Let's say, for the sake of argument, that quantum computers will exist in some useful fashion in the not too distant future.

And if that is the case, fundamental changes will be needed in education, supply chains, and national policies for us to use the machines to solve complex problems, panelists said a forum hosted by R Street Institute this week.

"We need ... to prepare people to think about computation in a fundamentally different way," said Chris Fall, senior advisor at the Center for Strategic and International Studies, during the discussion.

On conventional computers, information is encoded in strings of 0s and 1s, while in quantum computers, information is encoded in quantum bits that have a value of 0, 1, or a superposition of both states. This allows quantum computers to store much more information than a classic machine and process it in less time, in theory. There are limitations, such as the fact that they are unstable and prone to error despite efforts to address that, and may hit a wall if unprotected from background radiation. Encryption-breaking quantum computers are forever 15 years away.

Sorry, yes, we're assuming they will eventually work.

Google, D-Wave, IBM, Intel, Microsoft, Honeywell, and so on, are building qubits in different ways. Their goal is to build fault-tolerant machines that can run super-fast calculations by tempering qubit behavior and correcting errors introduced from the environment.

"The routine manipulation of the properties of single atoms in people's devices, devices, cars that is going to change everything. We don't have a full understanding of how that's going to happen." Fall said.

Starting now, education needs to be better for people to take advantage of the quantum processing breakthroughs as the hardware journey matures, the panelists said. Problem solving and algorithms will look very different in areas like finance and science, for example.

"The language of quantum algorithms are linear algebra and probabilities. This is not something that we do a good job of teaching our kids from a very early stage. That is kind of where we need to get started now," Fall said.

Quantum computing is a different problem-solving system and calculates differently from conventional computers, was the gist of the discussion.

Governments will need to drive change if quantum computing is a matter of national interest and public need, said Scott Friedman, a senior policy advisor of the House Homeland Security Committee.

Global legislation to protect semiconductor supply chains, like the CHIPS for America Act and Europe's Chips Act, needs to factor in quantum computing infrastructure, panelists said.

Most cryogenic refrigerators for quantum computers are made in Europe, and the United States needs to work with allies to secure those supply chains, said Allison Schwartz, global government relations and public affairs leader at quantum computer maker D-Wave Systems.

The government also needs to facilitate collaboration and bridge a gap between educators, developers, and scientists involved in algorithms and developing hardware, the panelists said.

The US introduced legislation called QUEST (Quantum User Expansion for Science and Technology) for increased access of quantum hardware and resources for research and further education. A National Quantum Initiative Act (NQI) was signed into law in 2018 to supercharge quantum computing development and research, but activity around these have stalled.

"The advisory committee for the NQI hasn't met in a while ... on the executive branch side. An easy next step to bring more focus in this area would be to convene that again and get broader input from the community," said Kate Weber, policy lead for quantum, robotics, and fundamental research at Google, which hopes to a build a fault-tolerant computer by 2030.

The moderator, R Street Institute senior fellow Miles Taylor, raised the idea of quantum computers creating sentient beings, much like the machines in the Terminator movies.

"I don't know if we're going to have a sentient computer," CSIS's Fall said, adding, "we're learning to manipulate single atoms at ... industrial scale. That's not a laboratory project. It'll change the world."

See the original post here:
'Quantum computer algorithms are linear algebra, probabilities. This is not something that we do a good job of teaching our kids' - The Register

IonQ on Friday became the first quantum computing hardware company to go public, via a special purpose acquisition company (SPAC).

Why it matters: Quantum represents the next generation of computing, and while the industry is likely still years away from producing widely reliable hardware, IonQ's performance should be an indicator of how the market views the technology's potential.

Stay on top of the latest market trends and economic insights with Axios Markets. Subscribe for free

What's happening: IonQ began trading on the New York Stock Exchange Friday morning, and it ended the day down about 10%.

How it works: Maryland-based IonQ, which was founded in 2015, employs powerful lasers to trap ions from the rare Earth metal ytterbium, and uses them to form quantum bits or qubits the basic unit of quantum computing.

The company already produces a 22-qubit quantum computer that it sells access to through AWS, Microsoft Azure and Google Cloud platforms.

Fidelity is using IonQ's hardware to create algorithms that can crunch historical data to determine the likelihood of a borrower defaulting on a loan, while Goldman Sachs uses it to determine how the movement of one company's stock price is affected by changes in another company's price.

What they're saying: "It's still early in the overall lifecycle of the quantum market, but this is like asking investors whether they would have wanted to invest in Apple when the Apple II computer came out," says Peter Chapman, IonQ's CEO.

The catch: IonQ doesn't disclose its revenues though the company has said publicly it's in the "eight figures" and even some quantum computing experts believe the industry's promises have outpaced its accomplishments.

What to watch: Chapman says IonQ will use the capital raised from going public to fund its efforts to build a 64-qubit chip by the end of 2023.

Story continues

He claims those chips will eventually be able to be networked together to provide more than 1,000 qubits of processing power the level many experts believe is required before quantum computers can reliably outperform cloud-accessible classical supercomputers.

What's next: The XPRIZE Foundation announced yesterday that it would work with the Geneva Science and Diplomacy Anticipator to launch a global quantum computing innovation contest.

"The world faces massive computational problems, and we believe quantum computers can really help," says XPRIZE's Amir Banifatemi.

More from Axios: Sign up to get the latest market trends with Axios Markets. Subscribe for free

Read the original post:
IonQ becomes the first quantum computing hardware firm to go public - Yahoo News

Miles Tayler, senior fellow at the R Street Institute, recently moderated a fascinating panel on quantum computing.

Several others were with him on the panel: Chris Fall, Ph.D., senior adviser, presidents office, Center for Strategic and International Studies; Scott Friedman, senior policy adviser, House Homeland Security Committee; Allison Schwartz, global government relations and public affairs leader, D-Wave Systems; and Kate Weber, Ph.D., policy lead for quantum, robotics, and fundamental research, Google.

They spoke about the practical applications of quantum computing, how the U.S. was falling behind several companies on this technology, and why that could be a terrible thing.

Lets talk about quantum computing and how it will be a game-changer for everything from simulation and modeling to artificial intelligence (AI). Im pretty sure we arent ready for a quantum AI:

While we are still at least a decade from when we get to a point when quantum computers can even begin to reach their full potential, quantum emulators and current generation quantum computers are beginning to do some real work.

We are learning that quantum computers are naturally better when emulating and interacting with reality, because nature doesnt consist of just 1s and Os. The more complex a problem, the better able a quantum computer can deal with it.

Initial applications are increasingly focused on logistic types of problems with many moving parts. For instance, it is being used heavily by foreign governments that use it for logistics management, such as Australias military using autonomous vehicles that dont put soldiers or contractors at risk. Current generation computers were not powerful enough, and since the military lives or dies on logistics, having a far more effective tool using quantum computing could.

Australia would have an increasing advantage over time if it came to open conflict due to a quantum tool to aid in logistics. In addition, applied to emerging intelligent weapons, like drone swarms, quantum computing should position the drones collectively for maximum impact more effectively. Together, these two implementations would give a military unit with this capability a significant advantage over those that do not.

Other examples are emergency response modeling and execution. The quantum computer is first asked to create a plan for a major disaster. It then assists in getting the available resources to those that most need them and mapping out and dynamically changing the plan for evacuations depending on then-current conditions.

See more: IBM Partnering with University of Tokyo on Quantum Computer

But things get interesting when we add quantum computing capability to an AI. Quantum computing can provide AIs with the ability to emulate emotions and act like they are feeling them. While this alone wouldnt represent sentience, it would be hard to tell the difference. And a quantum AI would be better able to respond to complex signals, like expressions, eye movement, and body language that traditional computers find challenging.

An AI with a quantum back end could perform the role of therapist, say on a submarine or space exploration vessel that couldnt justify a human therapist. And it would be far less likely to be biased, assuming it was properly trained.

A quantum AI would have a significant advantage as a 100% audit function. It would look at every transaction and see whether it was likely fraudulent or in violation of policy from the related metadata. Current human-driven audit organizations dont have the bandwidth for 100% audits and miss a lot of actual crimes because they have to operate from far smaller samples.

Another area where quantum AI would make a considerable difference is government, as it could almost immediately identify graft and bribery. The relevant AI would be able to distribute the limited day-to-day resources daily more effectively, especially during a catastrophe, and assess liability for complex decisions far more accurately.

See more: IBM and the Promise of Quantum Hybrid Deep Learning AI

While quantum computing is still far from its potential, with only a tiny fraction of the number of qubits needed to demonstrate that potential, it is already showing viability in several areas.

Those areas are military, such as in logistics and weapons, smart cities, government, emergency response, modeling, and simulation, where the complex problems are beyond conventional computers capabilities.

These capabilities will be a competitive game-changer for the armed forces, governments, and companies that effectively use this technology first. There will be such a significant advantage in any highly complex market, like stock trading, that those that dont have access to this technology could quickly be eclipsed and made redundant by those that do. Fortunately, there is still time but that time is running out. Should a critical mass of governments, companies, or individuals get access to this technology, theyll have massive advantages over those that dont.

We are not ready for quantum AI, and we are running out of time.

See more: Top Performing Artificial Intelligence Companies

Read more:
Quantum AI: Are We Ready? - Datamation

Taking those questions in reverse order, Aliro Quantum is a young Harvard lab spin-out seeking to deliver the quantum networking technology many believe is critical to scaling up quantum computers. Aliro contends that clustering moderate size quantum computers, say 1000-qubit systems (still not buildable, though IBM says perhaps soon) or bigger, is the most likely way to create something resembling a monolithic 1M-qubit-or-more-sized quantum computer large enough to solve practical problems.

That thesis is at the core of our business model and of many others, said Prineha Narang, Aliro CTO, founder, Harvard professor. People, mostly from the hardware side, are trying to do this with us. Were interfacing down to the hardware getting down to the FPGAs were just not building the quantum hardware. We see the path to scale being through these networks, and those types of networks being part of the bigger picture of these entanglement-generating and entanglement-using large scale networks.

Whether these connected quantum computers end up being called clusters or distributed computing (both terms have currency now) or something else isnt yet clear, she said. Narang and Harvard colleague, John Philbin, have an interesting recentpaper(Computational Materials Insights Into Solid-State Multiqubit Systems) in the APS journal PRX Quantum.

There are, of course, many other quantum networking applications, but in essence they all connect some sort of quantum device (e.g. a sensor) to another quantum device. It should be noted not everyone agrees that clustering is the only or best path to scale-up quantum computers. PsiQuantum, for example, says its photonics-based quantum computer thats leveraging semiconductor fabrication techniques will scale to a million or more qubits.

That said, there is broad agreement that practical, scalable quantum networking is an important ingredient in the development of a robust quantum information sciences landscape. DOE has several related projects and there are similar efforts around the globe.

How do these devices work? Broadly, a quantum network must interface with a quantum computer (or other quantum device), capture and faithfully transmit a qubit-based information stream to another device able to use the data. Accomplishing that requires dealing with familiar quantum challenges: generating entanglement, managing coherency duration, enacting error correction, using quantum memory, and to reach any distance (WANs) reliable repeaters. Also, dont forget there are currently numerous qubit technologies such as semiconductor-based superconducting, trapped ions, cold atom, photonics, etc. A generalizable quantum network would need to be able to interface with any of them.

A positive for quantum networks is mature optical technology; high-quality optic fiber is a good transmission medium and the most viable current option. Aliro is focused on quantum network control plane and protocol development. It is leveraging quantum and traditional networking hardware. Think of Aliro as a little like Mellanox for quantum networking, said Narang.

Putting aside, for a moment, remaining technical challenges, consider Narangs ambitious milestones for Aliro and forecast for quantum networking:

Aliro was spun out of Narangs Harvard lab in 2019 where her research focuses on a variety of quantum topics spanning quantum materials, quantum information, and quantum molecular dynamics. The Aliro headcount is roughly 20 and growing, and Narang cites the greater Boston areas wealth of high tech resources (university, networking tech expertise, talent) as an important factor in deciding to set up shop there.

Weve been developing a control plane. Some of the things Im going to say are very similar to the language youd hear from classical networking. Were thinking about the quantum version in the same way. It has various layers, including a physical layer, like a classical network. The temptation is always, even in classical networking, to say lets do everything in the physical layer because the hardware is becoming better, said Narang.

But the reason classical networking has been so successful is that the details of the physical layer are abstracted away into some of these other layers. This is why every time theres a hardware upgrade, how I think about the internet doesnt change. That abstraction is what enables us to think about issues of timing, synchronization, and connecting these devices in the control plane. Thats really where the key value is.

The idea is to hide the underlying complexity such as qubit modality. Whats the right architecture for connecting to superconducting and trapped ion systems? What amount of architecting with a control plane is needed versus how much is overkill? So what can you do over a quantum channel versus what can you do over the classical channel in order to get the timing right or to get some of the synchronization problems solved? said Narang citing key questions.

We want people to come into this field and not have to figure out all of these other pieces, but to be able to easily interface with these systems. The phrase plug-and-play gets used a lot in the sales. [Quantum networking] is still not plug-and-play but its certainly become much more accessible to a broader set of engineers and scientists than five years ago, she said.

Besides clustering quantum computers, there is a major push to develop a so-called quantum internet. Among potential applications identified in a 2018 Science article are: secure communication, clock synchronization, extending the baseline of telescopes, secure identification, achieving efficient agreement on distributed data, exponential savings in communication, quantum sensor networks, as well as secure access to remote quantum computers in the cloud. (Figure from Science article, 10-31-2018, shown below.)

From a hardware standpoint, key components are missing at the moment, quantum repeaters being a significant one. This is an area where my lab does a lot of work in looking at how we think about third-generation quantum repeaters that actually can enable the kind of capacity you need to have a meaningful large-scale quantum network using solid state components. Theres a lot of talk about this now. DOE has announced a very big roadmap and blueprint to connect the various DOE labs, which, of course, are all across the country. Essentially, this is the quantum version of the ARPANET. And there are some hardware advances needed before we can talk about connecting something as big as that.

Having said that, a metropolitan area network is definitely much more achievable. This is where youre within the repeater-less bound. Theres actually fiber between Harvard, MIT, and Lincoln Labs and these things can be connected. Now, over a network like that, youre not having a very high bandwidth conversation with your buddies on the other side. But these are entanglement using and generating networks, theyre a proof of concept, testbeds. We have one here. Theres one at Argonne and Fermi Lab in the Chicago area, thats getting a lot of attention. These are attempts at figuring out what are the components, both hardware and software, that will become part of a larger scalable network, said Narang.

Narang noted that codesign is important in quantum networking development. As much as we are abstracting away from the hardware, there are also many hardware choices that need to be made that are informed by the protocols (software), said Narang.

Theres a temptation from the hardware community to say, Were going to build out the hardware, these folks are going to throw some software on there and its all going to be great. It turns out theres some hard constraints that are imposed on the hardware, based on some of the protocols and algorithms of interest. So codesign has been a really key component here. Were collaborating very closely with the DOE labs, in particular ESnet based out of LBNL though they (ESnet) have fiber all across the country. [We are working with them] on thinking about how we can emulate these long-haul links because thats where we see the value. We dont see value in simple quantum key distribution (QKD). There are people doing it, but you can look up very public documents from the DOD and NSA that say that they dont view the path in secure communication to be at all related to QKD. So for entanglement generating and using networks, the biggest value really is from having these components and getting to getting to scale.

Aliro envisions being able to spec out the entire network. This would entail having Aliro boxes at both ends and gaining access to existing high-quality fiber in between. Generating entanglement and sharing entanglement are core capabilities required. Quantum memory is also important (needed for repeaters). Routing is also a challenge and Aliro has put forward a set of protocols for routing, said Narang, who is working with the Quantum Internet Research Group (IETF Quantum IRG) seeking to set standards and is active in the NSF-affiliated Center for Quantum Networks.

She expects there to be a variety of node types, think smart and less so. Fees for entanglement-as-a-service would likely be based on both transmission fidelity and transmission rates. Big customers such as a bank might want exotic boxes and pay a premium; others might not require that. The Aliro website lists quantum-secure communications, improved GPS precision and reliability, and accurate positioning, navigation and timing as potential application for its entanglement-as-a-service (EaaS). That seems less connected to the idea of scaling up quantum computers via clustering. To some extent, the promotion may be aspirational as the quantum network world is still nascent.

Were partnering with hardware vendors that weve established relationships with. Im being intentionally a little vague here. Its a tight rope here, said Narang. Currently, if you deliver a network, its going to be slow, the entanglement rates are very slow. And its very small in the sense of the geography because were waiting for repeaters to come online to take this across the country. However, there are a lot of things that we can do to anticipate what kinds of repeaters well have. Were working with various types of architectures at testbeds like, the folks at Argonne, and the folks at Brookhaven. They have different realizations of what a repeater would look like.

Like many, Narang thinks moving quantum processing out of icy cold dilution refrigerators (a few degrees Kelvin) will be an important step. Theres a strong push in my research to look at quantum memories that are at temperatures above four Kelvin that can operate with reasonable fidelity at that temperature, because we think that [operating] with liquid nitrogen cooled (77 kelvin) is no problem, but as soon as youre talking about, you know, these ultra-low temperature, pumped-helium systems, and there are. Shes a fan of solid state memory citing diamond and silicon carbide (color centers) which could offer higher temperature operating ranges.

Choosing partners and technologies is tricky. Weve been in deep conversations with both Google and Amazon and they have very different roadmaps going forward and we havent ourselves decided if would try to achieve both or pick one. There are reasons to pick and there are reasons to not pick, she said.

Likewise, photonics expertise will be critical. Xanadu and PsiQuantum are among the more prominent quantum computer companies trying to develop optically-based systems. PsiQuantum has been very direct about its plans to launch a million-qubit quantum computer.

We have talked with them, said Narang. We dont currently have a signed partnership with them. Were being very cautious to not get tied to one particular photonic platform. We think that we will need a long-term photonic platform partner, whether its going to be PsiQuantum or Xanadu, or another, were not sure. They, on their roadmaps, dont have plans for integrating quantum repeaters.

Thats okay, said Narang, but Aliro would prefer somebody on the photonics side thats interested both in these connected photonic processors, and how you bring in the repeater into the picture.

Stay tuned.

More:
Quantum Networking and Clustering What Is It? Why Should You Care? Who's Aliro? - HPCwire

This week, College Park, Maryland quantum computing company IonQ is officially going public.

Following a merger with dMY Technology Group Inc. III, which is a special purpose acquisition company based in Las Vegas, the firm will begin trading on the New York Stock Exchange on Friday, Oct. 1. The merger was officially approved on Tuesday by dMY III stockholders.

The company will be trading under the symbol IONQ, and CEO Peter Chapman said it is expected to raise $635 million, with an additional $132 million in outstanding warrants. Of this, $350 million will be raised through private investment in public equity (PIPE) funding from investors including Fidelity Management & Research Company, Silver Lake, Breakthrough Energy Ventures, MSD Partners, Hyundaiand Kia.

Founded in 2015 by University of Maryland College Park professor Dr. Chris Monroe and Duke University professor Dr. Jungsang Kim, IonQ specializes in trapped ion quantum computing. Drawing on two decades of research, the company is working to create more powerful computers than those currently available, and apply the technology to solving foundational problems in new ways.

IonQ first announced plans to go public earlier this year, estimating that the company would be valued at $2 billion when the deal closed. Chapman told Technical.ly that the IPO will make IonQ more competitive in talent recruiting and help it to reach the manufacturing stage with its products, particularly in quantum networking.

This was not actually a liquidity event for us, Chapman said. Most people when they get to an IPO, theyre thinking about how can they cash out there. But there isnt anyone actually cashing out. We just thought of this as a means to an end on how to raise money.

Going forward, Chapman said the company expects to double its 90-person team, which is spread across offices in College Park, Seattle and Boston.

Since it announced the IPO in March, 2021 has been a banner year for IonQ. It has landed partnerships that will help to further explore real-world applications of quantum computing with GE Research, the Fidelity Center for Applied Technology, Goldman Sachs and QCWare, Google, Accenture andSoftbank. It is teaming with theUniversity of Maryland on a new lab in College Park.

When it comes to tech advances, the company launched what it says is the industrys first reconfigurable multicore quantum architecture, as well as designed and launched a chipset known as Evaporated Glass Traps. This year also brought its second research credit program cohort, which offers free credits to academics building novel quantum algorithms (Want to know more about quantums rise out of the lab? Check out our explainer here).

[Going public] will lift all the boats in quantum computing in this sense that we can show that it can be done in quantum now, and thats probably good for the entire industry, Chapman said.

Nir Minerbi, CEO and cofounder of Classiq, a fellow quantum company, agrees, although he thinks theres still more work to be done in the industry.

Organizations understand that the ability to extract true business value from quantum computing grows as more qubits with higher quality are available, said Minerbi in a statement. IonQs funding is good news for the industry and their quantum roadmap is encouraging as well.

As the company moves into the new year, Chapman said IonQ will be expanding into the drug discovery, materials science and battery industries. But, he noted, the possibilities with quantum computing offer plenty of new, yet-to-be-discovered options, as well.

Every day at the company is fun. You have a customer thats doing something that has never been done before, Chapman said. Its a pretty exciting place to be.

Originally posted here:
IonQ is set to make its public trading debut. Here's a look at the quantum computing company's 2021 highlights - Technical.ly DC

The global Quantum Computing in Manufacturing market focuses on encompassing major statistical evidence for the Quantum Computing in Manufacturing industry as it offers our readers a value addition on guiding them in encountering the obstacles surrounding the market. A comprehensive addition of several factors such as global distribution, manufacturers, market size, and market factors that affect the global contributions are reported in the study. In addition the Quantum Computing in Manufacturing study also shifts its attention with an in-depth competitive landscape, defined growth opportunities, market share coupled with product type and applications, key companies responsible for the production, and utilized strategies are also marked.

Key players in the global Quantum Computing in Manufacturing market:

International Business Machines (United States), D-Wave Systems (Canada), Microsoft (United States), Amazon (United States), Rigetti Computing (United States), Google (United States), Intel (United States), Honeywell International (United States), Quantum Circuits (United States), QC Ware (United States), Atom Computing, Inc. (United States), Xanadu Quantum Technologies Inc. (Canada), Zapata Computing, Inc. (United States), Strangeworks, Inc (United States)

Free Sample Report + All Related Graphs & Charts @:https://www.advancemarketanalytics.com/sample-report/179263-global-quantum-computing-in-manufacturing-market

Quantum computing is the computing technique that uses the collective resource of quantum states, Some of them main resources are superposition and entanglement, to perform computation. As these are able to execute quantum computations that is why it also called quantum computers. Quantum computing harnesses the phenomena of quantum mechanics to deliver a huge leap forward in computation to solve certain problems. Quantum computing is an area of study focused on the development of computer-based technologies centered on the principles of quantum theory.

On 12 February 2021 To further progress into the quantum age, various projects are in the works to take computing to the next level. After forming a consortium in December, EU stakeholders have launched an effort to supercharge quantum processor production.

Whats Trending in Market?

Integration With Advance Technologies

What are the Market Drivers?

Raising Deposal Income

The Global Quantum Computing in Manufacturing Market segments and Market Data Break Down are illuminated below:

by Application (Simulation & Testing, Financial Modeling, Artificial Intelligence & Machine Learning, Cybersecurity & Cryptography, Other), Component (Quantum Computing Devices, Quantum Computing Software, Quantum Computing Services)

The study encompasses a variety of analytical resources such as SWOT analysis and Porters Five Forces analysis coupled with primary and secondary research methodologies. It covers all the bases surrounding the Quantum Computing in Manufacturing industry as it explores the competitive nature of the market complete with a regional analysis.

Have Any Questions Regarding Global Quantum Computing in Manufacturing Market Report, Ask Our [emailprotected]https://www.advancemarketanalytics.com/enquiry-before-buy/179263-global-quantum-computing-in-manufacturing-market

The Quantum Computing in Manufacturing industry report further exhibits a pattern of analyzing previous data sources gathered from reliable sources and sets a precedent growth trajectory for the Quantum Computing in Manufacturing market. The report also focuses on a comprehensive market revenue streams along with growth patterns, Local reforms, COVID Impact analysis with focused approach on market trends, and the overall growth of the market.

Moreover, the Quantum Computing in Manufacturing report describes the market division based on various parameters and attributes that are based on geographical distribution, product types, applications, etc. The market segmentation clarifies further regional distribution for the Quantum Computing in Manufacturing market, business trends, potential revenue sources, and upcoming market opportunities.

The Quantum Computing in Manufacturing market study further highlights the segmentation of the Quantum Computing in Manufacturing industry on a global distribution. The report focuses on regions of LATAM, North America, Europe, Asia, and the Rest of the World in terms of developing market trends, preferred marketing channels, investment feasibility, long term investments, and business environmental analysis. The Quantum Computing in Manufacturing report also calls attention to investigate product capacity, product price, profit streams, supply to demand ratio, production and market growth rate, and a projected growth forecast.

Read Detailed Index of full Research Study at @https://www.advancemarketanalytics.com/reports/179263-global-quantum-computing-in-manufacturing-market

In addition, the Quantum Computing in Manufacturing market study also covers several factors such as market status, key market trends, growth forecast, and growth opportunities. Furthermore, we analyze the challenges faced by the Quantum Computing in Manufacturing market in terms of global and regional basis. The study also encompasses a number of opportunities and emerging trends which are considered by considering their impact on the global scale in acquiring a majority of the market share.

Some Point of Table of Content:Chapter One: Report OverviewChapter Two: Global Market Growth TrendsChapter Three: Value Chain of Quantum Computing in Manufacturing MarketChapter Four: Players ProfilesChapter Five: Global Quantum Computing in Manufacturing Market Analysis by RegionsChapter Six: North America Quantum Computing in Manufacturing Market Analysis by CountriesChapter Seven: Europe Quantum Computing in Manufacturing Market Analysis by CountriesChapter Eight: Asia-Pacific Quantum Computing in Manufacturing Market Analysis by CountriesChapter Nine: Middle East and Africa Quantum Computing in Manufacturing Market Analysis by CountriesChapter Ten: South America Quantum Computing in Manufacturing Market Analysis by CountriesChapter Eleven: Global Quantum Computing in Manufacturing Market Segment by TypesChapter Twelve: Global Quantum Computing in Manufacturing Market Segment by Applications

Buy This Exclusive Research Here: https://www.advancemarketanalytics.com/buy-now?format=1&report=179263

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, West Europe or Southeast Asia.

Contact US:Craig Francis (PR & Marketing Manager)AMA Research & Media LLPUnit No. 429, Parsonage Road Edison, NJNew Jersey USA 08837Phone: +1 (206) 317 1218[emailprotected]

Link:
Quantum Computing in Manufacturing Market Booming with International Business Machines, D-Wave Systems, Microsoft Canoom - Canoom

BMW has been preparing to be quantum-ready for the past four years.

Quantum computing may still be at an early stage, but BMW has been quietly ramping up plans for the moment when it reaches maturity.

Most recently, the company justlaunched a "quantum computing challenge" a call for talent designed to encourage external organizations to come up with solutions that will help the car manufacturer make the best use of quantum technologies.

"It's a search for hidden gems," Oliver Wick, technology scout at BMW Research and Technology, tells ZDNet.

"It's a clear message to the world that BMW is working on quantum, and if you have innovative algorithms or great hardware, then please come to us and we can check if we could use it for BMW."

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

The challenge, which is run in partnership with Amazon's quantum computing division AWS Braket, is targeting corporations as well as startups and academics with a simple pitch: come up with quantum solutions to the problems that BMW has identified.

Specifically, explains Wick, BMW wants to see four challenges addressed. In the pre-production stage, quantum algorithms could help optimize the configuration of features for the limited number of cars that can be assembled for various tests, so that as many tests as possible can be carried out with a minimal amount of resources.

Similarly, optimization algorithms could improve sensor placement on vehicles, to make sure that the final configurations of sensors can reliably detect obstacles in different driving scenarios something that is becoming increasingly important as autonomous driving becomes more common.

Candidates have also been invited to submit ideas for the simulation of material deformation during production, to predict costly problems in advance, as well as for the use of quantum machine learning to classify imperfections, cracks and scratches during automated quality inspection.

Participants are required to submit a concept proposal for any of the four challenges, after which a panel of experts will shortlist the most promising ideas. The successful candidates will then have a few months to build out their solutions on Amazon Braket, before pitching them next December. Winning ideas will earn a contract with BMW to implement their projects in real-life pilots.

"We are using the power of the crowd to solve our own problems inside BMW," says Wick.

The quantum challenge is only the latest development in a strategy that aims to aggressively push the company's quantum readiness.

BMW's high-performance computers are currently handling 2,000 tasks a day, ranging from high-end visualizations to crash simulations; but even today's most sophisticated systems are fast reaching their computing limits.

Quantum computers, however, could one day carry out computations exponentially faster, meaning that they could resolve problems that classical computers find intractable. For example, the amount of compute power required to optimize vehicle sensor placement is proving to be increasingly challenging for classical algorithms to take on; quantum algorithms, on the other hand, could come up with solutions in minutes. At BMW's production scale, this could mean huge business value.

Wick explains that the potential of quantum computers was identified by the company as early as 2017. A tech report promptly followed to acquire some knowledge about the technology and its key providers, before work started on proofs of concept.

At this stage, says Wick, the biggest challenge was to find out the business case for quantum computing. "We initiated proofs of concept in optimization or scheduling, but those were activities in which no business case was included," says Wick. "Initially, everybody came to me asking why we even needed quantum computing."

But now proof of concepts are slowly starting to emerge as business projects. One of the company's first research proposals, for instance, looked at the use of quantum computers to calculate the optimum circuit to be followed by a robot sealing welding seams on a vehicle. More recently, BMWunveiled that it has been making progress in designing quantum algorithmsfor supply-chain management, which have been successfully tested on Honeywell's 10-qubit system.

SEE: Supercomputers are becoming another cloud service. Here's what it means

BMW says it has now identified over 50 challenges at various stages of the value chain where quantum computing could provide significant benefits four of which have now been delegated to the crowd thanks to the quantum challenge.

In other words, from a blue-sky type of endeavor, quantum computing is now solidly implanted in BMW's strategy. "We've now built two teams, one in the development department and one in the IT department," says Wick. "From this perspective, we have integrated quantum computer in our strategy."

Partnerships are central to this approach. Last June, BMW co-founded the Quantum Technology and Application Consortium (QUTAC), together with firms ranging from Bosch to Volkswagen. The objective, says Wick, is to come up with a set of problems shared across different industries, to join forces in finding solutions that can then be applied to each specific use case.

BMW is also providing a 5.1 million ($6 million) to the University of Munich to support a professorship, who will be expected to conduct research into applying quantum technologies to industry problems such as those faced by BMW.

But just because quantum computing has become part of BMW's business strategy doesn't mean that the technology is already generating value. Quantum computers are still small-scale experimental devices that are utterly incapable of running programs large enough to be useful. They are known as Noisy, Intermediate-Scale Quantum Computers (NISQ), a term of reflective of how emergent the technology remains.

"We are in the NISQ era and we will need better quantum computers," says Wick. "Personally, I think we could start having business benefits in five years. But that doesn't mean we should wait for five years, lay back, and let other companies do the work instead."

SEE:Bigger quantum computers, faster: This new idea could be the quickest route to real world apps

Preparing for large-scale quantum computers means developing partnerships with the best talent, filing patents to secure IP, but also understanding company processes very well to know how to reform them.

"You need imagination to re-think your own processes," says Wick. "I can imagine that in the next 20 years, BMW customers will sit in front of a screen and configure their own BMW in real time, for example. This is what quantum computing is for to re-think processes and setups."

The biggest challenge for now, according to Wick, is tofully understand the ever-expanding quantum ecosystem, to make sure that the right quantum algorithms are fitted with the right quantum hardware to solve the right company problem.

This is easier said than done in a field that is buzzing with activity, and where noise and reality can be hard to distinguish. Quantum computing is rapidly joining blockchain, AR, VR and others on the list of popular buzzwords, and Wick can only count on his experience as a technology scout to make sure that the company doesn't fall to the quantum hype.

In the automotive industry, BMW's competitors are getting ready for quantum computing to change business processes, too. Volkswagen, for one,was early in joining the bandwagon, and has been expanding its capabilities ever since. The pressure is on to not fall behind in the race for quantum technologies, or so it would seem and BMW is making it clear that it wants to be in the lead.

See the original post here:
Quantum computing: How BMW is getting ready for the next technology revolution - ZDNet

Recent scientific and technological breakthroughs in quantum computing hardware and software demonstrate the commercial viability of quantum computers. Specifically, Honeywell and Cambridge Quantum just announced three scientific and technical milestones that significantly move large-scale quantum computing into the commercial world

These milestones include demonstrated real-time quantum error correction (QEC), doubling the quantum volume of Honeywells System H1 to 1,024, and developing a new quantum algorithm that uses fewer qubits to solve optimization problems. Lets break each of these topical areas down into understandable bits of information.

Related: What Will it Take to Make a Successful Quantum Computing Platform? Two Things

Optical signal conditioning used on quantum computers.

Real-time quantum error correction (QEC) is used in quantum computing to protect the information from errors due to decoherence and other quantum noise. Quantum decoherence is the loss of coherence. Decoherence can be viewed as the loss of information from a system into the environment. Quantum coherence is needed to perform computing on quantum information encoded in quantum states.

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

In contrast, classical error correction employs redundancy. The simplest way to achieve redundancy is to store the information multiple times in memory and then constantly compare the information to determine if corruption has occurred.

Another difference between classical and quantum error correction is one of continuity. In classic error correction, the bit is either a 1 or a 0, i.e., it is either flipped on or off. However, errors are continuous in the quantum state. Continuous errors can occur on a qubit, in which a qubit is partially flipped, or the phase is partially changed.

Honeywell researchers have addressed quantum error correction by creating a single logical qubit from seven of the ten physical qubits available on the H1 Model and then applying multiple rounds of QEC. Protected from the main types of errors that occur in a quantum computer, the logical qubit combats errors that accumulate during computations.

Quantum Volume (QV) is the other key metric used to gauge quantum computing performance. QV is a single number meant to encapsulate the performance of quantum computers, like a classical computer's transistor count in Moores Law.

QV is a hardware-agnostic metric that IBM initially used to measure the performance of its quantum computers. This metric was needed since a classical computers transistor count and a quantum computers quantum bit count isnt the same. Qubits decohere, forgetting their assigned quantum information in less than a millisecond. For quantum computers to be commercially viable and useful, they must have a few low-error, highly connected, and scalable qubits to ensure a fault-tolerant and reliable system. That is why QV now serves as a benchmark for the progress being made by quantum computers to solve real-world problems.

According to Honeywells recent release, the System Model H1 has become the first to achieve a demonstrated quantum volume of 1024. This QV represents a doubling of its record from justfour months ago.

The third milestone comes from Cambridge Quantum Computing recently merged with Honeywell - also has developed a new quantum algorithm that uses fewer qubits to solve optimization problems.

Honeywell and Cambridge Quantum Computing (CQC) have met three key quantum milestones with the Model H1 systems.

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.

Go here to see the original:
Quantum Computing Tech is Amazing. But What Does Business Think? - DesignNews

Google's scientists now rather excitingly say that their results establish a "scalable approach" to study time crystals on current quantum processors.

In a new research paper, Google scientists claim to have used a quantum processor for a useful scientific application: to observe a genuine time crystal.

If 'time crystal' sounds pretty sci-fi that's because they are. Time crystals are no less than a new "phase of matter", as researchers put it, which has been theorized for some years now as a new state that could potentially join the ranks of solids, liquids, gases, crystals and so on. Thepaper remains in pre-print and still requires peer review.

Time crystals are also hard to find. But Google's scientists now rather excitingly say that their results establish a "scalable approach" to study time crystals on current quantum processors.

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

Understanding why time crystals are interesting requires a little bit of background in physics particularly, knowledge of the second law of thermodynamics, which states that systems naturally tend to settle in a state known as "maximum entropy".

To take an example: if you pour some milk into a coffee cup, the milk will eventually dissolve throughout the coffee, instead of sitting on the top, enabling the overall system to come to an equilibrium. This is because there are many more ways for the coffee to randomly spread throughout the coffee than there are for it to sit, in a more orderly fashion, at the top of the cup.

This irresistible drive towards thermal equilibrium, as described in the second law of thermodynamics, is reflective of the fact that all things tend to move towards less useful, random states. As time goes on, systems inevitably degenerate into chaos and disorder that is, entropy.

Time crystals, on the other hand, fail to settle in thermal equilibrium. Instead of slowly degenerating towards randomness, they get stuck in two high-energy configurations that they switch between and this back-and-forth process can go on forever.

To explain this better, Curt von Keyserlingk, lecturer at the school of physics and astronomy at the University of Birmingham, who did not participate in Google's latest experiment, pulls out some slides from an introductory talk to prospective undergraduate students. "They usually pretend to understand, so it might be useful," von Keyserlingk warns ZDNet.

It starts with a thought experiment: take a box in a closed system that is isolated from the rest of the universe, load it with a couple of dozens of coins and shake it a million times. As the coins flip, tumble and bounce off each other, they randomly move positions and increasingly become more chaotic. Upon opening the box, the expectation is that you will be faced with roughly half the coins on their heads side, and half on their tails.

It doesn't matter if the experiment started with more coins on their tails or more coins on their heads: the system forgets what the initial configuration was, and it becomes increasingly random and chaotic as it is shaken.

This closed system, when it is translated into the quantum domain, is the perfect setting to try and find time crystals, and the only one known to date. "The only stable time crystals that we've envisioned in closed systems are quantum mechanical," says von Keyserlingk.

Enter Google's quantum processor, Sycamore,which is well known for having achieved quantum supremacyand is now looking for some kind of useful application for quantum computing.

A quantum processor, by definition, is a perfect tool to replicate a quantum mechanical system. In this scenario, Google's team represented the coins in the box with qubits spinning upwards and downwards in a closed system; and instead of shaking the box, they applied a set of specific quantum operations that can change the state of the qubits, which they repeated many times.

This is where time crystals defy all expectations. Looking at the system after a certain number of operations, or shakes, reveals a configuration of qubits that is not random, but instead looks rather similar to the original set up.

"The first ingredient that makes up a time crystal is that it remembers what it was doing initially. It doesn't forget," says von Keyserlingk. "The coins-in-a-box system forgets, but a time crystal system doesn't."

It doesn't stop here. Shake the system an even number of times, and you'll get a similar configuration to the original one but shake it an odd number of times, and you'll get another set up, in which tails have been flipped to heads and vice-versa.

And no matter how many operations are carried out on the system, it will always flip-flop, going regularly back-and-forth between those two states.

Scientists call this a break in the symmetry of time which is why time crystals are called so. This is because the operation carried out to stimulate the system is always the same, and yet the response only comes every other shake.

"In the Google experiment, they do a set of operations on this chain of spins, then they do exactly the same thing again, and again. They do the same thing at the hundredth step that they do at the millionth step, if they go that far," says von Keyserlingk.

"So they subject the system to a set of conditions that have symmetry, and yet the system responds in a manner that breaks that symmetry. It's the same every two periods instead of every period. That's what makes it literally a time crystal."

SEE:Bigger quantum computers, faster: This new idea could be the quickest route to real world apps

The behavior of time crystals, from a scientific perspective, is fascinating: contrary to every other known system, they don't tend towards disorder and chaos. Unlike the coins in the box, which get all muddled up and settle at roughly half heads and half tails, they buck the entropy law by getting stuck in a special, time-crystal state.

In other words, they defy the second law of thermodynamics, which essentially defines the direction that all natural events take. Ponder that for a moment.

Such special systems are not easy to observe. Time crystals have been a topic of interest since 2012, when Nobel Prize-winning MIT professor Frank Wilczek started thinking about them; and the theory has been refuted, debated and contradicted many times since then.

Several attempts have been made to create and observe time crystals to date, with varying degrees of success. Only last month, a team from Delft University of Technology in the Netherlandspublished a pre-print showing that they had built a time crystal in a diamond processor, although a smaller system than the one claimed by Google.

The search giant's researchers used a chip with 20 qubits to serve as the time crystal many more, according to von Keyserlingk, than has been achieved until now, and than could be achieved with a classical computer.

Using a laptop, it is fairly easy to simulate around 10 qubits, explains von Keyserlingk. Add more than that, and the limits of current hardware are soon reached: every extra qubit requires exponential amounts of memory.

The scientist stops short of stating that this new experiment is a show of quantum supremacy. "They're not quite far enough for me to be able to say it's impossible to do with a classical computer, because there might be a clever way of putting it on a classical computer that I haven't thought of," says von Keyserlingk.

"But I think this is by far the most convincing experimental demonstration of a time crystal to date."

SEE: Quantum computing just took on another big challenge, one that could be as tough as steel

The scope and control of Google's experiment means that it is possible to look at time crystals for longer, do detailed sets of measurements, vary the size of the system, and so on. In other words, it is a useful demonstration that could genuinely advance science and as such, it could be key in showing the central role that quantum simulators will play in enabling discoveries in physics.

There are, of course, some caveats. Like all quantum computers, Google's processor still suffers from decoherence, which can cause a decay in the qubits' quantum states, and means that time crystals' oscillations inevitably die out as the environment interferes with the system.

The pre-print, however, argues that as the processor becomes more effectively isolated, this issue could be mitigated.

One thing is certain: time crystals won't be sitting in our living rooms any time soon, because scientists are yet to find a definitive useful application for them. It is unlikely, therefore, that Google's experiment was about exploring the business value of time crystals; rather, it shows what could potentially be another early application of quantum computing, and yet another demonstration of the company's technological prowess in a hotly contested new area of development.

The rest is here:
Google says it has created a time crystal in a quantum computer, and it's weirder than you can imagine - ZDNet

Image credits: Google Quantum AI

As the Quantum computing race is heating up, many companies across countries are spending billions on different qubit technologies to stabilise and commercialise the technology. While it is too early to declare a winner in quantum computing, Googles quantum computing lab may have created something truly remarkable.

In the latest development, researchers at Google, in collaboration with physicists at Princeton, Stanford, and other universities, have created the worlds first Time Crystal inside a quantum computer.

Get to know the amazing finalists here

Time crystals developed by Google could be the biggest scientific accomplishment for fundamental physics and quantum physics. Dreamt up by the Nobel Prize-winning physicist Frank Wilczek in 2012, the notion of time crystals is now moving from theory to reality.

In a recently published study, Observation of Time-Crystalline Eigenstate Order on a Quantum Processor, the researchers claim that Time Crystal is a new phase of matter that violates Newtons law of Thermodynamics.

Well, a time crystal sounds like a complicated component of a time machine, but it is not. So, what exactly are Time Crystals? As per researchers, a time crystal is a new phase of matter that alternates between two shapes, never losing any energy during the process.

To make it simple, regular crystals are an arrangement of molecules or atoms that form a regular repeated pattern in space. A time crystal, on the other hand, is an arrangement of molecules or atoms that form a regular, repeated pattern but in time. Meaning, theyll sit in one pattern for a while, then flip to another, and repeat back and forth.

Explaining about Time Crystal in layman terms to Silicon Canals, Loc Henriet, head of Applications and Quantum Software, Pasqal, explains, Some phases of matter are known to spontaneously break symmetries. A crystal breaks spatial translation: one finds atoms only at well-defined positions. Magnets break discrete spin symmetry: the magnetisation points to a well-defined direction. However, no known physical system was known to break one of the simplest symmetries: translation in time. Googles DTC result is the most convincing experimental evidence of the existence of non-equilibrium states of matter that break time-translation symmetry.

Further, Time crystals can withstand energy processes without entropy and transform endlessly within an isolated system without expending any fuel or energy.

Our work employs a time-reversal protocol that discriminates external decoherence from intrinsic thermalisation, and leverages quantum typicality to circumvent the exponential cost of densely sampling the eigenspectrum, says researchers. In addition, we locate the phase transition out of the DTC with experimental finite-size analysis. These results establish a scalable approach to study non-equilibrium phases of matter on current quantum processors.

For the demonstration, the researchers used a chip with 20 qubits to serve as the time crystal. Its worth mentioning that researchers performed the experiments on Googles Sycamore device, which solved a task in 200 seconds that would take a conventional computer 10,000 years.

According to the researchers, their experiment offers preliminary evidence that their system could create time crystals. This discovery could have profound implications in the world of quantum computing if its proven.

Henriet shares, This result is most interesting from a fundamental physics standpoint, as an identification of a novel quantum phase of matter. In itself, it will not directly impact our day-to-day life but it illustrates the richness of many-body quantum physics out-of-equilibrium. It also proves that quantum processors are now powerful enough to discover new interesting regimes for quantum matter with disruptive properties.

The consequence is amazing: You evade the second law of thermodynamics, says Roderich Moessner, director of the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany, and a co-author on the Google paper.

This is just this completely new and exciting space that were working in now, says Vedika Khemani, a condensed matter physicist now at Stanford who co-discovered the novel phase, while she was a graduate student and co-authored the new paper with the Google team.

In 2012, Frank Wilczek came up with the idea of time crystals while teaching a class about ordinary (spatial) crystals.

If you think about crystals in space, its very natural also to think about the classification of crystalline behaviour in time, he told Quanta.

Googles quantum computer has certainly achieved what many thought was impossible. Having said that, the experiment is in the preliminary stage and requires a lot of work. Moreover, the pre-print version of the research awaits validation from the scientists community and has to be reviewed by peers as well.

There are good reasons to think that none of those experiments completely succeeded, and a quantum computer like [Googles] would be particularly well placed to do much better than those earlier experiments, University of Oxford physicist John Chalker, who wasnt involved in the research, told Quanta.

How partnering up with Salesforce helped him succeed!

See more here:
From theory to reality: Google claims to have created physics-defying 'time crystal' inside its quantum computer - Silicon Canals