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 CIO's guide to Quantum computing

Quantum computers offer great promise for cryptography and optimization problems, and companies are racing to make them practical for business use. ZDNet explores what quantum computers will and wont be able to do, and the challenges that remain.

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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.

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 thatmodelling 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) tosupport 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-Waveto explore how quantum algorithms could help design new proteins that could eventually be used as therapeutic drugs.

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.

SEE: There are two types of quantum computing. Now one company says it wants to offer both

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 Daimlerhas now partnered with IBMto 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.

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.

SEE: Scientists are using quantum computing to help them discover signs of life on other planets

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 Atosthat 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.

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.

SEE: Quantum computing is at an early stage. But investors are already getting excited

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 havenow tweaked their algorithmsto be able to run the Monte Carlo simulation on quantum hardware that could be available in as little as five years' time.

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 hasalready 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.

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.

SEE: Quantum computers could read all your encrypted data. This 'quantum-safe' VPN aims to stop that

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 IBMto 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.

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%.

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 particlesto generate streams of random numbers that can then be used to build stronger cryptography keys.

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Quantum computers: Eight ways quantum computing is going to change the world - ZDNet

On October 1 of this year, IonQ became the first pure-play quantum computing start-up to go public. At this writing, the stock (NYSE: IONQ) was around $15 and its market capitalization was roughly $2.89 billion. Co-founder and chief scientist Chris Monroe says it was fun to have a few of the companys roughly 100 employees travel to New York to ring the opening bell of the New York Stock Exchange. It will also be interesting to listen to IonQs first scheduled financial results call (Q3) on November 15.

IonQ is in the big leagues now. Wall Street can be brutal as well as rewarding, although these are certainly early days for IonQ as a public company. Founded in 2015 by Monroe and Duke researcher Jungsang Kim who is the company CTO IonQ now finds itself under a new magnifying glass.

How soon quantum computing will become a practical tool is a matter of debate, although theres growing consensus that it will, in fact, become such a tool. There are several competing flavors (qubit modality) of quantum computing being pursued. IonQ has bet that trapped ion technology will be the big winner. So confident is Monroe that he suggests other players with big bets on other approaches think superconducting, for example are waking up to ion traps advantages and are likely to jump into ion trap technology as direct competitors.

In a wide-ranging discussion with HPCwire, Monroe talked about ion technology and IonQs (roughly) three-step plan to scale up quickly; roadblocks facing other approaches (superconducting and photonic); how an IonQ system with about 1,200 physical qubits and home-grown error-correction will be able to tackle some applications; and why IonQ is becoming a software company and thats a good thing.

In ion trap quantum computing, ions are held in position by magnetic forces where they can be manipulated by laser beams. IonQ uses ytterbium (Yb) atoms. Once the atoms are turned into ions by stripping off one valence electron, IonQ use a specialized chip called alinear ion trap to hold the ions precisely in 3D space. Literally, they sort of float above the surface. This small trap features around 100 tiny electrodes precisely designed, lithographed, and controlled to produce electromagnetic forces that hold our ions in place, isolated from the environment to minimize environmental noise and decoherence, as described by IonQ.

It turns out ions have naturally longer coherence times and therefore require somewhat less error correction and are suitable for longer operations. This is the starting point for IonQs advantage. Another plus is that system requirements themselves are less complicated and less intrusive (noise producing) than systems for semiconductor-based, superconducting qubits think of the need to cram control cables into a dilution refrigerator to control superconducting qubits. That said, all of the quantum computing paradigms are plenty complicated.

For the moment, ion traps using lasers to interact with the qubits is one of the most straightforward approaches. It has its own scaling challenge but Monroe contends modular scaling will solve that problem and leverage ion traps other strengths.

Repeatability [in manufacturing superconducting qubits] is wonderful but we dont need atomic scale deposition, like you hear of with five nanometer feature sizes on the latest silicon chips, said Monroe. The atoms themselves are far away from the chips, theyre 100 microns, i.e. a 10th of a millimeter away, which is miles atomically speaking, so they dont really see all the little imperfections in the chip. I dont want to say it doesnt matter. We put a lot of care into the design and the fab of these chips. The glass trap has certain features; [for example] its actually a wonderful material for holding off high voltage compared to silicon.

IonQ started with silicon-based traps and is now moving to evaporated glass traps.

What is interesting is that weve built the trap to have several zones. This is one of our strategies for scale. Right now, at IonQ, we have exactly one chain of atoms, these are the qubits, and we typically have a template of about 32 qubits. Thats as many as we control. You might ask, how come youre not doing 3200 qubits? The reason is, if you have that many qubits, you better be able to perform lots and lots of operations and you need very high quality operations to get there. Right now, the quality of our operation is approaching 99.9%. That is a part per 1000 error, said Monroe.

This is sort of back of the envelope calculations but that would mean that you can do about 1000 ops. Theres an intuition here [that] if you have n qubits, you really want to do about n2 ops. The reason is, you want these pairwise operations, and you want to entangle all possible pairs. So if you have 30 qubits, you should be able to get to about 1000 ops. Thats sort of where we are now. The reason we dont have 3200 yet is that if you have 3200 qubits, you should be able to do 10 million ops and that means your noise should be one part in 107. Were not there yet. We have strategy to get there, said Monroe.

While you could put more ions in a trap, controlling them becomes more difficult. Long chains of ions become soft and squishy. A smaller chain is really stiff [and] much less noisy. So 32 is a good number. 16 might be a good number. 64 is a good number, but its going to be somewhere probably under 100 ions, said Monroe.

The first part of the strategy for scaling is to have multiple chains on a chip that are separated by a millimeter or so which prevents crosstalk and permits local operations. Its sort of like a multi-core classical architecture, like the multi-core Pentium or something like that. This may sound exotic, but we actually physically move the atoms, we bring them together, the multiple chains to connect them. Theres no real wires. This is sort of the first [step] in rolling out a modular scale-up, said Monroe.

In proof of concept work, IonQ announced the ability to arbitrarily move four chains of 16 atoms around in a trap, bringing them together and separating them without losing any of the atoms. It wasnt a surprise we were able to do that, said Monroe. But it does take some design in laying out the electrodes. Its exactly like surfing, you know, the atoms are actually surfing on an electric field wave, and you have to design and implement that wave. That was that was the main result there. In 2022, were going to use that architecture in one of our new systems to actually do quantum computations.

There are two more critical steps in IonQs plan for scaling. Error correction is one. Clustering the chips together into larger systems is the other. Monroe tackled the latter first.

Think about modern datacenters, where you have a bunch of computers that are hooked together by optical fibers. Thats truly modular, because we can kind of plug and play with optical fibers, said Monroe. He envisions something similar for trapped ion quantum computers. Frankly, everyone in the quantum computing community is looking at clustering approaches and how to use them effectively to scale smaller systems into larger ones.

This interface between individual atom qubits and photonic qubits has been done. In fact, my lab at University of Maryland did this for the first time in 2007. That was 14 years ago. We know how to do this, how to move memory quantum bits of an atom onto a propagating photon and actually, you do it twice. If you have a chip over here and a chip over here, you bring two fibers together, and they interfere and you detect the photons. That basically makes these two photons entangled. We know how to do that.

Once we get to that level, then were sort of in manufacturing mode, said Monroe. We can stamp out chips. We imagine having a rack-mounted chips, probably multicore. Maybe well have several 100 atoms on that chip, and a few of the atoms on the chip will be connected to optical conduits, and that allows us to connect to the next rack-mounted system, he said.

They key enabler, said Monroe, is a nonblocking optical switch. Think of it as an old telephone operator. They have, lets say they have 100 input ports and 100 output ports. And the operator connects, connects with any input to any output. Now, there are a lot of connections, a lot of possibilities there. But these things exist, these automatic operators using mirrors, and so forth. Theyre called n-by-n, nonblocking optical switches and you can reconfigure them, he said.

Whats cool about that is you can imagine having several hundred, rack-mounted, multi-core quantum computers, and you feed them into this optical switch, and you can then connect any multi-core chip to any other multi-core chip. The software can tell you exactly how you want to network. Thats very powerful as an architecture because we have a so-called full connection there. We wont have to move information to nearest neighbor and shuttle it around to swap; we can just do it directly, no matter where you are, said Monroe.

The third leg is error correction, which without question is a daunting challenge throughout quantum computing. The relative unreliability of qubits means you need many redundant physical qubits estimates vary widely on how many to have a single reliable logical qubit. Ions are among the better behaving qubits. For starters, all the ions are literally identical and not subject to manufacturing defects. A slight downside is that Ion qubit switching speed is slower than other modalities, which some observers say may hamper efficient error correction.

Said Monroe, The nice thing about trapped ion qubits is their errors are already pretty good natively. Passively, without any fancy stuff, we can get to three or four nines[i] before we run into problems.

What are those problems? I dont want to say theyre fundamental, but there are brick walls that require a totally different architecture to get around, said Monroe. But we dont need to get better than three or four nines because of error correction. This is sort of a software encoding. The price you pay for error correction, just like in classical error correction encoding, is you need a lot more bits to redundantly encode. The same is true in quantum. Unfortunately, with quantum there are many more ways you can have an error.

Just how many physical qubits are needed for a logical qubit is something of an open question.

It depends what you mean by logical qubit. Theres a difference in philosophy in the way were going forward compared to many other platforms. Some people have this idea of fault tolerant quantum computing, which means that you can compute infinitely long if you want. Its a beautiful theoretical result. If you encode in a certain way, with enough overhead, you can actually you can run gates as long as you want. But to get to that level, the overhead is something like 100,000 to one, [and] in some cases a million to one, but that logical qubit is perfect, and you get to go as far as you want [in terms of number of gate operations], he said.

IonQ is taking a different tack that leverages software more than hardware thanks to ions stability and less noisy overall support system [ion trap]. He likens improving qubit quality to buying a nine in the commonly-used five nines vernacular of reliability. Five nines 99.999 percent (five nines) is used describe availability, or put another way, time between shutdowns because of error.

Were going to gradually leak in error correction only as needed. So were going to buy a nine with an overhead of about 16 physical qubits to one logical qubit. With another overhead of 32 to one, we can buy another nine. By then we will have five nines and several 100 logical qubits. This is where things are going to get interesting, because then we can do algorithms that you cant simulate classically, [such] as some of these financial models were doing now. This is optimizing some function, but its doing better than the classical result. Thats where we think we will be at that point, he said.

Monroe didnt go into detail about exactly how IonQ does this, but he emphasized that software is the big driver now at IonQ. Our whole approach at IonQ is to throw everything up to software as much as we can. Thats because we have these perfectly replicable atomic qubits, and we dont have manufacturing errors, we dont have to worry about a yield or anything like that everything is a control problem.

So how big a system do you need to run practical applications?

Thats a really good question, because I can safely say we dont exactly know the answer to that. What we do know if you get to about 100 qubits, maybe 72, or something like that, and these qubits are good enough, meaning that you can do 10s of 1000s of ops. Remember, with 100 qubits you want to do about 10,000 ops to something you cant simulate classically. This is where you might deploy some machine learning techniques that you would never be able to do classically. Thats probably where the lowest hanging fruit are, said Monroe.

Now for us to get to 100 [good] qubits and say 50,000 Ops, that requires about 1000 physical qubits, maybe 1500 physical qubits. Were looking at 1200 physical qubits, and this might be 16 cores with 64 ions in each core before we have to go to photonic connections. But the photonic connection is the key because [its] where you start to have a truly modular data center. You can stamp these things out. At that point, were just going to be making these things like crazy, and wiring them together. I think well be able to do interesting things before we get to that stage and it will be important if we can show some kind of value (application results/progress) and that we have the recipe for scaling indefinitely, thats a big deal, he said.

It is probably going too far to say that Monroe believes scaling up IonQs quantum computer is now just a straightforward engineering task, but it sometimes sound that way. The biggest technical challenges, he suggests, are largely solved. Presumably, IonQ will successfully demonstrate its modular architecture in 2022. He said competing approaches superconducting and all-photonics, for example wont be able to scale. They are stuck, he said.

I think they will see atomic systems as being less exotic than they once thought. I mean, we think of computers as built from silicon and as solid state. For better for worse you have companies that that forgot that they supposed to build computers, not silicon or superconductors. I think were going to see a lot more fierce competition on our own turf, said Monroe. There are ion trap rivals. Honeywell is one such rival (Honeywell has announced plans to merge with Cambridge Quantum), said Monroe.

His view of the long-term is interesting. As science and hardware issues are solved, software will become the driver. IonQ already has a substantial software team. The company uses machine learning now to program its control system elements such as the laser pulses and connectivity. Were going to be a software company in the long haul, and Im pretty happy with that, said Monroe.

IonQ has already integrated with the three big cloud providers (AWS, Google, Microsoft) quantum offerings and embraced the growing ecosystem of software and tools providers and has APIs for use with a variety of tools. Monroe, like many in the quantum community, is optimistic but not especially precise about when practical applications will appear. Sometime in the next three years is a good guess, he suggests. As for which application area will be first, it may not matter in the sense that he thinks as soon as one domain shows benefit (e.g. finance or ML) other domains will rush in.

These are heady times at IonQ, as they are throughout quantum computing. Stay tuned.

[i] He likens improving qubit quality to buying a nine in the commonly-used five nines vernacular of reliability. Five nines 99.999 percent (five nines) is used describe availability, or put another way, time between shutdowns because of error.

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IonQ Is First Quantum Startup to Go Public; Will It be First to Deliver Profits? - HPCwire

David Cowan had already been an investor at Bessemer Venture Partners for 20 years when he came across an upstart company that was rapidly building an audience around a novel idea: Watching other people play video games. The company was called Twitch. Shortly thereafter, Cowan and Bessemer led a $15 million Series B investment in the business. Less than two years later, Amazon came calling with an acquisition offer Twitch and Cowan couldnt refuse. It was, in many ways, the dream scenario for a venture capitalist.

But it wasnt long before Cowan began to have regrets.

An early backer of Twitch, David Cowan is now investing in the transformative potential of quantum computers like this one.

I invested in the company at like a $65 million pre-money (valuation), Cowan says today. And then 18 months later I had the opportunity to sell it for a billion dollars. And I thought, Hurray. And that was a big mistake. Because, you know, only two years later, the company was clearly worth $10 billion.

Id say the biggest lesson of that was that I had to recalibrate my expectations for what successful companies can do."

These days, Cowan spends his days investing in areas like space technology, cybersecurity and sustainable agriculturesectors you might describe as deep tech or frontier tech. I spoke to him over Zoom this week about one particular investment thats been making headlines this month. And by the sounds of it, underestimating this companys potential is not going to be a problem.

Still a partner at Bessemer, Cowan is now also an investor in and a board member at Rigetti Computing, a quantum computing company that agreed to go public in early October by merging with a SPAC at a $1.5 billion valuation. Thats up from $129 million when Bessemer took its stake in the company last year.

Ive tried before to explain quantum computing, and you can certainly find other explanations elsewhere, so I wont go into too much detail here. Suffice it to say that quantum computers are a new kind of machine that exploits the inherent strangeness of very small particles to perform immensely complicated calculations, with the potential to be trillions of times more powerful than current supercomputers.

If the industry fulfills that potential, Cowan believes the consequences will be incredible.

I mean, simply put, curing cancer, he said.

Perhaps the most exciting applications of quantum computing are in medicine. There are trillions of atoms in each cell and trillions of cells in the human body, all interacting with each other in an unceasing biological dance. Current superconductors are seriously powerful machines, but unspooling that kind of choreography is beyond their reach.

Its also beyond the reach of modern quantum computers. The technology for these machines is still in its adolescence. Theoretically, though, a quantum computer could map the way molecules and data points interact in previously unimaginable ways. And doctors and researchers could use those maps to find new therapies and cures.

The potential is equally vast in a wide range of other industries.

Its not going to change how you get your scoop of ice cream from the local store, Cowan said. But anything that requires machine learning or optimization, or certainly anything that requires an understanding of physicslike biology, chemistry, materialsanything that involves simulation, like designing airplanes or cars, anything that uses heavy computation, which of course is lots and lots of interesting industriesall of those will get a huge boost."

Different companies are trying to build quantum computers in different ways. Rigettis technology is based in superconducting qubitsqubits being the quantum computing analog to the bits in a traditional computer. In Cowans view, Rigetti is engaged in a three-way race for supremacy in the superconductor space. You might have heard of its two rivals: Google and IBM.

But whats that old saying about the size of the dog in the fight?

David Cowan has been at Bessemer since 1992.

Why do I like Rigetti? Well, two reasons. One is that I can't buy a big piece of Google or IBM, Cowan said with a grin. But the second thing is that I've seen in many industries that, as formidable as the major tech companies are, a committed dedicated startup will usually out-innovate the tech giants. And so even though Google and IBM have more money and more people, I still believe that Rigetti is going to way outpace them."

Rigetti will bring in $458 million in proceeds from its SPAC merger to help fund its ongoing R&D and bring its quantum computing technology to market. Wall Street heavyweights T. Rowe Price and Franklin Templeton are both taking part in a $100 million PIPE investment to support the deal. So too is In-Q-Tel, the venture arm of the Central Intelligence Agency. And so too are Bessemer and Cowananother sign of his belief in Rigettis long-term potential.

Im a buyer, not a seller, Cowan said. This has the opportunity to become one of the massive tech companies on the planet. I mean, this is, this is no less important than the transistor for the 20th century in terms of computation."

It will be a while before we find out one way or the other. Quantum computers arent going to fully replace modern supercomputers any time soon. The technology is still developing. A lot could change for Rigetti over the next decade. One thing is certain, though: This time around, Cowan isnt going to have any regrets about cashing out early.

Who knows when, who knows how much money it'll take. It's a risky venture, Cowan said. But for this one, the payoff is worth it.

Excerpt from:
An Early Investor In Twitch Explains Why He's Betting Big On Quantum Computing - Forbes

A programmable photonic circuit has been developed that can execute various quantum algorithms and is potentially highly scalable. This device could pave the way for large-scale quantum computers based on photonic hardware. Image by . CC BY 2.5

A new report suggests China might be winning the race to build the most powerful quantum computers, based on the development of a 66-qubit programmable superconducting quantum computing system. This feat was performed at Hefei National Laboratory for Physical Sciences at the Microscale of the University of Science and Technology of China.

Whether the accelerating pace is truly in the hands of China is fact or hyperbole, this is something that will be borne out through future tests. Certainly interest in investing in quantum computing is at a high.

For instance, in a recent study from Classiq, it was found that 38 percent of respondents said that competitive advantage is the most beneficial outcome that would be realised from an effective quantum computing strategy. In addition, 82 percent of people said that they see quantum computing as a business necessity (as based on a survey of more than 500 U.S. professionals).

For business with an eye for the future, the same survey finds that this interest in quantum computing stands second only to an interest with virtual and augmented reality.

There remains, however, a key piece of the quantum arms race that is yet to be won, and few technologists have made advances towards it. This centres on software, according to Nir Minerbi, who is CEO at the company Classiq.

Minerbi tells Digital Journal that even Chinas latest quantum computer will be less remarkable without viable quantum software.

According to Minerbi, investing in quantum software is the next step in creating lasting competitive advantage in this arms race.

The technology leader explains: Whether because of the cybersecurity implications or just to get dramatically better at drug discovery, logistics or financial services, many countries understand the strategic advantage of having advanced quantum technology.

This is something that is subject to large amounts of investment globally, and Minerbi points out that China is certainly not an exception, as evidenced by billions of dollars in investment.

As to what such future-state technology might be used for, Minerbi speculates: If Chinas computer is as powerful as they say, it can be used for both good and bad purposes. It can be used to develop vaccines in record time, but such technology can eventually crack the encryption of the worlds financial transactions.

Either way, Minerbi notes: This next-generation hardware is useless without the ability to write sophisticated software to it. Software investments are another dimension in which certain countries can create lasting competitive advantage in this arms race.

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Software will become the final key to unlocking quantum computing power - Digital Journal

PARIS, Nov. 4, 2021 Pasqal, developers of neutral atom-based quantum technology, today announced it was named Startup of the Year by LUsine Nouvelle, a leading French business news site covering economic and industrial news across industries. LUsine Nouvelles awards programs honor innovations, individuals and projects that aim to solve societys biggest challenges.

Founded in 2019 as a spin-off from Institut dOptique, Pasqal was the first startup dedicated to quantum computing in France. The company is on an accelerated growth track and expects to grow from 40 employees to 100 by the end of 2022. Pasqal raised a 25 M Series A funding round in June 2021, one of the largest series A rounds in Europe for a deep tech startup. This award comes on the heels of a momentous year for Pasqal. In 2021, the company grew its employee base by 300%, adding 30 new team members from eight different regions.

This award recognizes Pasqals tremendous contributions to the quantum ecosystem. Pasqals initiatives are aligned with the French quantum national plan and the France 2030 investment plan which identified deep tech and quantum computing as critical industries for Frances success. Pasqal aims to solve real-word challenges through quantum technology and believes it will deliver a 1000-qubit quantum processor to the market in 2023, faster than the quantum development roadmaps of the tech giants in the field. Capable of operating at room temperature, Pasqals full-stack, software-agnostic quantum processing units have the potential to address complex problems in medicine, finance and sustainability more efficiently than classical computers. Pasqals open-source library, Pulser enablesthecontrolof neutralatoms-basedprocessors at the level of laser pulses.

Pasqal is already exploring specific use cases across industries. The company is working with a leading French utility company, EDF, to optimize charging schedules for electric vehicles to combat climate change. Pasqal is also working with Crdit Agricole CIB and Multiverse Computing to design and implement new approaches running on classical and quantum computers to outperform state-of-the-art algorithms for capital markets and risk management. In addition, the company is working with Qubit Pharmaceuticals to accelerate drug discovery through quantum technology. Pasqal hopes these initial use cases will open the door to additional applications in carbon capture, energy and sustainability.

With the companys recent funding, Pasqal plans to continue innovating and developing new solutions. By the end of 2022, Pasqal plans to provide cloud access to its quantum computing services and hopes to deliver a full quantum computing device operating on the cloud by 2023.

Georges-Olivier Reymond, CEO and founder of Pasqal, accepted the award at LUsine Nouvelles Foundations of the Industry event today in Paris. The event was attended by more than 150 industry leaders and decision-makers, uniting various industry sectors in France and Europe.

Were honored to be named Startup of the Year among the many French technology startups aiming to solve the worlds biggest challenges, said Reymond. Were proud to be part of Frances hub for technology innovation, supported by the French government, and we look forward to putting our quantum technology to real-world use throughout the region.

To learn more about Pasqal and its award-winning solutions, please visit: http://www.pasqal.io.

About Pasqal

Pasqalis building quantum processors out of neutral atoms atoms possessing an equal number of electrons and protons through the use of optical tweezers using laser light, enabling the engineering of full-stack processors with high connectivity and scalability.

The company is dedicated to delivering a 1000-qubit quantum processor by 2023 to help customers achieve quantum advantage in the fields of quantum simulation and optimization across several vertical sectors, including finance, energy and supercomputing.

For more information, please contact the company:contact@pasqal.io

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Pasqal named startup of the year by L'Usine Nouvelle - EurekAlert

Size comparison of qubits The illustration shows the size difference between spin qubits and superconducting qubits. Credit: University of Copenhagen

Quantum physicists at the University of Copenhagen are reporting an international achievement for Denmark in the field of quantum technology. By simultaneously operating multiple spin qubits on the same quantum chip, they surmounted a key obstacle on the road to the supercomputer of the future. The result bodes well for the use of semiconductor materials as a platform for solid-state quantum computers.

One of the engineering headaches in the global marathon towards a large functional quantum computer is the control of many basic memory devices qubits simultaneously. This is because the control of one qubit is typically negatively affected by simultaneous control pulses applied to another qubit. Now, a pair of young quantum physicists at the University of Copenhagens Niels Bohr Institute PhD student, now Postdoc, Federico Fedele, 29 and Asst. Prof. Anasua Chatterjee, 32, working in the group of Assoc. Prof. Ferdinand Kuemmeth, have managed to overcome this obstacle.

The brain of the quantum computer that scientists are attempting to build will consist of many arrays of qubits, similar to the bits on smartphone microchips. They will make up the machines memory.

The famous difference is that while an ordinary bit can either store data in the state of a 1 or 0, a qubit can reside in both states simultaneously known as quantum superposition which makes quantum computing exponentially more powerful.

Global qubit research is based on various technologies. While Google and IBM have come far with quantum processors based on superconductor technology, the UCPH research group is betting on semiconductor qubits known as spin qubits.

Broadly speaking, they consist of electron spins trapped in semiconducting nanostructures called quantum dots, such that individual spin states can be controlled and entangled with each other, explains Federico Fedele.

Spin qubits have the advantage of maintaining their quantum states for a long time. This potentially allows them to perform faster and more flawless computations than other platform types. And, they are so minuscule that far more of them can be squeezed onto a chip than with other qubit approaches. The more qubits, the greater a computers processing power. The UCPH team has extended the state of the art by fabricating and operating four qubits in a 22 array on a single chip.

Thus far, the greatest focus of quantum technology has been on producing better and better qubits. Now its about getting them to communicate with each other, explains Anasua Chatterjee:

Now that we have some pretty good qubits, the name of the game is connecting them in circuits which can operate numerous qubits, while also being complex enough to be able to correct quantum calculation errors. Thus far, research in spin qubits has gotten to the point where circuits contain arrays of 22 or 33 qubits. The problem is that their qubits are only dealt with one at a time.

Federico Fedele, Anasua Chatterjee, and Ferdinand Kuemmeth. Credit: University of Copenhagen

It is here that the young quantum physicists quantum circuit, made from the semiconducting substance gallium arsenide and no larger than the size of a bacterium, makes all the difference:

The new and truly significant thing about our chip is that we can simultaneously operate and measure all qubits. This has never been demonstrated before with spin qubits nor with many other types of qubits, says Chatterjee, who is one of two lead authors of the study, which has recently been published in the journal Physical Review X Quantum.

The four spin qubits in the chip are made of the semiconducting material gallium arsenide. Situated between the four qubits is a larger quantum dot that connects the four qubits to each other, and which the researchers can use to tune all of the qubits simultaneously.

Being able to operate and measure simultaneously is essential for performing quantum calculations. Indeed, if you have to measure qubits at the end of a calculation that is, stop the system to get a result the fragile quantum states collapse. Thus, it is crucial that measurement is synchronous, so that the quantum states of all qubits are shut down simultaneously. If qubits are measured one by one, the slightest ambient noise can alter the quantum information in a system.

The realization of the new circuit is a milestone on the long road to a semiconducting quantum computer.

To get more powerful quantum processors, we have to not only increase the number of qubits, but also the number of simultaneous operations, which is exactly what we did states Professor Kuemmeth, who directed the research.

At the moment, one of the main challenges is that the chips 48 control electrodes need to be tuned manually, and kept tuned continuously despite environmental drift, which is a tedious task for a human. Thats why his research team is now looking into how optimization algorithms and machine learning could be used to automate tuning. To allow fabrication of even larger qubit arrays, the researchers have begun working with industrial partners to fabricate the next generation of quantum chips. Overall, the synergistic efforts from computer science, microelectronics engineering, and quantum physics may then lead spin qubits to the next milestones.

Reference: Simultaneous Operations in a Two-Dimensional Array of Singlet-Triplet Qubits by Federico Fedele, Anasua Chatterjee, Saeed Fallahi, Geoffrey C. Gardner, Michael J. Manfra and Ferdinand Kuemmeth, 8 October 2021, PRX Quantum.DOI: 10.1103/PRXQuantum.2.040306

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Innovative Chip Resolves Quantum Headache Paves Road to Supercomputer of the Future - SciTechDaily

he project includes the construction and commissioning of the first quantum computer in southern Europe, which will be operational by the end of 2022 and will be installed at BSC.

The Barcelona Supercomputing Center (BSC) has begun coordination work on the Quantum Spain project, which provides for the construction and installation of the first quantum computer based on European technology. The strategic objective of the Quantum Spain project, approved last Tuesday by the Council of Ministers, is to create a solid quantum computing ecosystem in Spain.

Quantum Spain involves 25 universities and infrastructure and supercomputing centres, from 14 autonomous communities and will be managed by BSC, as the main node of theSpanish Supercomputing Network(RES). The coordinator of the project will be the doctor in quantum computing Alba Cervera, researcher at BSC.

The project foresees the construction of a quantum computer that will be installed at BSC headquarters and that will progressively be equipped with chips of different generations and numbers of qubits. The qubit is the basic unit of quantum computing and the Quantum Spain project will use qubits based on superconducting circuit technology. The construction of the hardware will be carried out in collaboration with companies specialized in this emerging sector.

The forecast is that the computer will have a first operational two-qubit chip by the end of 2022 and will progressively incorporate new versions of chips, until reaching 20 qubits in 2025. The objective of Quantum Spain is not to compete with other quantum computers in number of qubits. We want quality before quantity. This is a realistic project that is committed to having a powerful quantum computer, but not at the cost of sacrificing those quantum properties that make it special. The goal is to have a quality, functional device that is useful and can be used to solve real problems in the near future. We want it to be useful for Spain to develop its own algorithms, to promote its transversal use both for research and for companies and to train future users of this technology. "

The priority: create a quantum ecosystem

The priority of Quantum Spain, framed in the National Strategy for Artificial Intelligence (ENIA), is to establish a solid quantum computing ecosystem in Spain, taking advantage of and promoting the talent of local researchers who are experts in this technology. This objective is based on four pillars:

A technology with intense international competition

Quantum computing has potential applications in AI, in quantum chemistry, in finance, in optimization of production chain processes, cryptography, cybersecurity, logistics and in many problems that require intense computational needs. Currently, it is one of the research and development areas on which a more intense international career is being carried out and different countries have already announced plans to obtain computers based on quantum technologies.

One of the peculiarities of Quantum Spain's commitment is that it does not intend to join this race by buying hardware from third countries and is committed to the development of its own technology, to limit dependence and maintain the maximum possible degree of technological and economic sovereignty.

This program is fully aligned with the European commitment to quantum computing, through the EuroHPC Joint Undertaking alliance, which promotes European capabilities in supercomputing. The objective of the Commission and the countries as a whole is to provide European users of HPC with quantum computers integrated into the large supercomputing centers, such as BSC. This will coincide with the growing demand for this type of computing from industry and the world and will encourage the emergence of real use case applications in Europe.

Another priority of the project is to promote synergies between quantum technologies and artificial intelligence - a field known as "Quantum Machine Learning" -, taking advantage of the characteristics of quantum infrastructures to facilitate the training process of certain deep learning algorithms.

This project, promoted by the Secretary of State for Digitalization and Artificial Intelligence (SEDIA) of the Ministry of Economic Affairs and Digital Transformation, is part of the Recovery, Transformation and Resilience Plan and measure 15 of the National Artificial Intelligence Strategy ( ENIA), thus also advancing in the implementation of the Digital Spain 2025 agenda.

This article was first published on October 29 by Barcelona Supercomputing Center.

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BSC will coordinate Quantum Spain, the national quantum computing ecosystem - Science Business

image:In the lower right a near-IR laser separates the two electrons (empty circles) from the two kinds of holes (solid circles). The charges are accelerated away from each other by the fluctuating electric field from the terahertz laser (gray wave). The changing field then drags the charges toward each other, at which point they combine and emit two flashes of light. The trajectories are depicted in one dimension of space with time flowing from the bottom right to top left. view more

Credit: Brian Long

Lightspeed is the fastest velocity in the universe. Except when it isnt. Anyone whos seen a prism split white light into a rainbow has witnessed how material properties can influence the behavior of quantum objects: in this case, the speed at which light propagates.

Electrons also behave differently in materials than they do in free space, and understanding how is critical for scientists studying material properties and engineers looking to develop new technologies. An electrons wave nature is very particular. And if you want to design devices in the future that take advantage of this quantum mechanical nature, you need to know those wavefunctions really well, explained co-authorJoe Costello, a UC Santa Barbara graduate student in condensed matter physics.

In a new paper, co-lead authors Costello, Seamus OHara and Qile Wu and their collaborators developed a method to calculate this wave nature, called a Bloch wavefunction, from physical measurements. This is the first time that theres been experimental reconstruction of a Bloch wavefunction, said senior authorMark Sherwin, a professor of condensed matter physics at UC Santa Barbara. The teams findings appear in the journalNature, coming out more than 90 years after Felix Bloch first described the behavior of electrons in crystalline solids.

Like all matter, electrons can behave as particles and waves. Their wave-like properties are described by mathematical objects called wavefunctions. These functions have both real and imaginary components, making them what mathematicians call complex functions. As such, the value of an electrons Bloch wavefunction isnt directly measurable; however, properties related to it can be directly observed.

Understanding Bloch wavefunctions is crucial to designing the devices engineers have envisioned for the future, Sherwin said. The challenge has been that, because of inevitable randomness in a material, the electrons get bumped around and their wavefunctions scatter, as OHara explained. This happens extremely quickly, on the order of a hundred femtoseconds (less than one millionth of one millionth of a second). This has prevented researchers from getting an accurate enough measurement of the electrons wavelike properties in a material itself to reconstruct the Bloch wavefunction.

Fortunately, the Sherwin group was the right set of people, with the right set of equipment, to tackle this challenge.

The researchers used a simple material, gallium arsenide, to conduct their experiment. All of the electrons in the material are initially stuck in bonds between Ga and As atoms. Using a low intensity, high frequency infrared laser, they excited electrons in the material. This extra energy frees some electrons from these bonds, making them more mobile. Each freed electron leaves behind a positively charged hole, a bit like a bubble in water. In gallium arsenide, there are two kinds of holes, heavy holes and light holes, which behave like particles with different masses, Sherwin explained. This slight difference was critical later on.

All this time, a powerful terahertz laser was creating an oscillating electric field within the material that could accelerate these newly unfettered charges. If the mobile electrons and holes were created at the right time, they would accelerate away from each other, slow, stop, then speed toward each other and recombine. At this point, they would emit a pulse of light, called a sideband, with a characteristic energy. This sideband emission encoded information about the quantum wavefunctions including their phases, or how offset the waves were from each other.

Because the light and heavy holes accelerated at different rates in the terahertz laser field, their Bloch wavefunctions acquired different quantum phases before they recombined with the electrons. As a result, their wavefunctions interfered with each other to produce the final emission measured by the apparatus. This interference also dictated the polarization of the final sideband, which could be circular or elliptical even though the polarization of both lasers was linear.

Its the polarization that connects the experimental data to the quantum theory, which was expounded upon by postdoctoral researcherQile Wu. Qiles theory has only one free parameter, a real-valued number that connects the theory to the experimental data. So we have a very simple relation that connects the fundamental quantum mechanical theory to the real-world experiment, Wu said.

Qile's parameter fully describes the Bloch wavefunctions of the hole we create in the gallium arsenide, explained co-first authorSeamus OHara, a doctoral student in the Sherwin group. The team can acquire this by measuring the sideband polarization and then reconstruct the wavefunctions, which vary based on the angle at which the hole is propagating in the crystal. Qile's elegant theory connects the parameterized Bloch wavefunctions to the type of light we should be observing experimentally.

The reason the Bloch wavefunctions are important, Sherwin added, is because, for almost any calculation you want to do involving the holes, you need to know the Bloch wavefunction.

Currently scientists and engineers have to rely on theories with many poorly-known parameters. So, if we can accurately reconstruct Bloch wavefunctions in a variety of materials, then that will inform the design and engineering of all kinds of useful and interesting things like laser, detectors, and even some quantum computing architectures, Sherwin said.

This achievement is the result of over a decade of work, combined with a motivated team and the right equipment. A meeting between Sherwin and Renbao Liu, at the Chinese University of Hong Kong, at a conference in 2009 precipitated this research project. Its not like we set out 10 years ago to measure Bloch wavefunctions, he said; the possibility emerged over the course of the last decade.

Sherwin realized that the unique, building-sized UC Santa Barbara Free-Electron Lasers could provide the strong terahertz electric fields necessary to accelerate and collide electrons and holes, while at the same time possessing a very precisely tunable frequency.

The team didnt initially understand their data, and it took a while to recognize that the sideband polarization was the key to reconstructing the wavefunctions. We scratched our heads over that for a couple of years, said Sherwin, and, with Qiles help, we eventually figured out that the polarization was really telling us a lot.

Now that theyve validated the measurement of Bloch wavefunctions in a material they are familiar with, the team is eager to apply their technique to novel materials and more exotic quasiparticles. Our hope is that we get some interest from groups with exciting new materials who want to learn more about the Bloch wavefunction, Costello said.

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Working through a mental bloch - EurekAlert