Category Archives: Quantum Computing

United States and The Netherlands Sign Joint Statement of Cooperation on Quantum Information Science and Technology  Quantum Computing Report

See the rest here:
United States and The Netherlands Sign Joint Statement of Cooperation on Quantum Information Science and Technology - Quantum Computing Report

HCLTech Trends Report: Al, multi-cloud and quantum computing to drive change in 2023  CNBCTV18

Go here to read the rest:
HCLTech Trends Report: Al, multi-cloud and quantum computing to drive change in 2023 - CNBCTV18

Why IBM is no longer interested in breaking patent recordsand how it plans to measure innovation in the age of open source and quantum computing  Fortune

Read this article:
Why IBM is no longer interested in breaking patent recordsand how it plans to measure innovation in the age of open source and quantum computing -...

Quantum computers perform calculations based on the probability of an object's state before it is measured - instead of just 1s or 0s - which means they have the potential to process exponentially more data compared to classical computers.

Classical computers carry out logical operations using the definite position of a physical state. These are usually binary, meaning its operations are based on one of two positions. A single state - such as on or off, up or down, 1 or 0 - is called a bit.

In quantum computing, operations instead use the quantum state of an object to produce what's known as a qubit. These states are the undefined properties of an object before they've been detected, such as the spin of an electron or the polarisation of a photon.

Rather than having a clear position, unmeasured quantum states occur in a mixed 'superposition', not unlike a coin spinning through the air before it lands in your hand.

These superpositions can be entangled with those of other objects, meaning their final outcomes will be mathematically related even if we don't know yet what they are.

The complex mathematics behind these unsettled states of entangled 'spinning coins' can be plugged into special algorithms to make short work of problems that would take a classical computer a long time to work out if they could ever calculate them at all.

Such algorithms would be useful in solving complex mathematical problems, producing hard-to-break security codes, or predicting multiple particle interactions in chemical reactions.

Building a functional quantum computer requires holding an object in a superposition state long enough to carry out various processes on them.

Unfortunately, once a superposition meets with materials that are part of a measured system, it loses its in-between state in what's known as decoherence and becomes a boring old classical bit.

Devices need to be able to shield quantum states from decoherence, while still making them easy to read.

Different processes are tackling this challenge from different angles, whether it's to use more robust quantum processes or to find better ways to check for errors.

For the time being, classical technology can manage any task thrown at a quantum computer. Quantum supremacy describes the ability of a quantum computer to outperform their classical counterparts.

Some companies, such as IBM and Google, claim we might be close, as they continue to cram more qubits together and build more accurate devices.

Not everybody is convinced that quantum computers are worth the effort. Some mathematicians believe there are obstacles that are practically impossible to overcome, putting quantum computing forever out of reach.

Time will tell who is right.

All topic-based articles are determined by fact checkers to be correct and relevant at the time of publishing. Text and images may be altered, removed, or added to as an editorial decision to keep information current.

Here is the original post:
How Do Quantum Computers Work? : ScienceAlert

Slowly but surely, quantum computing is getting ready for its closeup.

Google made headlines in October 2019 upon proclaiming that it had achieved the long-anticipated breakthrough of quantum supremacy. Thats when a quantum computer is able to perform a task a conventional computer cant. Not in a practical amount of time, anyway. For instance, Google claimed the test problem it ran would have taken a classical computer thousands of years to complete though some critics and competitors called that a gross exaggeration.

IBM, for one, wasnt having it. The other big player in quantum, it promptly posted a response essentially arguing that Google had underestimated the muscle of IBM supercomputers which, though blazingly fast, arent of the quantum variety.

Tech giant head-butting aside, Googles achievement was a genuine milestone one that further established quantum computing in the broader consciousness and prompted more people to wonder: What will these things actually do?

But even once quantum computing reigns supreme, its potential impact remains largely theoretical. But thats more a reflection of quantum computings still-fledgling status than unfulfilled promise.

Before commercial-scale quantum computing is a thing, however, researchers must clear some major hurdles. Chief among them is upping the number of qubits, units of information that these impressive pieces of hardware use to perform tasks. Whereas classical computer bits exist as 1s or 0s, qubits can be either or both simultaneously. Thats key to massively greater processing speeds, which are necessary to simulate molecular-level quantum mechanics.

Despite quantums still-hypothetical nature and the long road ahead, predictions and investment abound. Google CEO Sundar Pichai likened his companys recent proof-of-concept advancement to the Wright brothers 12-second flight: Though very basic and short-lived, it demonstrated whats possible. And whats possible, experts say, is impressive indeed.

From cybersecurity to pharmaceutical research to finance, here are some ways quantum computing facilitates major advancements.

More on Quantum Computing5 Skills You Need to Launch a Quantum Computing Career

Location: Armonk, New York

Quantum computing and artificial intelligence may prove to be mutual back-scratchers. As VentureBeat explained, advances in deep learning will likely increase our understanding of quantum mechanics while at the same time fully realized quantum computers could far surpass conventional ones in data pattern recognition. Regarding the latter, IBMs quantum research team has found that entangling qubits on the quantum computer that ran a data-classification experiment cut the error rate in half compared to unentangled qubits.

What this suggests, an essay in the MIT Technology Review noted, is that as quantum computers get better at harnessing qubits and at entangling them, theyll also get better at tackling machine-learning problems.

IBMs research came in the wake of another promising machine-learning classification algorithm: a quantum-classical hybrid run on a 19-qubit machine built by Rigetti Computing.

Harnessing [quantum computers statistical distribution] has the potential to accelerate or otherwise improve machine learning relative to purely classical performance, Rigetti researchers wrote. The hybridization of classical compute and quantum processors overcame a key challenge in realizing that aim, they explained.

Both are important steps toward the ultimate goal of significantly accelerating AI through quantum computing. Which might mean virtual assistants that understand you the first time. Or non-player-controlled video game characters that behave hyper-realistically. The potential advancements are numerous.

I think AI can accelerate quantum computing," Googles Pichai said, "and quantum computing can accelerate AI.

Location: New York, New York

The list of partners that comprise Microsofts so-called Quantum Network includes a slew of research universities and quantum-focused technical outfits, but precious few business affiliates. However, two of the five NatWest and Willis Towers Watson are banking interests. Similarly, at IBMs Q Network, JPMorgan Chase stands out amid a sea of tech-focused members as well as government and higher-ed research institutions.

That hugely profitable financial services companies would want to leverage paradigm-shifting technology is hardly a shocker, but quantum and financial modeling are a truly natural match thanks to structural similarities. As a group of European researchers wrote last year, [T]he entire financial market can be modeled as a quantum process, where quantities that are important to finance, such as the covariance matrix, emerge naturally.

A lot of recent research has focused specifically on quantums potential to dramatically speed up the so-called Monte Carlo model, which essentially gauges the probability of various outcomes and their corresponding risks. A 2019 paper co-written by IBM researchers and members of JPMorgans Quantitative Research team included a methodology to price option contracts using a quantum computer.

Its seemingly clear risk-assessment application aside, quantum in finance could have a broad future. If we had [a commercial quantum computer] today, what would we do?Nikitas Stamatopoulos, a co-author of the price-options paper, wondered. The answer today is not very clear.

Location: Redmond, Washington

The world has a fertilizer problem that extends beyond an overabundance of poop. Much of the planets fertilizer is made by heating and pressurizing atmospheric nitrogen into ammonia, a process pioneered in the early 1900s by German chemist Fritz Haber.

The so-called Haber process, though revolutionary, proved quite energy-consuming: some three percent of annual global energy output goes into running Haber, which accounts for more than one percent of greenhouse gas emissions. More maddening, some bacteria perform that process naturally we simply have no idea how and therefore cant leverage it.

With an adequate quantum computer, however, we could probably figure out how and, in doing so, significantly conserve energy. In 2017, researchers from Microsoft isolated the cofactor molecule thats necessary to simulate. And theyll do that just as soon as the quantum hardware has a sufficient qubit count and noise stabilization. Googles CEO told MIT he thinks the quantum improvement of Haber is roughly a decade away.

Related ReadingQuantum Computing Movies: How Realistic Are They?

Location: Berkeley, California

Recent research into whether quantum computing might vastly improve weather prediction has determined its a topic worth researching! And while we still have little understanding of that relationship, many in the field view it as a notable use case.

Ray Johnson, the former CTO at Lockheed Martin and now an independent director at quantum startup Rigetti Computing, is among those whove indicated that quantum computings method of simultaneous (rather than sequential) calculation will likely be successful in analyzing the very, very complex system of variables that is weather.

While we currently use some of the worlds most powerful supercomputers to model high-resolution weather forecasts, accurate numerical weather prediction is notoriously difficult. In fact, it probably hasnt been that long since you cursed an off-the-mark meteorologist.

Location: London, England

To presidential candidate Andrew Yang, Googles quantum milestone meant that no code is uncrackable. He was referring to a much-discussed notion that the unprecedented factorization power of quantum computers would severely undermine common internet encryption systems.

But Googles device (like all current QC devices) is far too error-prone to pose the immediate cybersecurity threat that Yang implied. In fact, according to theoretical computer scientist Scott Aaronson, such a machine wont exist for quite a while. But the looming danger is serious. And the years-long push toward quantum-resistant algorithms like the National Institute of Standards and Technologys ongoing competition to build such models illustrates how seriously the security community takes the threat.

One of just 26 so-called post-quantum algorithms to make the NISTs semifinals comes from, appropriately enough, British-based cybersecurity leader Post-Quantum. Experts say the careful and deliberate process exemplified by the NISTs project is precisely what quantum-focused security needs. As Dr. Deborah Franke of the National Security Agency told Nextgov, There are two ways you could make a mistake with quantum-resistant encryption: One is you could jump to the algorithm too soon, and the other is you jump to the algorithm too late.

Location: Toronto, Ontario

The real excitement about quantum is that the universe fundamentally works in a quantum way, so you will be able to understand nature better, Googles Pichai told MIT Technology Review in the wake of his companys recent announcement. Its early days, but where quantum mechanics shines is the ability to simulate molecules, molecular processes, and I think that is where it will be the strongest. Drug discovery is a great example.

One company focusing computational heft on molecular simulation, specifically protein behavior, is Toronto-based biotech startup ProteinQure. Flush with $4 million in recent seed funding as of 2019, it partners with quantum-computing leaders (IBM, Microsoft and Rigetti Computing) and pharma research outfits (SRI International, AstraZeneca) to explore QCs potential in modeling protein.

Thats the deeply complex but high-yield route of drug development in which proteins are engineered for targeted medical purposes. Although its vastly more precise than the old-school trial-and-error method of running chemical experiments, its infinitely more challenging from a computational standpoint. As Boston Consulting Group noted, merely modeling a penicillin molecule would require an impossibly large classical computer with 10-to-the-86th-power bits. For advanced quantum computers, though, that same process could be a snap and could lead to the discovery of new drugs for serious maladies like cancer, Alzheimers and heart disease.

Cambridge, Mass.-based Biogen is another notable company exploring quantum computings capacity for drug development. Focused on neurological disease research, the biotech firm announced a 2017 partnership with quantum startup 1QBit and Accenture.

Location: Stuttgart, Germany

QCs potential to simulate quantum mechanics could be equally transformative in other chemistry-related realms beyond drug development. The auto industry, for example, wants to harness the technology to build better car batteries.

In 2018, German car manufacturer Daimler AG (the parent company of Mercedes-Benz) announced two distinct partnerships with quantum-computing powerhouses Google and IBM. Electric vehicles are mainly based on a well-functioning cell chemistry of the batteries, the company wrote in its magazine at the time. Quantum computing, it added, inspires justified hope for initial results in areas like cellular simulation and the aging of battery cells. Improved batteries for electric vehicles could help increase adoption of those vehicles.

Daimler is also looking into how QC could potentially supercharge AI, plus manage an autonomous-vehicle-choked traffic future and accelerate its logistics. It follows in the footsteps of another major Teutonic transportation brand: Volkswagen. In 2017, the automaker announced a partnership with Google focused on similar initiatives. It also teamed up with D-Wave Systems in 2018.

Location: Wolfsburg, Germany

Volkswagens exploration of optimization brings up a point worth emphasizing: Despite some common framing, the main breakthrough of quantum computing isnt just the speed at which it will solve challenges, but the kinds of challenges it will solve.

The traveling salesman problem, for instance, is one of the most famous in computation. It aims to determine the shortest possible route between multiple cities, hitting each city once and returning to the starting point. Known as an optimization problem, its incredibly difficult for a classical computer to tackle. For fully realized QCs, though, it could be much easier.

D-Wave and VW have already run pilot programs on a number of traffic- and travel-related optimization challenges, including streamlining traffic flows in Beijing, Barcelona and Lisbon. For the latter, a fleet of buses traveled along distinct routes that were tailored to real-time traffic conditions through a quantum algorithm, which VW continues to tweak after each trial run. According to D-Wave CEO Vern Brownell, the companys pilot brings us closer than ever to realizing true, practical quantum computing.

Location: College Park, Maryland

In the search for sustainable energy alternatives, hydrogen fuel, when produced without the use of fossil fuels, is serving to be a viable solution for reducing harmful greenhouse gas emissions. Most hydrogen fuel production is currently rooted in fossil fuel use, though quantum computing could create an efficient avenue to turn this around.

Electrolysis, the process of deconstructing water into basal hydrogen and oxygen molecules, can work to extract hydrogen for fuel in an environmentally-friendly manner. Quantum computing has already been helping research how to utilize electrolysis for the most efficient and sustainable hydrogen production possible.

As of 2019, IonQ performed the first simulation of a water molecule on a quantum device, marking as evidence that computing is able to approach accurate chemical predictions. As of 2022, IonQ released Forte, its newest generation of quantum systems allowing software-configurability and greater flexibility for researchers and other users. Theres hopes that the power of quantum computing can further climate change solution research on a large and accelerated scale.

Location: Boulder, Colorado

Quantum computing has become a hot topic amongst the tech industry, though one particular company is keeping it cool. ColdQuanta is known for its use of cold atom quantum computing, in which laser-cooled atoms can act the role as qubits. With this method, fragile atoms can be kept cold while the operating system remains at room temperature, allowing quantum devices to be used in various environments.

To aid in research conducted by NASAs Cold Atom Laboratory, ColdQuantas Quantum Core technology was successfully shipped to the International Space Station in 2019. The technology has since been expected to be used to support communications, global positioning, and signal processing applications. ColdQuanta has also been signed in multi-million dollar contracts by U.S. government agencies to develop quantum atomic clock and ion trap system technologies as of 2021.

Go here to read the rest:
10 Quantum Computing Applications & Examples to Know | Built In

Accelerating advances in quantum computingare serving as powerful reminders that the technology is rapidly advancing toward commercial viability. In just the past few months, for example, a research center in Japan announced a breakthrough in entangling qubits (the basic unit of information in quantum, akin to bits in conventional computers) that could improve error correction in quantum systems and potentially make large-scale quantum computers possible. And one company in Australia has developed software that has shown in experiments to improve the performance of any quantum-computing hardware.

As breakthroughs accelerate, investment dollars are pouring in, and quantum-computing start-ups are proliferating. Major technology companies continue to develop their quantum capabilities as well: companies such as Alibaba, Amazon, IBM, Google, and Microsoft have already launched commercial quantum-computing cloud services.

Of course, all this activity does not necessarily translate into commercial results. While quantum computing promises to help businesses solve problems that are beyond the reach and speed of conventional high-performance computers, use cases are largely experimental and hypothetical at this early stage. Indeed, experts are still debating the most foundational topics for the field (for more on these open questions, see sidebar, Debates in quantum computing).

Still, the activity suggests that chief information officers and other leaders who have been keeping an eye out for quantum-computing news can no longer be mere bystanders. Leaders should start to formulate their quantum-computing strategies, especially in industries, such as pharmaceuticals, that may reap the early benefits of commercial quantum computing. Change may come as early as 2030, as several companies predict they will launch usable quantum systems by that time.

To help leaders start planning, we conducted extensive research and interviewed 47 experts around the globe about quantum hardware, software, and applications; the emerging quantum-computing ecosystem; possible business use cases; and the most important drivers of the quantum-computing market. In the report Quantum computing: An emerging ecosystem and industry use cases, we discuss the evolution of the quantum-computing industry and dive into the technologys possible commercial uses in pharmaceuticals, chemicals, automotive, and financefields that may derive significant value from quantum computing in the near term. We then outline a path forward and how industry decision makers can start their efforts in quantum computing.

An ecosystem that can sustain a quantum-computing industry has begun to unfold. Our research indicates that the value at stake for quantum-computing players is nearly $80 billion (not to be confused with the value that quantum-computing use cases could generate).

Because quantum computing is still a young field, the majority of funding for basic research in the area still comes from public sources (Exhibit 1).

Exhibit 1

However, private funding is increasing rapidly. In 2021 alone, announced investments in quantum-computing start-ups have surpassed $1.7 billion, more than double the amount raised in 2020 (Exhibit 2). We expect private funding to continue increasing significantly as quantum-computing commercialization gains traction.

Exhibit 2

Hardware is a significant bottleneck in the ecosystem. The challenge is both technical and structural. First, there is the matter of scaling the number of qubits in a quantum computer while achieving a sufficient level of qubit quality. Hardware also has a high barrier to entry because it requires a rare combination of capital, experience in experimental and theoretical quantum physics, and deep knowledgeespecially domain knowledge of the relevant options for implementation.

Multiple quantum-computing hardware platforms are under development. The most important milestone will be the achievement of fully error-corrected, fault-tolerant quantum computing, without which a quantum computer cannot provide exact, mathematically accurate results (Exhibit 3).

Exhibit 3

Experts disagree on whether quantum computers can create significant business value before they are fully fault tolerant. However, many say that imperfect fault tolerance does not necessarily make quantum-computing systems unusable.

When might we reach fault tolerance? Most hardware players are hesitant to reveal their development road maps, but a few have publicly shared their plans. Five manufacturers have announced plans to have fault-tolerant quantum-computing hardware by 2030. If this timeline holds, the industry will likely establish a clear quantum advantage for many use cases by then.

The number of software-focused start-ups is increasing faster than any other segment of the quantum-computing value chain. In software, industry participants currently offer customized services and aim to develop turnkey services when the industry is more mature. As quantum-computing software continues to develop, organizations will be able to upgrade their software tools and eventually use fully quantum tools. In the meantime, quantum computing requires a new programming paradigmand software stack. To build communities of developers around their offerings, the larger industry participants often provide their software-development kits free of charge.

In the end, cloud-based quantum-computing services may become the most valuable part of the ecosystem and can create outsize rewards to those who control them. Most providers of cloud-computing services now offer access to quantum computers on their platforms, which allows potential users to experiment with the technology. Since personal or mobile quantum computing is unlikely this decade, the cloud may be the main way for early users to experience the technology until the larger ecosystem matures.

Most known use cases fit into four archetypes: quantum simulation, quantum linear algebra for AI and machine learning, quantum optimization and search, and quantum factorization. We describe these fully in the report, as well as outline questions leaders should consider as they evaluate potential use cases.

We focus on potential use cases in a few industries that research suggests could reap the greatest short-term benefits from the technology: pharmaceuticals, chemicals, automotive, and finance. Collectively (and conservatively), the value at stake for these industries could be between roughly $300 billion and $700 billion (Exhibit 4).

Exhibit 4

Quantum computing has the potential to revolutionize the research and development of molecular structures in the biopharmaceuticals industry as well as provide value in production and further down the value chain. In R&D, for example, new drugs take an average of $2 billion and more than ten years to reach the market after discovery. Quantum computing could make R&D dramatically faster and more targeted and precise by making target identification, drug design, and toxicity testing less dependent on trial and error and therefore more efficient. A faster R&D timeline could get products to the right patients more quickly and more efficientlyin short, it would improve more patients quality of life. Production, logistics, and supply chain could also benefit from quantum computing. While it is difficult to estimate how much revenue or patient impact such advances could create, in a $1.5 trillion industry with average margins in earnings before interest and taxes (EBIT) of 16 percent (by our calculations), even a 1 to 5 percent revenue increase would result in $15 billion to $75 billion of additional revenues and $2 billion to $12 billion in EBIT.

Quantum computing can improve R&D, production, and supply-chain optimization in chemicals. Consider that quantum computing can be used in production to improve catalyst designs. New and improved catalysts, for example, could enable energy savings on existing production processesa single catalyst can produce up to 15 percent in efficiency gainsand innovative catalysts may enable the replacement of petrochemicals by more sustainable feedstock or the breakdown of carbon for CO2 usage. In the context of the chemicals industry, which spends $800 billion on production every year (half of which relies on catalysis), a realistic 5 to 10 percent efficiency gain would mean a gain of $20 billion to $40 billion in value.

The automotive industry can benefit from quantum computing in its R&D, product design, supply-chain management, production, and mobility and traffic management. The technology could, for example, be applied to decrease manufacturing processrelated costs and shorten cycle times by optimizing elements such as path planning in complex multirobot processes (the path a robot follows to complete a task) including welding, gluing, and painting. Even a 2 to 5 percent productivity gainin the context of an industry that spends $500 billion per year on manufacturing costswould create $10 billion to $25 billion of value per year.

Finally, quantum-computing use cases in finance are a bit further in the future, and the advantages of possible short-term uses are speculative. However, we believe that the most promising use cases of quantum computing in finance are in portfolio and risk management. For example, efficiently quantum-optimized loan portfolios that focus on collateral could allow lenders to improve their offerings, possibly lowering interest rates and freeing up capital. It is earlyand complicatedto estimate the value potential of quantum computingenhanced collateral management, but as of 2021, the global lending market stands at $6.9 trillion, which suggests significant potential impact from quantum optimization.

In the meantime, business leaders in every sector should prepare for the maturation of quantum computing.

Until about 2030, we believe that quantum-computing use cases will have a hybrid operating model that is a cross between quantum and conventional high-performance computing. For example, conventional high-performance computers may benefit from quantum-inspired algorithms.

Beyond 2030, intense ongoing research by private companies and public institutions will remain vital to improve quantum hardware and enable moreand more complexuse cases. Six key factorsfunding, accessibility, standardization, industry consortia, talent, and digital infrastructurewill determine the technologys path to commercialization.

Leaders outside the quantum-computing industry can take five concrete steps to prepare for the maturation of quantum computing:

Leaders in every industry have an uncommon opportunity to stay alert to a generation-defining technology. Strategic insights and soaring business value could be the prize.

Visit link:
Quantum computing use cases--what you need to know | McKinsey