What is a quantum computer?

What is quantum computing? Everything you need to know about the strange world of quantum computers

Google, IBM, Microsoft, Amazon are all looking into it, but quantum computing is still widely misunderstood. This is everything you need to know about the next stage of computing, and everything that it could unlock.

While researchers don't understand everything about the quantum world, what they do know is that quantum particles hold immense potential, in particular to hold and process large amounts of information.

What is quantum computing and how does it work?

Quantum computing exploits the puzzling behavior that scientists have been observing for decades in nature's smallest particles – think atoms, photons or electrons. At this scale, the classical laws of physics ceases to apply, and instead we shift to quantum rules.

While researchers don't understand everything about the quantum world, what they do know is that quantum particles hold immense potential, in particular to hold and process large amounts of information. Successfully bringing those particles under control in a quantum computer could trigger an explosion of compute power that would phenomenally advance innovation in many fields that require complex calculations, like drug discovery, climate modelling, financial optimization or logistics.

As Bob Sutor, chief quantum exponent at IBM, puts it: "Quantum computing is our way of emulating nature to solve extraordinarily difficult problems and make them tractable," he tells ZDNet.

What is a quantum computer?

Quantum computers come in various shapes and forms, but they are all built on the same principle: they host a quantum processor where quantum particles can be isolated for engineers to manipulate.

The nature of those quantum particles, as well as the method employed to control them, varies from one quantum computing approach to another. Some methods require the processor to be cooled down to freezing temperatures, others to play with quantum particles using lasers – but share the goal of finding out how to best exploit the value of quantum physics.

What's the difference between a quantum computer and a classical computer?

The systems we have been using since the 1940s in various shapes and forms – laptops, smartphones, cloud servers, supercomputers – are known as classical computers. Those are based on bits, a unit of information that powers every computation that happens in the device.

In a classical computer, each bit can take on either a value of one or zero to represent and transmit the information that is used to carry out computations. Using bits, developers can write programs, which are sets of instructions that are read and executed by the computer.

Classical computers have been indispensable tools in the past few decades, but the inflexibility of bits is limiting. As an analogy, if tasked with looking for a needle in a haystack, a classical computer would have to be programmed to look through every single piece of hay straw until it reached the needle.

There are still many large problems, therefore, that classical devices can't solve. "There are calculations that could be done on a classical system, but they might take millions of years or use more computer memory that exists in total on Earth," says Sutor. "These problems are intractable today."

How do quantum computers improve on classical devices?

At the heart of any quantum computer are qubits, also known as quantum bits, and which can loosely be compared to the bits that process information in classical computers.

Qubits, however, have very different properties to bits, because they are made of the quantum particles found in nature – those same particles that have been obsessing scientists for many years.

One of the properties of quantum particles that is most useful for quantum computing is known as superposition, which allows quantum particles to exist in several states at the same time. The best way to imagine superposition is to compare it to tossing a coin: instead of being heads or tails, quantum particles are the coin while it is still spinning.

By controlling quantum particles, researchers can load them with data to create qubits – and thanks to superposition, a single qubit doesn't have to be either a one or a zero, but can be both at the same time. In other words, while a classical bit can only be heads or tails, a qubit can be, at once, heads and tails.

This means that, when asked to solve a problem, a quantum computer can use qubits to run several calculations at once to find an answer, exploring many different avenues in parallel.

So in the needle-in-a-haystack scenario about, unlike a classical machine, a quantum computer could in principle browse through all hay straws at the same time, finding the needle in a matter of seconds rather than looking for years – even centuries – before it found what it was searching for.

What's more: qubits can be physically linked together thanks to another quantum property called entanglement, meaning that with every qubit that is added to a system, the device's capabilities increase exponentially – where adding more bits only generates linear improvement.

Every time we use another qubit in a quantum computer, we double the amount of information and processing ability available for solving problems. So by the time we get to 275 qubits, we can compute with more pieces of information than there are atoms in the observable universe. And the compression of computing time that this could generate could have big implications in many use cases.

Quantum computers are all built on the same principle: they host a quantum processor where quantum particles can be isolated for engineers to manipulate.

Why is quantum computing so important?

"There are a number of cases where time is money. Being able to do things more quickly will have a material impact in business," Scott Buchholz, managing director at Deloitte Consulting, tells ZDNet.

The gains in time that researchers are anticipating as a result of quantum computing are not of the order of hours or even days. We're rather talking about potentially being capable of calculating, in just a few minutes, the answer to problems that today's most powerful supercomputers couldn't resolve in thousands of years, ranging from modelling hurricanes all the way to cracking the cryptography keys protecting the most sensitive government secrets.

And businesses have a lot to gain, too. According to recent research by Boston Consulting Group (BCG), $5 to $10 billion of which will be generated in the next five years if key vendors deliver on the technology as they have promised.

What is a quantum computer used for?

Programmers write problems in the form of algorithms for classical computers to resolve – and similarly, quantum computers will carry out calculations based on quantum algorithms. Researchers have already identified that some quantum algorithms would be particularly suited to the enhanced capabilities of quantum computers.

For example, quantum systems could tackle optimization algorithms, which help identify the best solution among many feasible options, and could be applied in a wide range of scenarios ranging from supply chain administration to traffic management. ExxonMobil and IBM, for instance, are working together to find quantum algorithms to reduce the distance and time traveled by fleets.

Quantum simulation algorithms are also expected to deliver unprecedented results, as qubits enable researchers to handle the simulation and prediction of complex interactions between molecules in larger systems, which could lead to faster breakthroughs in fields like materials science and drug discovery.

With quantum computers capable of handling and processing much larger datasets,

with faster training times and more capable algorithms. And researchers have also demonstrated that quantum algorithms which for now are too mathematically difficult for classical computers to break.

What are the different types of quantum computers?

To create qubits, which are the building blocks of quantum computers, scientists have to find and manipulate the smallest particles of nature – tiny parts of the universe that can be found thanks to different mediums. This is why there are currently many types of quantum processors being developed by a range of companies.

One of the most advanced approaches consists of using superconducting qubits, which are made of electrons, and come in the form of the familiar chandelier-like quantum computers. Both IBM and Google have developed superconducting processors.

Another approach that is gaining momentum is trapped ions, which Honeywell and IonQ are leading the way on, and in which qubits are housed in arrays of ions that are trapped in electric fields and then controlled with lasers.

Major companies like Xanadu and PsiQuantum, for their part, are investing in yet another method that relies on quantum particles of light, called photons, to encode data and create qubits. Qubits can also be created out of silicon spin qubits – which Intel is focusing on – but also cold atoms or even diamonds.

Quantum annealing, an approach that was chosen by D-Wave, is a different category of computing altogether. It doesn't rely on the same paradigm as other quantum processors, known as the gate model. Quantum annealing processors are much easier to control and operate, which is why D-Wave has already developed devices that can manipulate thousands of qubits, where virtually every other quantum hardware company is working with about 100 qubits or less. On the other hand, the annealing approach is only suitable for a specific set of optimization problems, which limits its capabilities.

Both IBM and Google have developed superconducting processors.

What can you do with a quantum computer today?

Right now, with a mere 100 qubits being the state of the art, there is very little that can actually be done with quantum computers. For qubits to start carrying out meaningful calculations, they will have to be counted in the thousands, and even millions.

"While there is a tremendous amount of promise and excitement about what quantum computers can do one day, I think what they can do today is relatively underwhelming," says Buchholz.

Increasing the qubit count in gate-model processors, however, is incredibly challenging. This is because keeping the particles that make up qubits in their quantum state is difficult – a little bit like trying to keep a coin spinning without falling on one side or the other, except much harder.

Keeping qubits spinning requires isolating them from any environmental disturbance that might cause them to lose their quantum state. Google and IBM, for example, do this by placing their superconducting processors in temperatures that are colder than outer space, which in turn require sophisticated cryogenic technologies that are currently near-impossible to scale up.

In addition, the instability of qubits means that they are unreliable, and still likely to cause computation errors. This has

Although research is advancing at pace, therefore, quantum computers are for now stuck in what is known as the NISQ era: noisy, intermediate-scale quantum computing – but the end-goal is to build a fault-tolerant, universal quantum computer.

As Buchholz explains, it is hard to tell when this is likely to happen. "I would guess we are a handful of years from production use cases, but the real challenge is that this is a little like trying to predict research breakthroughs," he says. "It's hard to put a timeline on genius."

What is quantum supremacy?

In 2019, Google claimed at its 54-qubit superconducting processor called Sycamore had achieved quantum supremacy – the point at which a quantum computer can solve a computational task that is impossible to run on a classical device in any realistic amount of time.

Google said that Sycamore has calculated, in only 200 seconds, the answer to a problem that would have taken the world's biggest supercomputers 10,000 years to complete.

More recently, saying that their quantum processor had taken 200 seconds to achieve a task that would have taken 600 million years to complete with classical devices.

This is far from saying that either of those quantum computers are now capable of outstripping any classical computer at any task. In both cases, the devices were programmed to run very specific problems, with little usefulness aside from proving that they could compute the task significantly faster than classical systems.

Without a higher qubit count and better error correction, proving quantum supremacy for useful problems is still some way off.

What is the use of quantum computers now?

Organizations that are investing in quantum resources see this as the preparation stage: their scientists are doing the groundwork to be ready for the day that a universal and fault-tolerant quantum computer is ready.

In practice, this means that they are trying to discover the quantum algorithms that are most likely to show an advantage over classical algorithms once they can be run on large-scale quantum systems. To do so, researchers typically try to prove that quantum algorithms perform comparably to classical ones on very small use cases, and theorize that as quantum hardware improves, and the size of the problem can be grown, the quantum approach will inevitably show some significant speed-ups.

For example, scientists at Japanese steel manufacturer Nippon Steel recently came up with a quantum optimization algorithm that could compete against its classical counterpart for a small problem that was run on a 10-qubit quantum computer. In principle, this means that the same algorithm equipped with thousands or millions of error-corrected qubits could eventually optimize the company's entire supply chain, complete with the management of dozens of raw materials, processes and tight deadlines, generating huge cost savings.

The work that quantum scientists are carrying out for businesses is, therefore, highly experimental, and so far there are fewer than 100 quantum algorithms that have been shown to compete against their classical equivalents – which only points to how emergent the field still is.

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Who is going to win the quantum computing race?

With most use cases requiring a fully error-corrected quantum computer, just who will deliver one first is the question on everyone's lips in the quantum industry, and it is impossible to know the exact answer.

All quantum hardware companies are keen to stress that their approach will be the first one to crack the quantum revolution, making it even harder to discern noise from reality. "The challenge at the moment is that it's like looking at a group of toddlers in a playground and trying to figure out which one of them is going to win the Nobel Prize," says Buchholz.

"I have seen the smartest people in the field say they're not really sure which one of these is the right answer. There are more than half a dozen different competing technologies and it's still not clear which one will wind up being the best, or if there will be a best one," he continues.

In general, experts agree that the technology will not reach its full potential until after 2030. The next five years, however, may start bringing some early use cases as error correction improves and qubit counts start reaching numbers that allow for small problems to be programmed.

IBM is one of the rare companies that has committed to a specific quantum roadmap, which defines the ultimate objective of realizing a million-qubit quantum computer. In the nearer term, Big Blue anticipates that it will release a 1,121-qubit system in 2023, which might mark the start of the first experimentations with real-world use cases.

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In general, experts agree that quantum computers will not reach their full potential until after 2030.

Image: IBM

What about quantum software?

Developing quantum hardware is a huge part of the challenge, and arguably the most significant bottleneck in the ecosystem. But even a universal fault-tolerant quantum computer would be of little use without the matching quantum software.

"Of course, none of these online facilities are much use without knowing how to 'speak' quantum," Andrew Fearnside, senior associate specializing in quantum technologies at intellectual property firm Mewburn Ellis, tells ZDNet.

Creating quantum algorithms is not as easy as taking a classical algorithm and adapting it to the quantum world. Quantum computing, rather, requires a brand-new programming paradigm that can only be run on a brand-new software stack.

Of course, some hardware providers also develop software tools, the most established of which is IBM's open-source quantum software development kit Qiskit. But on top of that, the quantum ecosystem is expanding to include companies dedicated exclusively to creating quantum software. Familiar names include Zapata, QC Ware or 1QBit, which all specialize in providing businesses with the tools to understand the language of quantum.

And increasingly, promising partnerships are forming to bring together different parts of the ecosystem. For example, the recent alliance between Honeywell, which is building trapped ions quantum computers, and quantum software company Cambridge Quantum Computing (CQC), has got analysts predicting that a new player could be taking a lead in the quantum race.

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What is cloud quantum computing?

The complexity of building a quantum computer – think ultra-high vacuum chambers, cryogenic control systems and other exotic quantum instruments – means that the vast majority of quantum systems are currently firmly sitting in lab environments, rather than being sent out to customers' data centers.

To let users access the devices to start running their experiments, therefore, quantum companies have launched commercial quantum computing cloud services, making the technology accessible to a wider range of customers.

The four largest providers of public cloud computing services currently offer access to quantum computers on their platform. IBM and Google have both put their own quantum processors on the cloud, while Microsoft's Azure Quantum and AWS's Braket service let customers access computers from third-party quantum hardware providers.

What does the quantum computing industry look like today?

The jury remains out on which technology will win the race, if any at all, but one thing is for certain: the quantum computing industry is developing fast, and investors are generously funding the ecosystem. Equity investments in quantum computing nearly tripled in 2020, and according to BCG, they are set to rise even more in 2021 to reach $800 million.

Government investment is even more significant: the US has unlocked $1.2 billion for quantum information science over the next five years, while the EU announced a €1 billion ($1.20 billion) quantum flagship. The UK for quantum technologies, and while official numbers are not known in China.

This has caused the quantum ecosystem to flourish over the past years, with new startups increasing from a handful in 2013 to nearly 200 in 2020. The appeal of quantum computing is also increasing among potential customers: according to analysis firm Gartner,

Who is getting quantum-ready now?

Although not all businesses need to be preparing themselves to keep up with quantum-ready competitors, there are some industries where quantum algorithms are expected to generate huge value, and where leading companies are already getting ready.

Goldman Sachs and JP Morgan are two examples of financial behemoths investing in quantum computing. That's because in banking, quantum optimization algorithms could give a boost to portfolio optimization, by better picking which stocks to buy and sell for maximum return.

In pharmaceuticals, where the drug discovery process is on average a $2 billion, 10-year-long deal that largely relies on trial and error, quantum simulation algorithms are also expected to make waves. This is also the case in materials science: companies like OTI Lumionics, for example, are exploring the use of quantum computers to design more efficient OLED displays.

Leading automotive companies including Volkswagen and BMW are also keeping a close eye on the technology, which could impact the sector in various ways, ranging from designing more efficient batteries to optimizing the supply chain, through to better management of traffic and mobility. Volkswagen, for example, pioneered the use of a quantum algorithm that optimised bus routes in real time by dodging traffic bottlenecks.

As the technology matures, however, it is unlikely that quantum computing will be limited to a select few. Rather, analysts anticipate that virtually all industries have the potential to benefit from the computational speedup that qubits will unlock.

There are some industries where quantum algorithms are expected to generate huge value, and where leading companies are already getting ready.

Image: IBM

Will quantum computers replace our laptops?

Quantum computers are expected to be phenomenal at solving a certain class of problems, but that doesn't mean that they will be a better tool than classical computers for every single application. Particularly, quantum systems aren't a good fit for fundamental computations like arithmetic, or for executing commands.

"Quantum computers are great constraint optimizers, but that's not what you need to run Microsoft Excel or Office," says Buchholz. "That's what classical technology is for: for doing lots of maths, calculations and sequential operations."

In other words, there will always be a place for the way that we compute today. It is unlikely, for example, that you will be streaming a Netflix series on a quantum computer anytime soon. Rather, the two technologies will be used in conjunction, with quantum computers being called for only where they can dramatically accelerate a specific calculation.

How will we use quantum computers?

Buchholz predicts that, as classical and quantum computing start working alongside each other, access will look like a configuration option. Data scientists currently have a choice of using CPUs or GPUs when running their workloads, and it might be that quantum processing units (QPUs) join the list at some point. It will be up to researchers to decide which configuration to choose, based on the nature of their computation.

Although the precise way that users will access quantum computing in the future remains to be defined, one thing is certain: they are unlikely to be required to understand the fundamental laws of quantum computing in order to use the technology.

"People get confused because the way we lead into quantum computing is by talking about technical details," says Buchholz. "But you don't need to understand how your cellphone works to use it.

"People sometimes forget that when you log into a server somewhere, you have no idea what physical location the server is in or even if it exists physically at all anymore. The important question really becomes what it is going to look like to access it."

And as fascinating as qubits, superposition, entanglement and other quantum phenomena might be, for most of us this will come as welcome news.

Ways quantum computing is going to change the world

Businesses are already exploring the future potential of quantum computers, and some industries anticipate big changes ahead.

From simulating new and more efficient materials to predicting how the stock market will change with greater precision, the ramifications of quantum computing for businesses are potentially huge.

The world's biggest companies are now launching

quantum computing programs

, and governments are pouring money into quantum research. For systems that have yet prove useful, quantum computers are certainly garnering lots of attention.

The reason is that quantum computers, although still far from having reached maturity, are expected to eventually usher in a whole new era of computing -- one in which the hardware is no longer a constraint when resolving complex problems, meaning that some calculations that would take years or even centuries for classical systems to complete could be achieved in minutes.

From simulating new and more efficient materials to predicting how the stock market will change with greater precision, the ramifications for businesses are potentially huge. Here are eight quantum use cases that leading organisations are exploring right now, which could radically change the game across entire industries.

1. DISCOVERING NEW DRUGS

The discovery of new drugs relies in part on a field of science known as molecular simulation, which consists of modelling the way that particles interact inside a molecule to try and create a configuration that's capable of fighting off a given disease.

Those interactions are incredibly complex and can assume many different shapes and forms, meaning that accurate prediction of the way that a molecule will behave based on its structure requires huge amounts of calculation.

Doing this manually is impossible, and the size of the problem is also too large for today's classical computers to take on. In fact, it's expected that modelling a molecule with only 70 atoms would take a classical computer up to 13 billion years.

This is why discovering new drugs takes so long: scientists mostly adopt a trial-and-error approach, in which they test thousands of molecules against a target disease in the hope that a successful match will eventually be found.

Quantum computers, however, have the potential to one day resolve the molecular simulation problem in minutes. The systems are designed to be able to carry out many calculations at the same time, meaning that they could seamlessly simulate all of the most complex interactions between particles that make up molecules, enabling scientists to rapidly identify candidates for successful drugs.

This would mean that life-saving drugs, which currently take an average 10 years to reach the market, could be designed faster -- and much more cost-efficiently.

Pharmaceutical companies are paying attention: earlier this year, healthcare giant Roche announced a partnership with Cambridge Quantum Computing (CQC) to support efforts in research tackling Alzheimer's disease.

And smaller companies are also taking interest in the technology. Synthetic biology start-up Menten AI, for example, has partnered with quantum annealing company D-Wave to explore how quantum algorithms could help design new proteins that could eventually be used as therapeutic drugs.

2. CREATING BETTER BATTERIES

From powering cars to storing renewable energy, batteries are already supporting the transition to a greener economy, and their role is only set to grow. But they are far from perfect: their capacity is still limited, and so is their charging speed, which means that they are not always a suitable option.

One solution consists of searching for new materials with better properties to build batteries. This is another molecular simulation problem -- this time modelling the behaviour of molecules that could be potential candidates for new battery materials.

Similar to drug design, therefore, battery design is another data-heavy job that's better suited to a quantum computer than a classical device.

This is why German car manufacturer Daimler has now partnered with IBM to assess how quantum computers could help simulate the behaviour of sulphur molecules in different environments, with the end-goal of building lithium-sulphur batteries that are better-performing, longer-lasting and less expensive that today's lithium-ion ones.

3. PREDICTING THE WEATHER

Despite the vast amounts of compute power available from today's cutting-edge supercomputers, weather forecasts -- particularly longer-range ones -- can still be disappointingly inaccurate. This is because there are countless ways that a weather event might manifest itself, and classical devices are incapable of ingesting all of the data required for a precise prediction

On the other hand, just as quantum computers could simulate all of the particle interactions going on within a molecule at the same time to predict its behaviour, so could they model how innumerable environmental factors all come together to create a major storm, a hurricane or a heatwave.

And because quantum computers would be able to analyse virtually all of the relevant data at once, they are likely to generate predictions that are much more accurate than current weather forecasts. This isn't only good for planning your next outdoor event: it could also help governments better prepare for natural disasters, as well as support climate-change research.

Research in this field is quieter, but partnerships are emerging to take a closer look at the potential of quantum computers. Last year, for instance, the European Centre for Medium-Range Weather Forecasts (ECMWF) launched a partnership with IT company Atos that included access to Atos's quantum computing simulator, in a bid to explore how quantum computing may impact weather and climate prediction in the future.

4. PICKING STOCKS

JP Morgan, Goldman Sachs and Wells Fargo are all actively investigating the potential of quantum computers to improve the efficiency of banking operations -- a use case often put forward as one that could come with big financial rewards.

There are several ways that the technology could support the activities of banks, but one that's already showing promise is the application of quantum computing to a procedure known as Monte Carlo simulation.

The Monte Carlo operation consists of pricing financial assets based on how the price of related assets changes over time, meaning that it's necessary to account for the risk inherent in different options, stocks, currencies and commodities. The procedure essentially boils down to predicting how the market will evolve -- an exercise that becomes more accurate with larger amounts of relevant data.

Quantum computers' unprecedented computation abilities could speed up Monte Carlo calculations by up to 1,000 times, according to research carried out by Goldman Sachs together with quantum computing company QC Ware. In even more promising news, Goldman Sachs' quantum engineers have now tweaked their algorithms to be able to run the Monte Carlo simulation on quantum hardware that could be available in as little as five years' time.

5. PROCESSING LANGUAGE

For decades, researchers have tried to teach classical computers how to associate meaning with words to try and make sense of entire sentences. This is a huge challenge given the nature of language, which functions as an interactive network: rather than being the 'sum' of the meaning of each individual word, a sentence often has to be interpreted as a whole. And that's before even trying to account for sarcasm, humour or connotation.

As a result, even state-of-the-art natural language processing (NLP) classical algorithms can still struggle to understand the meaning of basic sentences. But researchers are investigating whether quantum computers might be better suited to representing language as a network -- and, therefore, to processing it in a more intuitive way.

The field is known as quantum natural language processing (QNLP), and is a key focus of Cambridge Quantum Computing (CQC). The company has already experimentally shown that sentences can be parameterised on quantum circuits, where word meanings can be embedded according to the grammatical structure of the sentence. More recently, CQC released lambeq, a software toolkit for QNLP that can convert sentences into a quantum circuit.

6. HELPING TO SOLVE THE TRAVELLING SALESMAN PROBLEM

A salesman is given a list of cities they need to visit, as well as the distance between each city, and has to come up with the route that will save the most travel time and cost the least money. As simple as it sounds, the 'travelling salesman problem' is one that many companies are faced with when trying to optimise their supply chains or delivery routes.

With every new city that is added to the salesman list, the number of possible routes multiplies. And at the scale of a multinational corporation, which is likely to be dealing with hundreds of destinations, a few thousand fleets and strict deadlines, the problem becomes much too large for a classical computer to resolve in any reasonable time.

Energy giant ExxonMobil, for example, has been trying to optimise the daily routing of merchant ships crossing the oceans -- that is, more than 50,000 ships carrying up to 200,000 containers each, to move goods with a total value of $14 trillion.

Some classical algorithms exist already to tackle the challenge. But given the huge number of possible routes to explore, the models inevitably have to resort to simplifications and approximations. ExxonMobil, therefore, teamed up with IBM to find out if quantum algorithms could do a better job.

Quantum computers' ability to take on several calculations at once means that they could run through all of the different routes in tandem, allowing them to discover the most optimal solution much faster than a classical computer, which would have to evaluate each option sequentially.

ExxonMobil's results seem promising: simulations suggest that IBM's quantum algorithms could provide better results than classical algorithms once the hardware has improved.

7. REDUCING CONGESTION

Optimising the timing of traffic signals in cities, so that they can adapt to the number of vehicles waiting or the time of day, could go a long way towards smoothing the flow of vehicles and avoiding congestion at busy intersections.

This is another problem that classical computers find hard: the more variables there are, the more possibilities have to be computed by the system before the best solution is found. But as with the travelling salesman problem, quantum computers could assess different scenarios at the same time, reaching the most optimal outcome a lot more rapidly.

Microsoft has been working on this use case together with Toyoto Tsusho and quantum computing startup Jij. The researchers have begun developing quantum-inspired algorithms in a simulated city environment, with the goal of reducing congestion. According to the experiment's latest results, the approach could bring down traffic waiting times by up to 20%.

8. PROTECTING SENSITIVE DATA

Modern cryptography relies on keys that are generated by algorithms to encode data, meaning that only parties granted access to the key have the means to decrypt the message. The risk, therefore, is two-fold: hackers can either intercept the cryptography key to decipher the data, or they can use powerful computers to try and predict the key that has been generated by the algorithm.

This is because classical security algorithms are deterministic: a given input will always produce the same output, which means that with the right amount of compute power, a hacker can predict the result.

This approach requires extremely powerful computers, and isn't considered a near-term risk for cryptography. But hardware is improving, and security researchers are increasingly warning that more secure cryptography keys will be needed at some point in the future.

One way to strengthen the keys, therefore, is to make them entirely random and illogical -- in other words, impossible to guess mathematically.

And as it turns out, randomness is a fundamental part of quantum behaviour: the particles that make up a quantum processor, for instance, behave in completely unpredictable ways. This behaviour can, therefore, be used to determine cryptography keys that are impossible to reverse-engineer, even with the most powerful supercomputer.

Random number generation is an application of quantum computing that is already nearing commercialisation. UK-based startup Nu Quantum, for example, is finalizing a system that can measure the behavior of quantum particles to generate streams of random numbers that can then be used to build stronger cryptography keys.

Quantum computing is just getting going. But the hype could bring everything crashing down

From drug discovery to climate change, quantum computers have been pitched as a transformative solution to all sorts of business problems. But calls are mounting from within the field to distinguish hype from reality.

For many scientists working in the field, the keen interest that investors and CIOs are taking in quantum computing is a double-edged sword.

The idea that quantum computers will transform business and usher in a new era of unprecedented computing power is increasingly making its way into executive pitches as a marker of forward-thinking and innovation, with the technology often touted as the new must-have that could deliver a competitive edge.

But for many scientists working in the field, the keen interest that investors and CIOs are taking in quantum computing is a double-edged sword. While quantum computers eventually need to move out of labs and into businesses, the technology's commercialisation might be happening too soon, they warn, running the risk of relegating quantum computing to the much-dreaded 'over-hyped' category, along with virtual reality, blockchain or NFTs.

It's not that quantum computing isn't interesting. From a scientific perspective, it's hugely exciting -- which is why research has been ongoing in the field for decades.

In the early 90s, scientists were already getting excited about the idea of using quantum mechanics to build next-generation computers. This is because it had been observed that when particles in their smallest, quantum, state behave very differently to the way the laws of classical physics dictate.

For example, quantum particles can exist in various different states at the same time, in a sort of dual reality. That property, imagined scientists at the time, could be leveraged in the context of computing, with quantum particles able to carry different data in parallel, instead of being restricted, like the classical computer bit, to either a one or a zero. The idea of the quantum bit, or qubit, was born.

Armed with qubits, a computer could theoretically tackle hugely complex problems in no time, since different calculations could be carried out simultaneously in multiple parallel 'realities'.

"In principle, we've known as a community since the early 90s that quantum computing can solve problems that are hard for classical computers," said Bill Fefferman, assistant professor in the computer science department at the University of Chicago. "Those were theoretical results -- no experiments came with that. We were just saying that in principle, if a perfect quantum computer was ever built, it could do these things."

Fast-forward to the present day, and we are now seeing early prototypes of small-scale quantum computers -- systems that can control a small number of qubits, although usually not any more than 100 or so. The most powerful quantum machines built by IBM, for example, which is one of the most prominent investors in the field, currently boast 65 qubits.

With such few qubits, there is very little that quantum computers can actually do: researchers estimate that up to one million qubits, and potentially even more, would be necessary to build the perfect quantum system that engineers were dreaming up in the 90s. But scientists can still experiment with today's small-scale machines to hypothesise how things might turn out once the technology is more advanced, and the results they are seeing so far seem promising.

Chemical engineers, for example, are anticipating that quantum computers will be able to simulate large and complex molecules to predict the combinations that will best fight off disease in order to create life-saving drugs much faster; banking giants are counting on quantum systems to determine the best stocks to buy and sell for maximum return, based on calculations that can account for many more fast-changing factors; and car manufacturers are testing how the technology could revolutionise the design of batteries, the optimisation of supply chains or the management of traffic in dense, urban settings.

These early experiments are generating a lot of enthusiasm across fields that range from oil and gas to logistics, through cybersecurity, agriculture and even weather forecasting. Every single industry, some experts claim, is set to be transformed by the technology once it reaches maturity.

"Early experiments hint that this technology will hold the promise to solve very interesting problems that cannot be solved classically," says Fefferman.

It hasn't taken long for investors to take note. The quantum computing industry is flourishing, largely driven by deep-pocketed tech giants IBM and Google. They have now been joined by Amazon and Microsoft, which have both launched their own quantum programs, as well as scores of smaller companies

There are now nearly 200 quantum computing start-ups on the market, offering services in quantum software and hardware, and promising huge business improvements once the quantum revolution kicks in. The first publicly-traded firm dedicated to quantum computers, IonQ,

But some experts are now expressing doubts about the viability of this industry. For Sabine Hossenfelder, a researcher in theoretical physics at the Frankfurt Institute for Advanced Studies, the quantum computing industry is experiencing a bubble in the making -- and the consequences could be greatly detrimental to research.

"I work in basic research, and from my perspective all of the early applications of quantum are super exciting," Hossenfelder tells ZDNet. "But a lot of the stuff I read is unreasonably optimistic."

"The risk that I see is that you have all these investors who like the idea that soon enough we'll have a great quantum computer and we will make money with it because we'll solve all these problems -- but in five years or so they will realise these promises didn't pan out. Then they will pull out and it will be really hard to continue, even on the research side, because the bubble will dramatically deflate."

For Hossenfelder, the problem is mostly to do with the timeline. Hitting the one million qubit mark is a huge technical challenge, given the current less-than-100-qubit state-of-the-art. It's not only about successfully creating and controlling more qubits: engineers also have to think about ways to reduce the space needed to fit all of the equipment that's necessary to run the system. Current quantum computers already fill rooms-worth of machinery and tools; making the devices orders of magnitude larger with current technologies is simply unrealistic.

The next few years won't bring all of the technical solutions to these problems, argues Hossenfelder, comparing the challenge to building a modern-day PC a century ago and equipped only with wood.

And even if they do, even if there is a team working in secret on a new approach that could solve all of the existing bottlenecks in the next five to 10 years, it is far from certain that quantum computers will beat classical computers on all fronts. Quite the contrary: quantum systems are expected to be transformative for specific use cases, particularly simulation, but it's unlikely that they will be replacing our current laptops anytime soon.

"We have to be careful that we talk about them in an accurate way," says Fefferman. "Quantum computers are not a panacea; they won't be able to speed up all problems. There will be certain problems which even 30 or 100 years from now, when a perfect quantum computer exists, it won't be good at solving."

There is every indication that classical computers are here to stay, and that they will still be used for many tasks -- if not most of them. Quantum computers, in contrast, will be more of a special-purpose device that will generate extreme speed-ups on a set of very specific problems. What scientists are doing today, is trying to discover what exactly these problems might be.

So, where does the quantum computing industry hype start -- and end? "The high-level answer is there's definitely a fine
line," says Fefferman. There are many research teams with legitimate goals, as well as many businesses developing products that could be game-changing. But there are also a lot of companies riding the system and selling what has become known as "quantum snake oil".

Fefferman is not alone in warning against the unrealistic expectations that are being set for quantum computing. Computer scientist Scott Aaronson, for example, is a prominent critic of this bubble in the making, who writes in his that the call is now coming from inside the house, meaning that quantum scientists themselves are worrying about the proportions that the quantum field is prematurely reaching.

Hype isn't fundamentally bad for quantum computing: the industry needs commercial interest if it's to leave the realm of academia and achieve the dream born in the 90s. The danger lies in creating impossible-to-reach expectations too quickly -- in fact, in creating them at all. For scientists working in the field, this is only making the prospect of a 'quantum winter' all-too-imminent. The promise of quantum computing is certainly real; but realising it will require patience, and a strong degree of accountability.

Important Industry Functions Quantum Computing Could Soon Revolutionize

From AI to 5G, tech that once seemed as if it belonged in the realm of science fiction is starting to impact our everyday lives. The next sci-fi crossover may well be quantum computers.

Headlines on the accomplishments of supercomputers have popped up regularly in the past decade or so, with stories touting their help with issues ranging from predicting climate change and mapping the human bloodstream to defeating Jeopardy! champions. Through the use of multidimensional representation, quantum computers leave supercomputers in the dust. In 2019, Google’s quantum computer, Sycamore, took 200 seconds to perform a mathematical computation that would have taken IBM’s Summit supercomputer 10,000 years. That makes Sycamore about 158 million times faster than Summit.

The rise of quantum computing is an exciting development that could impact multiple facets of human life. So what might business and industry do with this technology? Below, eight experts from Forbes Technology Council share ways they foresee quantum computing revolutionizing the way companies operate.

1. Utilities Management

The supercomputing of the future is set to make disruptive changes in the energy and utility industry. From the quantum grid to cybersecurity, load pattern monitoring, leakage detection, and customer and workforce analytics, the technology will change the way billions of people consume energy and water and how utilities manage these precious resources. I’m very excited to watch these factors at play.

2. Advertising

Quantum computing will help companies leverage extremely large datasets, optimize bidding strategies for advertisements, and drastically improve machine learning and artificial intelligence. All this will improve real-time marketing strategies and allow advertisers to offer a level of ad personalization that’s unthinkable with traditional computing technologies.

3. Healthcare Research

Quantum computing will enable real-time healthcare research. Future research will be powered by new types of simulations that bring together many types of data not previously combined before, including sensors, images, genomics and real-world outcomes. All of this data will be updated continuously and dynamically. We will see the acceleration of drug discovery, proactive and predictive population health management, and truly personalized medicine (“N of 1”).

4. Supply Chain Management

It’s likely that the first way quantum computing will impact operations is in the supply chain. If Covid-19 showed us anything, it is that global supply chains are complicated and tenuous. Quantum computing will allow companies to maintain supply chains with fewer disruptions.

5. Pharmaceutical Development

Quantum computing operates on nonbinary principles that better resemble nature. Quantum computers could theoretically be faster at designing personalized drugs for a person with a given genome, age and environment. The permutations in this natural problem are large enough to require a new processing paradigm.

6. Autonomous Travel

Quantum computing is positioned to have a monumental effect on business, government and the individual lives of everyone in society today. From enabling intergalactic space flight to driving AI-powered autonomous vehicles, unbelievably fast computing capabilities paired with the ability to drive outcomes based on incredibly large data sets will be the differentiator for quantum computing.

7. Data Analysis

Quantum computing will significantly change the big data analysis process. Quantum computers can interpret and analyze voluminous data sets and perform data analytics at a more granular level than predictive machine learning algorithms can offer. Significantly, this will enable companies to generate useful insights for quick decision-making.

8. Fraud Detection

The second quantum computing revolution is here, but we’re still far from fully aware of what this tech can do. The awesome computing power of quantum devices can take optimizations, random checks and machine learning to new levels. In finance and cybersecurity, this means less risk and more muscle to detect fraud. Across industries, it means greater efficiency in examining patients, managing supply chains and more.

Which Industries Will Be Most Impacted By Quantum Computing?

Which industries will be most impacted by quantum computing?

There has been a lot of talk about a new era of supercomputers — known as “quantum computers” — that will infinitely expand the capabilities of traditional computers and outperform them on various axes, from speed to efficiency. For years now, I have been actively involved in the world of AI. Because quantum computing could have such a profound impact on how AI will grow in the future, I have followed the latest developments in quantum computers’ abilities.

Tech giants like IBM, Microsoft and Google have already taken big strides in the race to create the most potent quantum computer and achieve quantum supremacy — and their confidence in their own achievements is so high that Google, for example, has gone so far as to make a claim that the company has already achieved quantum supremacy, while IBM has made a promise to create a 1,000-qubit computer by 2023.

There is a fundamental difference between how traditional and quantum computers operate — and this difference can explain the new horizons that quantum computers could reach that were impossible to consider previously.

This essential difference comes down to the elements that computers operate on: Traditional computers operate on bits that only take the value of 0 or 1 — but never both at the same time. Traditional computers operate based on a binary system that, in many cases, does not match the uncertainty that the real world operates in despite a computer’s promised operational speed. Quantum computers, in contrast, operate on “qubits” — or “quantum bits” — that are not bound by traditional computers’ limitation to one of two states. Instead, qubits are able to take on two or more values at the same time — a quality otherwise known as “superposition.”

Without these traditional boundaries, quantum computers could operate at speeds faster than ever before, complete more tasks in shorter periods of time — and all simultaneously, as they’d hypothetically be freed of any limitations that traditional computers operate under.

With these new open doors and possibilities, there are a few industries that have the potential to undergo a significant transformation in the near future.

Chemical Industry

According to McKinsey, the capabilities of quantum computing will open the possibility of modeling particles “such as molecules, polymers, and solids, at a totally different level of precision. It would thus be possible to identify the most effective molecular designs or structures to accomplish specific tasks and achieve required effects — before synthesizing a single molecule in the lab.” For example, Cambridge Quantum Computing and JSR Corp have already used quantum computing to “model multi-reference states of molecules. Multi-reference states are often needed to describe the 'excited states' arising when molecules interact.”

Quantum computing could offer immense support to research and development in the chemical industry and could support the development of new products — as well as the discovery and study of the properties and behaviors of various molecular structures, according to Honeywell.

Healthcare And Drug Development

Drug discovery and development is a lengthy, costly process — it may take 10 years and over $2.5 billion to complete the process from discovery to commercialization. And even then, the success of the therapeutic drugs are not always guaranteed — in fact, by some estimates, the risk of failure is quite high.

Quantum computing could make it possible to minimize the risk of failure by accurately simulating and experimenting with various molecular compositions in order to evaluate the theoretical effectiveness of a therapeutic solution before full inception. Quantum computing could also accelerate the process of end-to-end testing and drug creation, making it possible to achieve breakthrough solutions more frequently and effectively — all while potentially decreasing the costs of drug testing and production. A number of companies, including Cloud Pharmaceuticals and ApexQubit, are already using quantum technologies for drug discovery and development.

Financial Services

Financial services have the potential to benefit from the efficacy and speed of quantum computing — especially in the areas of risk analysis, dynamic portfolio optimization and pricing, according to Bowery Capital.

While traditional computers can only search one file at a time or run single simulations of a portfolio at a time, a quantum computer could perform these operations simultaneously and suggest optimization options at a much higher speed. Quantum computing may also allow for greater prediction accuracy. Traditional algorithms calculating probabilities are far from infallible; quantum computers, due to their alleged ability to operate at lightning speed, could provide much faster and more accurate predictions. They could estimate risk in a more informed manner and continuously monitor behaviors and activities to identify anomalies or even prevent them from happening at any time.

Security

With quantum computers’ ability to analyze and decode data at very high speeds, the security of encrypted data known for being unbreakable today could render itself obsolete in the future. Quantum computers could simply break those with ease due to their power.

The solution to this risk may be quantum encryption — known as QKD, or quantum key distribution — which could maintain the privacy of data in a quantum-driven world. QKD relies on the properties of quantum physics to ensure that data can only be interpreted by two key parties and cannot be intercepted by a third party. Startups like QuantumLR are already offering quantum key solutions and services. Essentially, QKD uses photons to send data from one party to another. Only the two principal parties are able to decipher the properties of the photons; if a third party intercepts the transmission of data, the photons change their state, making it virtually impossible to decode the information exchanged between the two key endpoints.