises and Cloud Based), Application, Technology, End-use Industry and Region - Global Forecast to 2026", published by MarketsandMarkets™, the market is expected to grow from USD 472 million in 2021 to USD 1,765 million by 2026, at a CAGR of 30.2%. The early adoption of quantum computing in the banking and finance sector is expected to fuel the growth of the market globally. Other key factors contributing to the growth of the quantum computing market include rising investments by governments of different countries to carry out research and development activities related to quantum computing technology. Several companies are focusing on the adoption of QCaaS post-COVID-19. This, in turn, is expected to contribute to the growth of the quantum computing market. However, stability and error correction issues is expected to restrain the growth of the market.

Services segment is attributed to hold the largest share of the Quantum Computing market

The growth of services segment can be attributed to the increasing number of startups across the world that are investing in research and development activities related to quantum computing technology. This technology is used in optimization, simulation, and machine learning applications, thereby leading to optimum utilization costs and highly efficient operations in various end-use industries.

Cloud based deployment to witness the highest growth in Quantum Computing market in coming years

With the development of highly powerful systems, the demand for cloud-based deployment of quantum computing systems and services is expected to increase. This, in turn, is expected to result in a significant revenue source for service providers, with users paying for access to noisy intermediate-scale quantum (NISQ) systems that can solve real-world problems. The limited lifespan of rapidly advancing quantum computing systems also favors cloud service providers. The flexibility of access offered to users is another factor fueling the adoption of cloud-based deployment of quantum computing systems and services. For the foreseeable future, quantum computers are expected not to be portable. Cloud can provide users with access to different devices and simulators from their laptops.

Optimization accounted for a major share of the overall Quantum Computing market

Optimization is the largest application for quantum computing and accounted for a major share of the overall Quantum Computing market. Companies such as D-Wave Systems, Cambridge Quantum Computing, QC Ware, and 1QB Information Technologies are developing quantum computing systems for optimization applications. Networked Quantum Information Technologies Hub (NQIT) is expanding to incorporate optimization solutions for resolving problems faced by the practical applications of quantum computing technology.

Trapped ions segment to witness highest CAGR of Quantum Computing market during the forecast period

The trapped ions segment of the market is projected to grow at the highest CAGR during the forecast period as quantum computing systems based on trapped ions offer more stability and better connectivity than quantum computing systems based on other technologies. IonQ, Alpine Quantum Technologies, and Honeywell are a few companies that use trapped ions technology in their quantum computing systems.

Banking and finance is attributed to hold major share of Quantum Computing market during the forecast period

In the banking and finance end-use industry, quantum computing is used for risk modeling and trading applications. It is also used to detect the market instabilities by identifying stock market risks and optimize the trading trajectories, portfolios, and asset pricing and hedging. As the financial sector is difficult to understand; the quantum computing approach is expected to help users understand the complexities of the banking and finance end-use industry. Moreover, it can help traders by suggesting them solutions to overcome financial challenges.

APAC to witness highest growth of Quantum Computing market during the forecast period

APAC region is a leading hub for several industries, including healthcare and pharmaceuticals, banking and finance, and chemicals. Countries such as China, Japan, and South Korea are the leading manufacturers of consumer electronics, including smartphones, laptops, and gaming consoles, in APAC. There is a requirement to resolve complications in optimization, simulation, and machine learning applications across these industries. The large-scale development witnessed by emerging economies of APAC and the increased use of advanced technologies in the manufacturing sector are contributing to the development of large and medium enterprises in the region. This, in turn, is fueling the demand for quantum computing services and systems in APAC.

In APAC, the investments look promising, as most countries such as China, Japan, and South Korea have successfully contained the virus compared with the US and European countries. China is easing the restrictions placed on factory lockdowns and worker movement. Despite being the epicenter of COVID-19, China has maintained its dominant position as a global network leader.

The Quantum Computing market was dominated by International Business Machines (US), D-Wave Systems (Canada), Microsoft (US), Amazon (US), and Rigetti Computing (US).