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Quantum computers have been on my mind a lot lately. A friend who likes investing in tech, and who knows about my attempt to learn quantum mechanics, has been sending me articles on how quantum computers might help solve some of the biggest and most complex challenges we face as humans, as a Forbes commentator declared recently. My friend asks, What do you think, Mr. Science Writer? Are quantum computers really the next big thing?

Ive also had exchanges with two quantum-computing experts with distinct perspectives on the technologys prospects. One is computer scientist Scott Aaronson, who has, as I once put it, one of the highest intelligence/pretension ratios Ive ever encountered. Not to embarrass him further, but I see Aaronson as the conscience of quantum computing, someone who helps keep the field honest.

The other expert is physicist Terry Rudolph. He is a co-author, the R, of the PBR theorem, which, along with its better-known predecessor, Bells theorem, lays bare the peculiarities of quantum behavior. In 2011 Nature described the PBR Theorem as the most important general theorem relating to the foundations of quantum mechanics since Bells theorem was published in 1964. Rudolph is also the author of Q Is for Quantum and co-founder of the quantum-computing startup PsiQuantum. Aaronson and Rudolph are on friendly terms; they co-authored a paper in 2007, and Rudolph wrote about Q Is for Quantum on Aaronsons blog. In this column, Ill summarize their views and try to reach a coherent conclusion.

First, a little background. Quantum computers exploit superposition (a particle inhabits two or more mutually exclusive states at the same time) and entanglement (a special form of superposition, in which two or more particles influence each other in spooky ways) to do things that ordinary computers cant. A bit, the basic unit of information of a conventional computer, can be in one of two states, representing a one or zero. Quantum computers, in contrast, traffic in qubits, which are constructed out of superposed particles that embody numerous states simultaneously.

For decades, quantum computing has been little more than a hypothesis, or laboratory curiosity, as researchers wrestled with the technical complexities of maintaining superposition and entanglement for long enough to perform useful calculations. (Remember that as soon as you look at an electron or cat, its superposition vanishes.) Now, tech giants like IBM, Amazon, Microsoft and Google have invested in quantum computing, as have many smaller companies, 193 by one count. In March, the startup IonQ announced a $2 billion deal that would make it the first publicly traded firm dedicated to quantum computers.

The Wall Street Journal reports that IonQ plans to produce a device roughly the size of an Xbox videogame console by 2023. Quantum computing, the Journal states, could speed up calculations related to finance, drug and materials discovery, artificial intelligence and others, andcrack many of the defensesused to secure the internet. According to Business Insider, quantum machines could help us cure cancer, and even take steps to reverse climate change.

This is the sort of hype that bugs Scott Aaronson. He became a computer scientist because he believes in the potential of quantum computing and wants to help develop it. Hed love to see someone build a machine that proves the naysayers wrong. But he worries that researchers are making promises they cant keep. Last month, Aaronson fretted on his blog Shtetl-Optimized that the hype, which he has been countering for years, has gotten especially egregious lately.

Whats new, Aaronson wrote, is that millions of dollars are now potentially available to quantum computing researchers, along with equity, stock options, and whatever else causes ka-ching sound effects and bulging eyes with dollar signs. And in many cases, to have a shot at such riches, all an expert needs to do is profess optimism that quantum computing will have revolutionary, world-changing applications and have themsoon. Or at least, not object too strongly when others say that. Aaronson elaborated on his concerns in a two-hour discussion on the media platform Clubhouse. Below I summarize a few of his points.

Quantum-computing enthusiasts have declared that the technology will supercharge machine learning. It will revolutionize the simulation of complex phenomena in chemistry, neuroscience, medicine, economics and other fields. It will solve the traveling-salesman problem and other conundrums that resist solution by conventional computers. Its still not clear whether quantum computing will achieve these goals, Aaronson says, adding that optimists might be in for a rude awakening.

Popular accounts often imply that quantum computers, because superposition and entanglement allow them to carry out multiple computations at the same time, are simply faster versions of conventional computers. Those accounts are misleading, Aaronson says. Compared to conventional computers, quantum computers are unnatural devices that might be best suited to a relatively narrow range of applications, notably simulating systems dominated by quantum effects.

The ability of a quantum computer to surpass the fastest conventional machine is known as quantum supremacy, a phrase coined by physicist John Preskill in 2012. Demonstrating quantum supremacy is extremely difficult. Even in conventional computing, proving that your algorithm beats mine isnt straightforward. You must pick a task that represents a fair test and choose valid methods of measuring speed and accuracy. The outcomes of tests are also prone to misinterpretation and confirmation bias. Testing creates an enormous space for mischief, Aaronson says.

Moreover, the hardware and software of conventional computers keeps improving. By the time quantum computers are ready for the marketplace, they might lose potential customersif, for example, classical computers become powerful enough to simulate the quantum systems that chemists and materials scientists actually care about in real life, Aaronson says. Although quantum computers would retain their theoretical advantage, their practical impact would be less.

As quantum computing attracts more attention and funding, Aaronson says, researchers may mislead investors, government agencies, journalists, the public and, worst of all, themselves about their works potential. If researchers cant keep their promises, excitement might give way to doubt, disappointment and anger, Aaronson warns. The field might lose funding and talent and lapse into a quantum-computer winter like those that have plagued artificial intelligence.

Lots of other technologiesgenetic engineering, high-temperature superconductors, nanotechnology and fusion energy come to mindhave gone through phases of irrational exuberance. But something about quantum computing makes it especially prone to hype, Aaronson suggests, perhaps because quantum stands for something cool you shouldnt be able to understand.

And that brings me back to Terry Rudolph. In January, after reading about my struggle to understand the Schrdinger equation, Rudolph emailed me to suggest that I read Q Is for Quantum. The 153-page book explains quantum mechanics with a little arithmetic and algebra and lots of diagrams of black-and-white balls going in and out of boxes. Q Is for Quantum has given me more insight into quantum mechanics, and quantum computing, than anything Ive ever read.

Rudolph begins by outlining simple rules underlying conventional computing, which allow for the manipulation of bits. He then shifts to the odd rules of quantum computing, which stem from superposition and entanglement. He details how quantum computing can solve a specific problemone involving thieves stealing code-protected gold bars from a vault--much more readily than conventional computing. But he emphasizes, like Aaronson, that the technology has limits; it cannot compute the uncomputable.

After I read Q Is for Quantum, Rudolph patiently answered my questions about it. You can find our exchange (which assumes familiarity with the book) here. He also answered my questions about PsiQuantum, the firm he co-founded in 2016, which until recently has avoided publicity. Although he is wittily modest about his talents as a physicist (which adds to the charm of Q Is for Quantum), Rudolph is boosterish about PsiQuantum. He shares Aaronsons concerns about hype, and the difficulties of establishing quantum supremacy, but he says those concerns do not apply to PsiQuantum.

The company, he says, is closer than any other firm by a very large margin to building a useful quantum computer, one that solves an impactful problem that we would not have been able to solve otherwise (e.g., something from quantum chemistry which has real-world uses). He adds, Obviously, I have biases, and people will naturally discount my opinions. But I have spent a lot oftime quantitatively comparing what we are doing to others.

Rudolph and other experts contend that a useful quantum computer with robust error-correction will require millions of qubits. PsiQuantum, which constructs qubits out of light, expects by the middle of the decade to be building fault-tolerant quantum computers with fully manufactured components capable of scaling to a million or morequbits, Rudolph says. PsiQuantum has partnered with the semiconductor manufacturer GlobalFoundries to achieve its goal. The machines will be room-sized, comparable to supercomputers or data centers. Most users will access the computers remotely.

Could PsiQuantum really be leading all the competition by a wide margin, as Rudolph claims? Can it really produce a commercially viable machine by 2025? I dont know. Quantum mechanics and quantum computing still baffle me. Im certainly not going to advise my friend or anyone else to invest in quantum computers. But I trust Rudolph, just as I trust Aaronson.

Way back in 1994, I wrote a brief report for Scientific American on quantum computers, noting that they could, in principle, perform tasks beyond the range of any classical device. Ive been intrigued by quantum computing ever since. If this technology gives scientists more powerful tools for simulating complex phenomena, and especially the quantum weirdness at the heart of things, maybe it will give science the jump start it badly needs. Who knows? I hope PsiQuantum helps quantum computing live up to the hype.

This is an opinion and analysis article.

Further Reading:

Will Artificial Intelligence Ever Live Up to Its Hype?

Is the Schrdinger Equation True?

Quantum Mechanics, the Chinese Room Experiment and the Limits of Understanding

Quantum Mechanics, the Mind-Body Problem and Negative Theology

For more ruminations on quantum mechanics, see my new bookPay Attention: Sex, Death, and Science and Tragedy and Telepathy, a chapter in my free online bookMind-Body Problems.

Continued here:
Will Quantum Computing Ever Live Up to Its Hype? - Scientific American

What youll learn:

A couple examples from history highlight our failure to secure the technology thats playing an increasingly larger role in both our personal lives and business. When computers were first connected to the internet, we had no idea of the Pandoras Box that was being opened, and cybersecurity wasnt even considered a thing. We failed to learn our lesson when mobile phones exploded onto the world and again with IoT still making fast to market more important than security. This has constantly left cybersecurity behind the 8 ball in the ongoing effort to secure data.

As we race to quantum computing, well see another, and perhaps the greatest, fundamental shift in the way computing is done. Quantum computers promise to deliver an increase in computing power that could spur enormous breakthroughs in disease research, understanding global climate, and delving into the origins of the universe.

As a result, the goal to further advance quantum-computing research has rightfully attracted a lot of attention and funding including $625 million from the U.S. government.1 However, it also will make many of our trusted security techniques inadequate, enabling encryption to be broken in minutes or hours instead of the thousands of years it currently takes.

Two important algorithms that serve as a basis for security of most commonly utilized public-key algorithms today will be broken by quantum computers:

As we prepare for a post-quantum world, we have another opportunity to get security right. The challenge of replacing the existing public-key cryptography in these applications with quantum-computer-resistant cryptography is going to be formidable.

Todays state-of-the-art quantum computers are so limited that while they can break toy examples, they dont endanger commercially used key sizes (such as specified in NIST SP800-57). However, most experts agree its only a matter of time until quantum computers evolve to the point of being able to break todays cryptography.

Cryptographers around the world have been studying the issue of post-quantum cryptography (PQC), and NIST has started a standardization process. However, even though were likely five to 10 years away from quantum computers becoming widely available, were approaching what can be described as the event horizon.

Data that has been cryptographically protected by quantum-broken algorithms up to Day 0 of the PQC deployment will likely need to remain secure for years decades in some cases after quantum computers are in use. This is known as Moscas Theorem (see figure).

%{[ data-embed-type="image" data-embed-id="6081ce0f2f5c1329008b4613" data-embed-element="span" data-embed-size="640w" data-embed-alt="Illustration of a bad outcome under Mosca’s Theorem, where a quantum adversary can break the security requirements for recorded messages. The adversary could, for example, break the encryption on a recorded message or alter a legal document and generate a fake signature indistinguishable from a valid signature." data-embed-src="https://img.electronicdesign.com/files/base/ebm/electronicdesign/image/2021/04/PQC_Event_Horizon_Figure_1.6081ce0f24f07.png?auto=format&fit=max&w=1440" data-embed-caption="Illustration of a bad outcome under Moscas Theorem, where a quantum adversary can break the security requirements for recorded messages. The adversary could, for example, break the encryption on a recorded message or alter a legal document and generate a fake signature indistinguishable from a valid signature." ]}%

Deploying any secure solution takes time. Given the inherent longer development time of chips compared to software, chip-based security becomes even more pressing. Throw in the added challenge that PQC depends on entirely new algorithms, and our ability to protect against quantum computers will take many years to deploy. All this adds up to make PQC a moving target.

The good news is that, and I take heart in this, we seem to have learned from previous mistakes, and NISTs PQC standardization process is working. The effort has been underway for more than four years and has narrowed entrants from 69 to seven (four in the category of public-key encryption and three in the category of digital signatures) over three rounds.

However, in late January 2021, NIST started reevaluating a couple of the current finalists and is considering adding new entries as well as some of the candidates from the stand-by list. As mentioned previously, addressing PQC isnt an incremental step. Were learning as we go, which makes it difficult to know what you dont know.

The current finalists were heavily skewed toward a lattice-based scheme. What the potential new direction by NIST indicates is that as the community has continued studying the algorithms, lattice-based schemes may not be the holy grail we first had hoped.

Someone outside the industry may look at that as a failure, but I would argue thats an incorrect conclusion. Only by trial and error, facing failure and course correcting along the way, can we hope to develop effective PQC algorithms before quantum computers open another, potentially worse cybersecurity Pandoras box. If we fail to secure it, we risk more catastrophic security vulnerabilities than weve ever seen: Aggressors could cripple governments, economies, hospitals, and other critical infrastructure in a matter of hours.

While its old hat to say, Its time the world took notice of security and give it a seat at the table, the time to deliver on that sentiment is now.

Reference

1. Reuters, U.S. to spend $625 million in five quantum information research hubs

See the article here:
Are We Doomed to Repeat History? The Looming Quantum Computer Event Horizon - Electronic Design

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."

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

After a year in which scientists raced to understand Covid-19 and to develop treatments and vaccines to stop its spread, Cleveland Clinic is partnering with IBM to use next-generation technologies to advance healthcare research and potentially prevent the next public health crisis.

The two organizations on Tuesday announced the creation of the "Discovery Accelerator," which will apply technologies such as quantum computing and artificial intelligence to pressing life sciences research questions. As part of the partnership, Cleveland Clinic will become the first private-sector institution to buy and operate an on-site IBM quantum computer, called the Q System One. Currently, such machines only exist in IBM labs and data centers.

Quantum computing is expected to expedite the rate of discovery and help tackle problems with which existing computers struggle.

The accelerator is part of Cleveland Clinic's new Global Center for Pathogen Research & Human Health, a facility introduced in January on the heels of a $500 million investment by the clinic, the state of Ohio and economic development nonprofit JobsOhio to spur innovation in the Cleveland area.

The new center is dedicated to researching and developing treatments for viruses and other disease-causing organisms. That will include some research on Covid-19, including why it causes ongoing symptoms (also called "long Covid") for some who have been infected.

"Covid-19 is an example" of how the center and its new technologies will be used, said Dr. Lara Jehi, chief research information officer at the Cleveland Clinic.

"But ... what we want is to prevent the next Covid-19," Jehi told CNN Business. "Or if it happens, to be ready for it so that we don't have to, as a country, put everything on hold and put all of our resources into just treating this emergency. We want to be proactive and not reactive."

Quantum computers process information in a fundamentally different way from regular computers, so they will be able to solve problems that today's computers can't. They can, for example, test multiple solutions to a problem at once, making it possible to come up with an answer in a fraction of the time it would take a different machine.

Applied to healthcare research, that capability is expected to be useful for modeling molecules and how they interact, which could accelerate the development of new pharmaceuticals. Quantum computers could also improve genetic sequencing to help with cancer research, and design more efficient, effective clinical trials for new drugs, Jehi said.

Ultimately, Cleveland Clinic and IBM expect that applying quantum and other advanced technologies to healthcare research will speed up the rate of discovery and product development. Currently, the average time from scientific discovery in a lab to getting a drug to a patient is around 17 years, according to the National Institutes of Health.

"We really need to accelerate," Jehi said. "What we learned with the Covid-19 pandemic is that we cannot afford, as a human race, to just drop everything and focus on one emergency at a time."

Part of the problem: It takes a long time to process and analyze the massive amount of data generated by healthcare, research and trials something that AI, quantum computing and high-performance computing (a more powerful version of traditional computing) can help with. Quantum computers do that by "simulating the world," said Dario Gil, director of IBM Research.

"Instead of conducting physical experiments, you're conducting them virtually, and because you're doing them virtually through computers, it's much faster," Gil said.

For IBM, the partnership represents an important proof point for commercial applications of quantum computing. IBM currently offers access to quantum computers via the cloud to 134 institutions, including Goldman Sachs and Daimler, but building a dedicated machine on-site for one organization is a big step forward.

"What we're seeing is the emergency of quantum as a new industry within the world of information technology and computing," Gil said. "What we're seeing here in the context of Cleveland Clinic is ... a partner that says, 'I want the entire capacity of a full quantum computer to be [dedicated] to my research mission."

The partnership also includes a training element that will help educate people on how to use quantum computing for research which is likely to further grow the ecosystem around the new technology.

Cleveland Clinic and IBM declined to detail the cost of the quantum system being installed on the clinic's campus, but representatives from both organizations called it a "significant investment." Quantum computers are complex machines to build and maintain because they must be stored at extremely cold temperatures (think: 200 times colder than outer space).

The Cleveland Clinic will start by using IBM's quantum computing cloud offering while waiting for its on-premises machine to be built, which is expected to take about a year. IBM plans to later install at the clinic a more advanced version of its quantum computer once it is developed in the coming years.

Jehi, the Cleveland Clinic research lead, acknowledged that quantum computing technology is still nascent, but said the organization wanted to get in on the ground floor.

"It naturally needs nurturing and growing so that we can figure out what are its applications in healthcare," Jehi said. "It was important to us that we design those applications and we learn them ourselves, rather than waiting for others to develop them."

Read more:
Cleveland Clinic and IBM hope their tech partnership could help prevent the next pandemic - WTHITV.com

Quantum Computing Market is a professional and a detailed report focusing on primary and secondary drivers, market share, leading segments and geographical analysis. This analysis provides an examination of various market segments that are relied upon to observe the fastest development amid the estimated forecast frame. The report encompasses market definition, currency and pricing, market segmentation, market overview, premium insights, key insights and company profile of the key market players. The persuasive Quantum Computing market report also helps to know about the types of consumers, their response and views about particular products, and their thoughts for the step up of a product.

Quantum computing is an advanced developing computer technology which is based on the quantum mechanics and quantum theory. The quantum computer has been used for the quantum computing which follows the concepts of quantum physics. The quantum computing is different from the classical computing in terms of speed, bits and the data. The classical computing uses two bits only named as 0 and 1, whereas the quantum computing uses all the states in between the 0 and 1, which helps in better results and high speed. Quantum computing has been used mostly in the research for comparing the numerous solutions and to find an optimum solution for a complex problem and it has been used in the sectors like chemicals, utilities, defence, healthcare & pharmaceuticals and various other sectors. Quantum computing is used for the applications like cryptography, machine learning, algorithms, quantum simulation, quantum parallelism and others on the basis of the technologies of qubits like super conducting qubits, trapped ion qubits and semiconductor qubits. Since the technology is still in its growing phase, there are many research operations conducted by various organizations and universities including study on quantum computing for providing advanced and modified solutions for different applications. For instance, Mercedes Benz has been conducting research over the quantum computing and how it can be used for discovering the new battery materials for advanced batteries which can be used in electric cars. Mercedes Benz has been working in collaboration with the IBM on IBM Q network program, which allows the companies in accessing the IBMs Q network and early stage computing systems over the cloud. Global quantum computing market is projected to register a healthy CAGR of 29.5% in the forecast period of 2019 to 2026.

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Quantum Computing Market Scope and Segmentation:

Global quantum computing market is segmented into seven notable segments which are system, qubits, deployment model, component, application, logic gates and vertical.

Quantum Computing Market Country Level Analysis

For detailed insights on Global Quantum Computing Market Size, competitive landscape is provided i.e. Revenue Share Analysis (Million USD) by Players, Revenue Market Share (%) by Players and further a qualitative analysis is made towards market concentration rate, product differentiation, new entrants are also considered in heat map concentration.

New Business Strategies, Challenges & Policies are mentioned in Table of Content, Request TOC at @https://www.databridgemarketresearch.com/toc/?dbmr=global-quantum-computing-market&Somesh

Leading Key Players Operating in the Quantum Computing Market Includes:

Some of the major players operating in this market are Honeywell International, Inc., Accenture, Fujitsu, Rigetti & Co, Inc., 1QB Information Technologies, Inc., IonQ, Atom Computing, ID Quantique, QuintessenceLabs, Toshiba Research Europe Ltd, Google,Inc., Microsoft Corporation, Xanadu, Magiq Technologies, Inc., QX branch, NEC Corporation, Anyon System,Inc. Cambridge Quantum Computing Limited, QC Ware Corp, Intel Corporation and others.

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The Quantum Computing Market research covers a comprehensive analysis of the following facts:

Table of Content:

PART 01: EXECUTIVE SUMMARY

PART 02: SCOPE OF THE REPORT

PART 03: RESEARCH METHODOLOGY

PART 04: INTRODUCTION

PART 05: MARKET LANDSCAPE

PART 06: MARKET SIZING

PART 07: FIVE FORCES ANALYSIS

PART 08: MARKET SEGMENTATION BY PRODUCT

PART 09: MARKET SEGMENTATION BY DISTRIBUTION CHANNEL

PART 10: CUSTOMER LANDSCAPE

PART 11: MARKET SEGMENTATION BY END-USER

PART 12: REGIONAL LANDSCAPE

PART 13: DECISION FRAMEWORK

PART 14: DRIVERS AND CHALLENGES

PART 15: MARKET TRENDS

PART 16: COMPETITIVE LANDSCAPE

PART 17: COMPANY PROFILES

PART 18: APPENDIX

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Quantum Computing Market Share Current and Future Industry Trends, 2020 to 2027 The Courier - The Courier