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Quantum computing isnt yet far enough along that it could have helped curbthe spread of this coronavirus outbreak. But this emerging field of computing will almost certainly help scientists and researchers confront future crises.

Can we compress the rate at which we discover, for example, a treatment or an approach to this? asks Dario Gil, the director of IBM Research. The goal is to do everything that we are doing today in terms of discovery of materials, chemistry, things like that, (in) factors of 10 times better, 100 times better,

And that, he says, could be game-changing.

Quantum computing is thenext big thing in computing, and it promises exponential advances in artificial intelligence and machine learning through the next decade and beyond, leading to potential breakthroughs in healthcare and pharmaceuticals, fertilizers, battery power, and financial services.

For a consumer with a retirement fund, quantum computers over the next 10 to 15 years may help you make better personal financial decisions through the calculations that your broker is doing, says Bob Sutor, an IBM Research vice presidenttasked with driving the quantum computing ecosystem.

IBM, with 15 deployed quantum systems, is at the forefront of quantum computing. USA TODAYrecently got to tour a quantum lab in Yorktown Heights, New York.

But Google, Amazon, Intel, Microsoft and Honeywell are among other tech stalwarts working in the field, as are several venture-backed global startups.

IBM quantum computers system in the company's Yorktown Heights, N.Y., research lab.(Photo: Robert Deutsch)

The U.S. government, which is in a quantum race against China, has also lent support. In late 2018, President Trump signed the National Quantum Initiative Act into law to fund quantum research to the tune of $1.2 billion over a five-year period.

Here is a guide to help demystify quantum computing, which you will almost certainly hear a lot more about in the years ahead.

It isnt easy to get a grip around quantum computing or the field of physics it harnesses, quantum mechanics. But such machines they cost millions are designed to model nature.

In the simplest terms, they are exponentially more powerful than what we consider classical computers, whose basic fundamental units are expressed in1s or 0s or bits. Quantum computing takes a quantum leap with whatare known as quantum bits or "qubits for short.

Think about it this way: If you flip a coin, it will land as either heads or tails, or in those classical computer terms, 1s and 0s. But whats the state of that coin when it is still spinning? Thats kind of where qubits are, not necessarily as a 1 or a 0, but as all the possibilities in between.

Now lets take the analogy further. If you flip two coins in the physical world, the heads or tails of one coin has no bearing on the other. Qubits, though, can be entangled in multiple states at the same time.

This is one of those the 'Earth is not flat kind of moments, Gil says. There is actually a revolution going on.

A quantum computer chip is kept at a temperature thats colder than outer space in a cylinder that's part of an elaboraterefrigerated apparatus. The system has more than 2,000 components, including pulse tube coolers, superconducting coaxial lines, a mixing chamber and various circuits. It resembles a fancy chandelier.

The "chandelier" inside an IBM quantum computer.(Photo: Robert Deutsch)

In May 2016, IBM became the first company to put a quantum computer on the cloud, where anyone with the computing know-how could run experiments.

Currently, more than 150 billion programs and executions have been run on IBMs quantum machines, by more than 200,000 registered users in over 140 countries. There are over 12,000 monthly active users, and, on a typical day, the machines on the cloud run over 400 million quantum circuits.

IBM says it has signed contracts around quantum with more than 100 universities, national laboratories and companies.

For example, quantum researchers at IBM are teaming up with counterparts at Mercedes-Benz parent Daimler to develop next-generation batteries for electric vehicles. IBM is also partnering with Delta Air Lines to explore quantum opportunities in the travel business.

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This past October, Google said it achieved what's been described as quantum supremacy. It was able to perform a calculation in 200 seconds that supposedly would take a classic state-of-the-art supercomputer about 10,000 years to handle.

IBM pushed back. The company argued at the time that an ideal simulation of the same task can be performed on a classical system in 2 days and with far greater fidelity, which at that it said was a conservative, worst-case estimate.

Gil told USA TODAY thatpeople are not making a distinction of whats a lab experiment, versus what is a real system.

The claims around quantum computing keep coming.

Just this week, Honeywell announced what it said is the most powerful quantum computer yet, set for a mid-2020 release. Honeywell has formed a strategic partnership with JPMorgan Chase around financial solutions that exploit quantum. JPMorgan is also part of the IBM quantum ecosystem.

But these are still early days.Gilsays quantum computing today is in roughly the same spot where artificial intelligence was in 2010.

His IBM colleague Sutor says,Just to be clear, nobody on the planet has a quantum computer that can today do better that our classical computers.

ButIBM says it can double the power of a quantum computer every year, and at some point cross a threshold at which the quantum machines might leap past classical computers, at least to address certain types of problems.

There could be. Large future fault-tolerant quantum computers and such computers are not yet around the corner have the potential to crack current encryption systems. IBM is working with the National Institute of Standards and Technology (NIST) on changing encryption standards that promise to keepquantum systems efficient while at the same time keeping them secure.

Though security threats might be years away, Gil stresses the urgency to prepare now.You cannot just sit and ignore the problem, Gilsays.

Even years from now, you shouldn'texpectto have a quantum computer sitting on your desk.

But the technology made possible by quantum computers will start to insert itself into supporting and making consumer apps more powerful. And society would benefit if quantum computers can stop a potential pandemic before it ever really gets started.

Nature itself is one great big computer," Sutor says,in the way atoms and molecules and light interact.Can we learn enough about how it really does it and harness it for our own computing needs with the toughest sort of problems we have?

Email:ebaig@usatoday.com.Follow @edbaig on Twitter

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Could quantum computing help beat the next coronavirus? - USA TODAY

Aravind Ajad Yarra and Saji Thoppil, fellows at Wipro Limited, answer frequently asked questions about quantum computing

What should be kept in mind when implementing quantum technology?

Todays leaders are inundated with the disruptive power of quantum computing and its potential applications in AI, machine learning and data science. Gartner data reveals that by 2023, 95% of organisations researching it will utilise quantum-computing-as-a-service (QCaaS) to minimize risk and contain costs. Also, 20% of organisations will be seen budgeting for quantum computing projects, compared to less than 1% today.

We, Aravind Ajad Yarra, fellow, Wipro Limited and Saji Thoppil, fellow and chief technologist cloud and infrastructure Services, Wipro Limited, bring you the basics of quantum computing and demystify some of its unknown facets in todays evolving scenario.

Lets look at the commonly asked questions:

A: Most of us would have read quantum mechanics at high-school level physics and probably been baffled by its strange characteristics. Quantum mechanics is the physics that applies at atomic and subatomic levels. Thought of using the physics of quantum mechanics to computing is what has led to quantum computing.

Our present-day computing is largely based on Boolean logic, represented using binary bits, which assume the value of either 0 or 1. Quantum computing, on the other hand, uses quantum bits (qubits), which behave differently from classic bits and use quantum superposition state where each qubit can assume both 0 and 1 at the same time.

To get better clarity, I suggest reading this short article on quantum computing.

A: Quantum computing is one of the most exciting developments in recent computing history. For years, Moores law has been helping us to keep the innovation cycle in computing going and push the boundaries of what computing can offer to business, so much so that software is what is driving digital businesses. With Moores law reaching its saturation point, everyone is eagerly looking for whats next in computing. This is seen as something that can keep the computing innovation cycle going, hence this buzz.

If you hear the general hype, you might believe quantum computing might replace classic computing soon. However, that is far from reality. The superposition property that we mentioned earlier gives quantum computing some unique capability that traditional computing doesnt have. Simply put, qubit superposition allows quantum computing to solve certain classes of problems promptly, which might otherwise take years for classical computers.

IBM has established a roadmap for reaching quantum advantage and concluded that: for significant improvement over classical systems, the power of quantum computers must double every year. Read here

A: Quantum computers are not bigger or faster versions of existing computers. Quantum computing is fundamentally different from existing computing. The problems for which quantum computers are most useful are problems that classical computers are not good at.

Some of the classes of problems that quantum computers currently look at are optimisation problems, for example, addressing the classic travelling salesman problem. As the number of cities that have this problem increases, classic computers find it exponentially hard to find an optimum solution. Quantum computers proved very useful for these classes of problems. Solving such problems make quantum computers super useful in areas like gene analysis, drug discovery, chemical synthesis, weather simulations, newer types of encryption, unstructured search, and better deep neural networks, to name a few.

What is AI? Information Age has created a simple guide to AI, machine learning, neural networks, deep learning and random forests. Read here

A: There are two major approaches to quantum computing that are currently in use: circuit-based computers (aka universal quantum computers), and adiabatic computers.

Universal quantum computers are based on logical gates and work similar to the underlying logic foundations of classical computers. Hence, universal quantum computers are extremely useful for computing problems improving on our current knowledge base of solutions. However, qubits required for universal quantum computers are extremely difficult to realise physically because qubit instability makes it hard to produce universal quantum computers.

Adiabatic computers are analog, but are easier to produce. These are more relaxed with respect to qubit state stability. Hence, it is easier to produce 1000s of qubits on adiabatic computers. However, adiabatic computers can be used for limited use cases such as optimisation problems.

A: While most platform companies that are working to build quantum computers are taking bets on one or the other, enterprises can probably explore both of the models. While adiabatic computing is limited, there are production-ready adiabatic computers using real quantum bits (such as those from DWave), as well as digital annealers, which use digital qubits (from Atos and Fujitsu).

Its emerging technologies month on Information Age, that means augmented and virtual reality, quantum computing and blockchain. Read here

Circuit-based quantum computers are much more general purpose. While these have more utility for enterprises, no production-grade problems can be currently solved with the current state of these machines. I would suggest exploring both classes of computers, based on the case that one is trying to solve.

A: The best way to start with identification of use cases for quantum computing is to explore areas where classic computers are currently not good at. Optimisation problems are the best starting point for most enterprises. Based on the industry, different kinds of optimisation use cases can be considered for exploring quantum computers. These could be risk modelling, inventory or asset optimisation, among others.

Cryptography is another area where robust use cases can be identified by enterprises. Quantum computers, when production-ready, can potentially break current methods of encryption, leading to exposure of sensitive data. Identifying data that is very sensitive and has longer term value, and considering safe encryption methods using quantum key generation and distribution are other ways in which it can be used.

Machine learning is also a very promising use case. Quantum machine learning, as it is called, can use special purpose quantum circuits that can significantly boost the efficiency of machine learning algorithms.

A: Industries that are process-centric, such as pharmaceuticals and oil & gas exploration, are the early adopters. These industries can benefit from quantum computing in complex optimisation problems they need solve from time to time.

Apart from these asset-heavy industries, the manufacturing industry is also actively exploring quantum computing. Banks and other financial services companies, which have risk modelling needs, also rely a lot on quantum computing.

A: It is probably too early to talk about real-world scenarios where quantum computers have made an impact. While there are demonstrations by research labs to use quantum communication methods to send instant data transfer from satellite and breaking various encryption methods, these still look good in labs.

The reason for this is the current state of reliability in quantum computers. Qubits are highly sensitive, and they are prone to errors. Error correction methods that we currently use reduce the effective working qubits, but early results have been seen with digital annealers, which simulate adiabatic quantum computing using traditional digital computers.

Wipros Topcoder, for example, is currently working with Fujitsu to run crowdsourced challenging using Fujitsus digital annealer to solve real-world problems. Additionally, Airbus has been running open innovation challenges to solve some of its problems using quantum computing.

Quantum technologies also has appeal in the areas of communication, cryptography, sensors and measurements. Unlike quantum computing, where practical use cases are still in exploratory stages, these areas have industry-ready products that enterprises can put to use.

Quantum communication takes advantage of the nature of photons in flight and is able to detect if a photon has reached the recipient uninterrupted; this can ensure secure communications.

While quantum key generation (QKG) is used to generate truly random keys, quantum key distribution (QKD) is used for securely distributing keys. Both of these are essential for using a one-time pad cryptography technique, which is considered the holy grail in encryption.

Generating true random numbers for the quantum computing era, or indeed the pre-quantum era, is the aim. Crypta Labs reckon they have cracked it. Read here

Additionally, quantum sensors have niche applications where there is a need for highly accurate measurements of gravity, electric fields, time, position and magnetic field. In a fiercely competitive world, we can expect more enterprises wanting to leverage these to create unique offerings.

Given the nature of its evolution, it is hard to make an upfront business case for quantum computing. However, given the potential, I suggest that the business case be made in two parts.

The first part is to focus on near-term (1-2 years) use cases such as optimisation and encryption by using digital annealers for optimisation and photon-based ASICS for key generation. Digital annealers, or even simulators running on cloud, can solve several practical optimisation problems.

On the other hand, centres of excellence can be set up, leading to building expertise and solving relevant problems. Returns from these investments would set the stage for the second part, focusing on mid & longer term (2+ years) use cases, such as exploring machine learning and unstructured data search as part of centres of innovation and open innovation communities with small investments, but with longer period on returns.

Written by Aravind Ajad Yarra, fellow at Wipro Limited, and Saji Thoppil, fellow and chief technologist cloud and infrastructure Services at Wipro Limited

Excerpt from:
Cracking the uncertainty around quantum computing - Information Age

Science is at the heart of all Alex Garlands work, but the writer-director is less interested in erudite theories than he is in what those theories reveal about humanity itself. After Garlands directorial debut, Ex Machina, came out in 2014, he started circling the idea of quantum mechanics, reading about the subject in science journals and watching online lectures by physicists like David Deutsch and David Wallace. That growing obsession has resulted, years later, in Devs, a self-contained, eight-episode series for FX on Hulu, which Garland pursued after making Annihilation in 2018.

What tends to happen with me is that I get interested in a particular subject and then at some point a story just overlays itself over that subject, says Garland, sitting on the set of Devs last year in London. The point of being interested in a subject often goes on for years, and the story arrives later. Quite often when the story arrives, it comes fully formed its like a whole narrative just drops down onto it. Thats exactly what happened with this one.

This idea stemmed from whether we live in a deterministic universe or a nondeterministic universe a deterministic universe meaning a universe where everything is a result of a prior cause. And the philosophical implication for that is that it removes free will. If thats true, thats quite a big deal. It makes you re-think behavior, which means you re-think relationships and actions, things that one has done right or wrong.

Garland wrote and directed all eight episodes, which follow a coder named Lily Chan (Sonoya Mizuno, who also appeared in Ex Machina) who works for a Silicon Valley tech company called Amaya. A series of events leads Lily deeper and deeper into the secretive lab housed on the Amaya campus, known as Devs short for development. To say too much about the plot would ruin the unfolding narrative, but its enough to know that Devs houses a powerful quantum computer that has the potential to change our understanding of the universe. Nick Offerman plays Amayas chief executive, a man with dubious intentions, and Alison Pill embodies his severe right-hand woman, Katie.

Although the show is set in the present day, the technology depicted therein reflects some supposition, pushing past whats currently possible.

Karl Glusman, left, and Nick Offerman on the secluded Silicon Valley campus at the center of Devs.

(Miya Mizuno/FX)

Its got something in common with Ex Machina in that its sort of 10 years into the future, Garland notes. It allows for a big breakthrough, specifically in terms of computing, which is a thing that is currently being worked on It could really happen in the same way Ex Machina could really happen. Which is to say it probably couldnt happen, but something like it could happen. So maybe not that exact thing, but something very substantially important could easily flow from quantum computers.

The director, along with Mizuno, visited Googles quantum computer lab in Goleta, Calif., ahead of shooting and did extensive research while writing. He found the YouTube series PBS Space Time With Dr. Matt ODowd helpful in breaking down the subject. Garland spoke with people in Silicon Valley, including coders in the quantum labs. Which means that the series is in some ways accurate to contemporary American tech companies. But in terms of quantum computers, of which there are an undetermined number in existence, Devs hovers in a fictional space.

The people who are doing what quantum computers are doing are not remotely interested in trying to do the things talked about in Devs, nor would they be able to, Garland says. This is a speculation, a bit like the way Ex Machina speculates on a level of artificial intelligence that were not even close to achieving. Its more that there are underlying principles [in effect].

Garland was also interested in the state of private tech companies, modeling Offermans character, Forest, after an aging NoCal hippie, beard and all. The director is skeptical of anyone who is put on a pedestal like Steve Jobs or Mark Zuckerberg, because tapping into the tech bubble doesnt necessarily make you a scientific genius. It might just mean you were in the right place with the right thing at the right time.

Devs creator Alex Garland

Theres a line in the show where Forest is described as a genius and then someone says, Hes not a genius, hes an entrepreneur, Garland says. I was interested in the idea that we ascribe genius-like qualities to the people who run tech companies. I was thinking, Im not sure thats true. Im inherently skeptical of anything that gets deified, but also because it seemed reasonably apparent to me that some of these people are not geniuses. They are entrepreneurs. I was riffing off that. I got quite hung up on an idea that Silicon Valley was much more capitalist than we tend to see it as.

For Offerman, who jumped at the chance to work with Garland, Forest represents the nebulous sort of character who is vastly more interesting than one who is simply a villain.

As the eight episodes unfold, your idea of Who are the protagonists and who are the antagonists? becomes really murky, Offerman says. Which is really interesting, because I think thats true of real life. Especially in this crazy political climate we want everything to be really polarized. Is it right or is it wrong? Are you an [expletive] or are you a Democrat? You eventually come to learn why [Forest] does what he does and its pretty understandable. While you may or may not agree with his methods, you can have some empathy.

Mizuno felt similarly about her character. Lily is surprising, she says. Shes an outsider. She doesnt do everything everyone else does. She doesnt participate in groupthink the way most people do.

Devs actor Alison Pill once aspired to study quantum computing.

(Miya Mizuno/FX)

Pill, who wanted to study quantum mechanics after high school thanks to reading Gary Zukavs The Dancing Wu Li Masters, found Devs compelling because it allowed for deeper thoughts than the average TV series. She read extensively ahead of production, including A Briefer History of Time and David Foster Wallaces Everything and More: A Compact History of Infinity, and has continued to consider the philosophical ramifications of quantum computing ever since.

Having been unpracticed in thinking about these things, it was such a gift to be given a project that asks these questions, she says. Because I think people like thinking about this stuff. We forget sometimes we have so much magic around us regularly The challenge Alex poses to his viewers is one thats not Youre going to be overwhelmed by the science. Its Youre going to be overwhelmed by existence.

Alex has a predilection for examining our amazing ability to create technology and further explore the vast reaches of physics, Offerman adds. And then, naturally, the trouble that gets us into. The great dichotomy of bipedal primates being handed a smartphone: On one hand, you can do amazing things with it. And on the other hand, you can send pictures of your genitals to your intern and get in a lot of trouble.

Ultimately, Devs asks a lot of questions, but it does so in the context of a story about a group of individuals who are personally affected by the science and technology. Garland keeps it personal, because he feels that these sorts of lofty issues are inherently personal, affecting each of us as technology advances and private tech companies grow. For him, science is an entry point for a discussion of what it means to be alive. The series cant offer any real answers, but it can allow viewers to consider what those might be.

[Science is] seen as something which is dry and boring and hard to understand and thinks it has all the answers and all of those things are the opposite of what is actually the case, he says. Most scientists will talk more about what they dont know than about what they do know. Science contains not just philosophy but also poetry.

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'Devs': How the FX on Hulu show's tech compares with reality - Los Angeles Times

Cambridge Quantum Computing (CQC) is looking to explore and advance the application of quantum technologies to particle physics as part of the QUATERNION project in the CERN openlab.

Quantum computers and their potential is being researched by CERN through the openlab. The team is collaborating with major hardware vendors and users of quantum computing, launching a number of projects in this realm.

According to CERN, the enhanced computational capabilities of quantum computers could help to improve the analysis and classification of their vast data sets, thus helping to push back the boundaries of particle physics.

More recently, the CERN openlab team have stated they will leverage the power of t|ket, CQC's proprietary quantum development platform for the QUATERNION project.

CQC's t|ket converts machine-independent quantum circuits into executable circuits, reducing the number of required operations whilst optimising physical qubit arrangements.

The architecture-agnostic nature of t|ket will help the members of the CERN openlab project team to work across multiple platforms to achieve optimal results even on today's noisy quantum hardware, CERN states.

The QUATERNION project will also investigate the application of CQC's four qubit quantum technology device named Ironbridge to CERN's Monte Carlo methods for data analysis.

Such methods are not only a vital component of particle physics research, but are also applicable to many other areas, such as financial and climate modelling, CERN states.

Monte Carlo methods use high-quality entropy sources to simulate and analyse complex data. Using CQC's IronBridge platform, the world's first commercially available device-independent and quantum-certifiable cryptographic device, the teams will investigate for the first time the effects of certified entropy on Monte Carlo simulations.

CQC founder and CEO Ilyas Khan says, We are excited to collaborate with CERN, the European Laboratory for Particle Physics, on this innovative quantum computing based research project.

CQC is focussed on using the world's best science to develop technologies for the coming quantum age. Joining CERN openlab is a special development for any organisation and we look forward to developing advances together.

CERN openlab head Alberto Di Meglio says, Our unique public-private partnership works to accelerate the development of cutting-edge computing technologies for our research community.

Quantum computing research is one of the most exciting areas of study today; we are pleased to welcome CQC and their world-class scientists into collaboration with us.

CQC is a quantum computing software company that builds tools for the commercialisation of quantum technologies that will have a global impact.

CQC combines expertise in quantum software, specifically a quantum development platform (t|ket), enterprise applications in the areas of quantum chemistry (EUMEN), quantum machine learning (QML), and quantum augmented cybersecurity (IronBridge).

The company states it has a deep commitment to the cultivation of scientific research.

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Cambridge Quantum Computing teams up with CERN to advance quantum technologies - IT Brief Australia