Daily Archives: April 27, 2021

Quantum computing may conjure up the image of crazy-haired physicists working away in remote and isolated locations, but nothing could now be further from the truth.

The U.S. government authorized a $1 billion quantum computing plan late last year to get ahead of its adversaries. A few weeks ago, President Bidens infrastructure proposal included a further $180 billion investment in R&D for quantum computing, semiconductor chips, and other key technologies.

Related: 4 Experts Let The Cat Out Of The Box On Quantum Computing And Electronic Design

The governments bigger plan is to link government, private and university research to accelerate quantum computing technologies in the U.S. This plan is similar to the earlier US technology successes like the Manhattan Project to build the atomic bomb, the Apollo program to send humans to the moon, and others.

This gallery highlights major components in the governments quantum computing structure, starting with the National Quantum Initiative.

Related: 5 Key Segments Shape 2021 Semiconductor and EDA Markets

John Blyler is a Design News senior editor, covering the electronics and advanced manufacturing spaces. With a BS in Engineering Physics and an MS in Electrical Engineering, he has years of hardware-software-network systems experience as an editor and engineer within the advanced manufacturing, IoT and semiconductor industries. John has co-authored books related to system engineering and electronics for IEEE, Wiley, and Elsevier.

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Will the Government Succeed in Building a Quantum Computing Center? - DesignNews

GCHQ Director, Jeremy Fleming, said on Friday 23 April that the UK needs to prioritize advances in quantum computing if the country wants to prosper and remain secure.

Hes right. The vast amounts of data protected by RSA encryption is under threat of theft and forgery should quantum computing live up to promise.

While such peril remains years away at least, companies and governments worldwide are getting to grips with quantum computing, as the technology leaves the realm of physics laboratories and into the inboxes of presidents and prime ministers.

Classical computers, such as those in our phones, laptops, and even the worlds most powerful supercomputers, conduct computations with ones and zeros binary digits, or bits.

When presented with sufficiently complex problems, classical computers begin to struggle.

Consider this number:

25195908475657893494027183240048398571429282126204032027777137836043662020707595556264018525880784406918290641249515082189298559149176184502808489120072844992687392807287776735971418347270261896375014971824691165077613379859095700097330459748808428401797429100642458691817195118746121515172654632282216869987549182422433637259085141865462043576798423387184774447920739934236584823824281198163815010674810451660377306056201619676256133844143603833904414952634432190114657544454178424020924616515723350778707749817125772467962926386356373289912154831438167899885040445364023527381951378636564391212010397122822120720357

If we were to ask a classical, general-purpose computer which two prime numbers multiply together make this 617-digit number? it would have to essentially guess at each possible combination. Using this method, most estimates suggest it would take around 300 trillion years to crack much longer than the age of the universe. There are ways to speed this up, but this form of encryption is extremely difficult to crack classically.

This is vital for protecting important data and is the kind of problem that underpins RSA encryption which is used to protect vast amounts of data on the internet.

A quantum computer, on the other hand, could figure out the answer in seconds.

While researchers agree that you would need around a few thousand qubits to conduct such a calculation (were only around the 100-qubit mark right now), it is not beyond the realms of possibility for such a feat to be achieved this decade.

With vast use cases, ranging from artificial intelligence (AI) to weather forecasting, quantum computings potential encryption-cracking capabilities should put the technology firmly on the priority list for world leaders and security chiefs.

In the Vincent Briscoe Lecture, Fleming made frequent mention of quantum computing.

He highlighted that a small percentage of technologies must be truly sovereign to retain the UKs strategic technical advantage, and quantum computing is no doubt a core part of this. The elements of cryptographic technology that are a part of these technologies was no doubt an allusion to quantum computing. The country, or corporation, that possess the first full-scale, fault-tolerant quantum computer will be the biggest threat to cryptography the world has ever seen.

Fleming will undoubtably be aware of Chinas quantum supremacy announcement in December 2020, in which a team at the University of Science and Technology of China performed a calculation with a photonic quantum computer 100 trillion times the speed of classical supercomputers.

While photonic devices are so far unprogrammable, in that each can only perform one specific calculation, the progress in China is a wake-up call for Western powers to get to grips with the technology.

The UK is among the leaders in the West, in both spending and academic prowess, but Chinas $15bn of investments into quantum technologies dwarfs the rest of the pack President Biden will no doubt be keeping a close eye on developments in this nascent industry.

Quantum computing is no doubt going to develop significantly as a theme over the coming years, as recent developments indicate. Governments and corporations alike must now take steps to engage, or risk falling behind.

Integer factorization is just one of the applications of quantum computing, in what is becoming a rich ecosystem of research and development. GlobalDatas quantum computing value chain sets out the segments of this growing industry.Related Report Download the full report from GlobalData's Report StoreGet the Report

Latest report from Visit GlobalData Store

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GCHQ boss is right to be keeping his eye on quantum computing - Verdict

IonQ is the only company that provides access to its quantum computing platform via both the Amazon Braket and Microsoft Azure clouds, as well as through direct API access.

FREMONT, CA: IonQ announced full integration of its quantum computing platform with Qiskit, an open-source quantum software development kit, or SDK. Qiskit users can now submit programs directly to IonQ's platform without writing any new code. Through the Qiskit Partner Program, this new integration makes IonQ's high-connectivity high-fidelity 11 qubit system available to the 275,000+ enterprise, government, startup, partner, and university members already using Qiskit to create and run quantum programs.

As part of the announcement, IonQ has released an open-source provider library that integrates seamlessly with Qiskit, which can be found on the Qiskit Partners GitHub organization or downloaded via The Python Package Index. Qiskit users with an IonQ account will be able to run their quantum programs on IonQ's cloud quantum computing platform with little to no modificationsimply change the code to point to the IonQ backend and run as usual.

"IonQ is excited to make our quantum computers and APIs easily accessible to the Qiskit community," said IonQ CEO & President Peter Chapman. "Open source has already revolutionized traditional software development. With this integration, we're bringing the world one step closer to the first generation of widely-applicable quantum applications."

This integration builds on IonQ's ongoing success. IonQ recently entered into a merger agreement with dMY Technology Group, Inc. III to go public at an expected valuation of approximately $2 billion. IonQ also recently released a product roadmap setting out its plans to develop modular quantum computers small enough to be networked together in 2023, which could pave the way for broad quantum advantage by 2025. Last year, the company unveiled a new $5.5 million, 23,000 square foot Quantum Data Center in Maryland's Discovery District and announced the development of the world's most powerful quantum computer, featuring 32 perfect atomic qubits with low gate errors and an expected quantum volume greater than 4,000,000.

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IonQ Announces Full Integration of its Quantum Computing Platform with Qiskit - CIO Applications

Dr. Lee Braine has spent the past seven years working across Barclays' wealth management, markets, and corporate and investment banking divisions but his job couldn't be further from that of your typical City of London broker or trader.

A managing director in the bank's chief technology office, London-based Braine is responsible for research and engineering across corporate, investment, and retail banking. He has a special focus on distributed ledger technology, like blockchain, as well as quantum computing.

Insider sat down for a virtual chat with Braine who was named one of Business Insider's 100 Transformers to discuss what he's working on and where the industry is going next.

Transcript has been edited for clarity and length:

Insider: You're not an average banker. You're a computer scientist by training. Can you tell me a bit more about your background?

Braine: I have a PhD from University College London in computer sciencethe particular topic was object-oriented functional programming. I used that research knowledge in banking, and that included, for example, working with financial market infrastructures when I was in my twenties to produce new architectures and new optimization algorithms. In this case, it was for securities settlement. After that, I spent quite a few years working in technology management.

Within Barclays, for these last 7 years, I've been working on technology innovation. The typical thing I've been working on is responsibility for advanced technologies that Barclays needs to be up to speed on. We work closely with a variety of stakeholders, not just [technology] vendors, but also very closely with official institutions, including central banks, regulators, and the government on the potential of these new technologies, and the risks and any issues that may lie with them.

Insider: Let's talk about distributed ledgersyou lead Barclays' efforts there. Why is Barclays interested in distributed ledgers like the blockchain?

Braine: Interest was initially sparked about 5-6 years ago when we were looking at bitcoin from a technology perspective. That means not as an investable asset, but at other interesting, novel technologies underlying bitcoin that could be repurposed in more traditional financial services. There are several features of bitcoin that inspire a different way of working: at the lowest level, there may be things such as consensus algorithms, hashing technique, the chain of blocksall of those types of low-level technical things that everybody learned about in the last few years from blockchain. But higher up, there are new ways of working, almost new market models that get inspired by cryptocurrency.

For example, currently, financial market infrastructures are centralized financial institutions, and their technology is centralizedthey've got centralized databases and centralized processing. The decentralized nature of something like bitcoin has inspired people. Could we have a different model of the market? Could we imagine decentralizing, not just the technology, but also some of the rights and obligations of participating in such a network? So to make that abstract idea a bit more concrete: imagine if you've got a clearing house, and currently we send all our trades to the clearing house, it performs the processing and sends us back the result. Imagine if, instead, each of the participants formed a network, they operated peer-to-peer, and that peer-to-peer model then gets translated down into the technical solution. So that's a different way of workingyou can call that a distributed financial market infrastructure.

It's a big infrastructure change to the marketso why bother? What we see is quite a few potential benefits. These include radical simplification and rationalization. Another thread is you're able to speed up settlement times.

Insider: Tell me about Utility Settlement Coin and the Fnality investment.

Braine: The consortium was originally called Utility Settlement Coin, and then, about 2 years ago, a group of financial institutions so 14 banks and one exchange strategically invested to create the new entity, which was Fnality International. They're building a new payment system, and this is going to offer peer-to-peer settlements using an underlying blockchain platform. The money that moves on it will be one-to-one backed by funds that have been pre-deposited at a central bank, so it's effectively a pre-funding model. It allows a number of benefits in terms of settlement.

For example, you could continue operating outside of the window when the real time gross settlementRTGSis closed at the central bank. You could, for example, connect to other tokenized assets to allow atomic swap between them. If you had Fnality representing the payment leg on a payment blockchain, you could imagine a security leg on a security blockchain and the two of them could do instant settlement with the appropriate interconnect between the two. A key point here is that the money being backed by funds at the central bank means that there's lower risks associated with such payments.

Insider: You also work with the International Swaps and Derivatives Association (ISDA), right?

Braine: Yes. One of the things we've been progressing for a few years relates to a new standard for data and processing, and it's called the ISDA Common Domain Model. This model effectively provides a standard industry representation for events in the lifecycle of a trade. Currently, each institution builds their own solutions, so effectively, there's variation in how you code itsome may code in Java and others may code in C++, so different programming languages. They may store the data in different types of databases, and they may enrich the data with extra fields. So you've got variation there. Then, over time, each institution must manage and maintain its data stores. So across the industry, the same high-level functionality is implemented slightly differently on slightly different data sets. And each time there's a lifecycle event, they all need to sync up and reconcile to make sure that, yes, what's been affected in terms of an event, the before and after, is consistent.

That's incredibly inefficient as a solution. Imagine we had a browser for the internet, and each bank built their own browser, right? Of course we don't do that. We have a common browser, Chrome or Internet Explorer, we download it, we use it. So that same philosophy is being applied here. A distributed ledger de facto defines the common data structure that you all must use. And smart contract technology is a common process that they must all follow.

You then start getting the opportunity to transform the industry, and all the participants. And those opportunities don't come up very often. So I think we're living in interesting times where this technology is just reaching the right degree of maturity, and there's also appetite from the market participants to reduce costs.

Insider: Ok, tell me more about smart contracts, which I know you also research.

Braine: There are many, many business processes that could benefit from the rigor and standardization that smart contracts would bring. To give one example, interest rate swaps. So a few years ago, about 4 years ago, my team prototyped an interest rate swap from end to end. Complete end-to-end processing naturally fits with the idea of a smart contract, meaning the data that you construct at the beginning just flows throughyou don't transform it, you don't switch it into completely different systems.

The way I like to view it is, smart means automatable, and contract means enforceable. Other good use-cases include trade finance, loans, bonds, and syndicated loans. It's easy to identify 101 use cases for smart contracts; the challenge is identifying viable business cases where the industry can move together in concert, given that these are consortium plays, so you need your peers to be similarly motivated at the same time to grasp at the same propositions.

Insider: What sort of work are you doing in quantum computing?

Braine: Barclays started exploring quantum computing back in summer 2017. We did that by partnering with IBM. We set up a joint development project, and our goal initially was to learn more about quantum computing. It's a phenomenally complex topic, where even those that have quantitative research backgrounds find it challenging to understand the details.

We decided for our first proof of concept that we would look at a settlement optimization problem. This is a particular challenge where a market infrastructure looks to optimize the settlement of a batch of securities transactions. A typical batch may have 50,000 transactions, you've got many potential combinations that you could settle, and you need to work out what is the best combination. It's a problem that you typically can't solve perfectly, so you often run an optimization algorithm for long enough in order to solve it well enough, and then you repeat the batch later.

We were inspired by [the question]: could a quantum algorithm on a quantum computer solve that problem perfectly, or perhaps better than the classical ones? We looked at candidate quantum algorithms, we worked with IBM to implement an algorithm, we constructed candidate scenarios to run through test data, and we got the results. The key takeaway is that, for the first time, an algorithm has been run for settling securities transactions on a quantum computer. Obviously, it's only just test data and very small scale, so it's more of a proof of concept, but we've demonstrated that the proof of concept works.

In terms of next steps, we're currently exploring quantum machine learning. How many more buzzwords could you get into one conversation, right? We've run our first experiment comparing quantum and classical versions, and in the next couple of months, we'll be looking to publicly release our initial findings.

Insider: In real terms, what benefits might quantum computing bring to Barclays? And when?

Braine: We need to extrapolate for when we think the hardware will be sufficiently mature to be able to run real-world use cases. For perspective, we think that will be in the range of 4-8 years from now.

In terms of the type of benefits, it's almost like adding a special maths co-processor, and it's able to perform a number of functionsit's able to perform an optimization process faster than a traditional classical computer, or it's able to perform the process and get a higher-quality result. So this could be optimizing which assets you put in a portfolio, or running a number of Monte Carlo optimizations as part of a risk model. These types of things often require huge compute resources.

And that's why we're exploring this for researchnot because we think it could be perfectly used in the next year or two, but because we're learning, building a foundation. I would almost call it quantum awareness, where we're raising our awareness so that we could leverage it when the powerful machines come along in a few years' time that we could use for real world use cases.

Insider: Where is financial technology going next? How does that fit with traditional banking?

Braine: There are a number of key themes, one being machine learning and artificial intelligence. So the application of that technology, we've seen it deployed with fantastic effect, whether that's search or shopping or similar. There's great opportunity for those technologies to also be applied within financial services, particularly to further improve the customer experience.

Other key technologies include cloud computing.

Insider: Are you worried about disruption from tech startups?

Disruption is at the heart of my day job. We're often looking to see what technologies have potential for disruption, and to see how we could leverage or partner with third parties that have such potentially disruptive technologiesand also to understand the risks and potential issues that are associated with themso that we're able to have a sensible position in order to be able to advise the business.

Often if we're going to pick certain technologies, it may well be the case that what's viewed as a potential disruptor to Barclays could also be viewed as a potential partnership opportunity in terms of optimizing and improving some of our own internal processes.

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Meet the Barclays MD working to transform finance through distributed ledgers and quantum computing - Business Insider

When it comes to practical problems, including things such as the traveling salesman problem, a classic in optimization, the value of quantum is still to be decided, say Richard Moulds, left, head of Amazon's Braket quantum computing service, and Robert Liscouski, head of Quantum Computing Inc., which makes Qatalyst software to do optimization on both classical and quantum machines.

It's easy to imagine a problem for which, if one had a computer that magically leapt across steps of the computation, your life would be much better.

Say, for example, a computer that auto-magically searches through a vast space of possible solutions much faster than you can with a CPU or GPU.

That's the premise of quantum computing, and surprisingly, for all the hype, it's not clear if that premise is true.

"I don't think we've seen any evidence yet that a quantum machine can do anything that's commercially interesting faster or cheaper than a classical machine," Richard Moulds, head of Amazon Braket, the cloud giant's quantum computing service, said in an interview with ZDNet. "The industry is waiting for that to arrive."

It is the question of the "quantum advantage," the notion that the entangled quantum states in a quantum computer will perform better on a given workload than an electronic system.

"We haven't seen it yet," Robert Liscouski, CEO of Quantum Computing Inc, said of the quantum advantage, in the same Zoom interview with Moulds.

That aporia, the as-yet-unproven quantum advantage, is in fact the premise for a partnership announced this month, whereby QCI's Qatalyst software program will run as a cloud service on top of Braket.

QCI's corporate tag line is "ready-to-run quantum software," and the Qatalyst program is meant to dramatically simplify sending a computing task to the qubits of a quantum hardware machine, the quantum processing units, or QPUs, multiple instances of which are offered through Bracket, including D::Wave, IonQ, and Rigetti.

The idea is to get more people working with quantum machines precisely to find out what they might be good for.

"Our platform basically allows the democratization of quantum computing to extend to the user community," said Liscouski.

"If you look back on the quantum industry since it started, it's traditionally been very difficult to get access to quantum hardware," said Moulds, including some machines that are "totally unavailable unless you have a personal relationship with the the physicist that built it."

"We're trying to make it easy for everyone to have access to the same machinery; it shouldn't be those that have and those that have not, it should be everyone on the same flywheel," he said.

The spectrum of users who will be working with quantum comprise "two important communities" today, said Moulds, those that want to twiddle qubits at the hardware level, and those that want to spend time on particular problems in order to see if they actually gain any benefit when exposed to the quantum hardware.

"There's a lot of researchers focused on building better hardware, that is the defining force in this industry," said Moulds. "Those types of researchers need to be in the weeds, playing at the qubit level, tweaking the frequencies of the pulses sent to the chip inside the fridge."

On the other hand, "the other class of users is much more geared to Robert's view of the world: they don't really care how it gets done, they just want to understand how to program their problem so that it can be most easily solved."

That second class of users are "all about abstraction, all about getting away from the technology." As quantum evolves, "maybe it slides under so that customers don't even know it's there," mused Moulds.

When it comes to those practical problems, the value of quantum is still to be decided.

There has been academic work showing quantum can speed up tasks, but "that's not been applied to a problem that anybody cares about," said Moulds.

The entire quantum industry is "still finding its way to what applications are really useful," he said. "You tend to see this list of potential applications, a heralded era of quantum computing, but I don't think we really know," he said.

The Qatalyst software from QCI focuses on the kinds of problems that are of perennial interest, generally in the category of optimization, particularly constrained optimization, where a solution to a given loss function or objective function is made more complicated by having to narrow the solution to a bunch of variables that have a constraint of some sort enforced, such as bounded values.

"They are described at a high level as the traveling salesman problem, where you have multi-variate sort of outcomes," said Liscouski. "But it's supply-chain logistics, it's inventory management, it's scheduling, it's things that businesses do today that quantum can really accelerate the outcomes in the very near future."

Such problems are "a very important use case," said Moulds. Quantum computers are "potentially good at narrowing the field in problem spaces, searching through large potential combinations in a wide variety of optimization problems," he said.

However, "classical will probably give you the better result" at this time, said Liscouski.

One of the reasons quantum advantage is not yet certain is because the deep phenomena at the heart of the discipline, things such as entanglement, make the field much more complex than early digital computing.

"A lot of people draw the analogy between where we are and the emergence of the transistor," said Moulds.

"I think that's not true: this is not just a case of making the computers we have today smaller and faster and cheaper, we're not anywhere near that regime, that Moore's Law notion of just scaling these things up."

"There's fundamental scientific discoveries that have to be made to build machines that can tackle these sorts of problems on the grand scale that we've been talking about."

Beyond the machines' evolution, there is an evolution implicit for programmers. Quantum brings a fundamentally different approach to programming. "These are physics-based machines, they're not just computational engines that add ones and zeros together, it's not just a faster slide rule," said Moulds.

That different way of programming may, in fact, point the way to some near-term payoff for the Qatalyst software, and Braket. Both Liscouski and Moulds expressed enthusiasm for taking lessons learned from quantum and back-loading them into classical computers.

"Typically, access to quantum computing is through toolkits and resources that require some pretty sophisticated capabilities to program to ultimately get to some result that involves a quantum computer," observed Liscouski.

"With Braket, the platform provides both access to QPUs and classical computing at the same time, and the quantum techniques that we use in the platform will get results for both," said Liscouski.

"It isn't necessarily a black and white decision between quantum and classical," said Moulds. "There's an emerging area, particularly in the area of optimization, people use the term quantum-inspired approaches are used."

"What that means is, looking at the ways that quantum computers actually work and applying that as a new class of algorithms that run on classical machines," he said.

"So, there's a sort of a morphing going on," he said.

An advantage to working with QCI, said Moulds, is that "they bring domain expertise that we don't have," things such as the optimization expertise.

"We've coined the phrase, 'Build on Braket'," said Moulds. "We're trying to build a quantum platform, and we look to companies like QCI to bring domain expertise to use that platform and apply it to problems that customers have really got."

Also important is operational stability and reliability, said Moulds. For a first-tier Web service with tons of users, the priority for Amazon is "running a professional service, a platform that is reliable and secure and durable" on which companies can "build businesses and solve problems."

Although there are "experimental" aspects, he said, "this is not intended to be a best-effort showcase."

Although the quantum advantage is not certain, Moulds holds out the possibility someone working with the technology will find it, perhaps even someone working on Braket.

"The only way we can move this industry forward is by pulling the curtains apart and giving folks the chance to actually see what's real," he said.

"And, boy, the day we see a quantum computer doing something that is materially advantageous from a commercial point of view, you will not miss that moment, I guarantee."

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Quantum: It's still not clear what its good for, but Amazon and QCI will help developers find out - ZDNet