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Union Cabinet has given its approval for the National Quatum Mission.

Union ministers Anurag Thakur and Jitendra Singh announced today in a Cabinet briefing that the National Quantum Mission has received approval from the central government in an effort to encourage economic growth driven by quantum technology and elevate India to the forefront of this sector.

The mission, according to Union Minister Anurag Thakur, would continue from 2023-2024 to 2030-31 and cost a total of Rs 6,003.65 crore. He said this decision would propel India's technological advancements to unprecedented heights.

Mr Singh said that the decision to launch the National Quantum Mission is one of the most important steps taken by the government in the last nine years.

The minister said that India is the biggest user of information technology, and quantum technology is directly related to it.

This quantum technology is essentially related to information processing. This technology is better than the existing infrastructure of classic computers, which are transistor-based, as it is based on atom-based technology, which is much faster than the present technology.

It makes information processing fast, authentic, precise, and secured. He also said that the National Quantum Mission will give India a quantum jump in the technology sector.

India will be the sixth country to have a dedicated quantum mission after the US, Austria, Finland, France, and China.

Let's have a look at what is quantum computing and the advances made by India:

What is quantum computing?

According to the National Association of Software and Service Companies (NASSCOM), quantum computing is an emerging field that applies some basic principles of quantum mechanics to process information at radical speeds. A quantum computer uses quantum bits, or qubits. A qubit is made up of electrons or photons. Their spin or polarisation represents the state of the quantum, respectively.

According to the Microsoft, the quantum in "quantum computing" refers to the quantum mechanics that the system uses to calculate outputs. In physics, a quantum is the smallest possible discrete unit of any physical property. It usually refers to the properties of atomic or subatomic particles, such as electrons, neutrinos, and photons.

Quantum computers harness the unique behaviour of quantum physics-such as superposition, entanglement, and quantum interference-and apply it to computing. This introduces new concepts to traditional programming methods.

Advances India is going to make in it:

The government will set up four thematic hubs (T-Hubs) in top academic and national research and development institutes on the domains of quantum computing, quantum communication, quantum sensing and metrology, and quantum materials and devices.

The hubs will focus on the generation of new knowledge through basic and applied research and promote R&D in areas that are mandated for them.

Benefit to the country

Mr Singh said the mission can take the technology development ecosystem in the country to a globally competitive level.

The mission would greatly benefit communication, health, financial, and energy sectors, as well as drug design and space applications.

It will provide a huge boost to national priorities like Digital India, Make in India, Skill India, Stand-up India, Start-up India, Self-Reliant India, and Sustainable Development Goals (SDG), Mr Singh said.

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Quantum Computing: What It Is And Advances Made By India - NDTV

In many ways, the current spate of generative artificial intelligence (AI) services like ChatGPT can thank Nvidia (NVDA 0.95%) for their existence. Nvidia researches and designs semiconductors that accelerate computing time -- most notably GPUs (graphics processing units), originally used for high-end video game graphics and now being applied to train large-language models (LLMs) that ChatGPT runs on.

But a new breed of computing accelerator is being developed: quantum computing. Nvidia has announced software geared toward quantum computing researchers over the last few years. But does its latest hardware announcement, the DGX Quantum, propel the company into the world of designing quantum computing systems, too?

Nvidia's DGX Quantum is actually a collaboration with Israeli start-up Quantum Machines, which makes some hardware components for a quantum computing system. Specifically, DGX Quantum features a new Nvidia Grace Hopper GPU paired with an OPX+ from Quantum Machines, a "quantum control" unit that orchestrates the operations of a quantum computer.

The DGX Quantum, an Nvidia Grace Hopper GPU system paired with a Quantum Machines OPX+. Image source: Nvidia.

What does that mean? DGX Quantum isn't itself a quantum computer. Rather, it's a component in a quantum computing system, albeit an important one at this early stage of research and development for practical use of quantum computing.

According to Nvidia, a complete quantum computer requires a QPU (quantum computing processor, akin to a CPU or GPU), a system to perform operations on the QPU, a way to measure and record the resulting data, and a way to create and connect multiple QPUs that can operate with each other.

Quantum DGX is thus a means to govern the operation of this quantum computer system. And Quantum DGX will also make use of Nvidia's CUDA Quantum software stack, a hybrid platform of classical computing (CPUs and GPUs) and quantum computing (QPUs) that unifies an entire system to make it useful for researchers.

A growing number of quantum computer operators (like the National Institute of Advanced Industrial Science and Technology in Japan), quantum hardware makers IonQ, and start-up software developers (Agnostiq and QMware) have adopted CUDA Quantum in their operations.

The first deployment of the Quantum DGX hardware, the Israel Quantum Computing Center, is expected by the end of 2023.

At its most basic level, quantum computing is simply a means to further speed up computing times, enabling researchers to experiment with big problems that classical computers can't solve. Accelerated computing is Nvidia's specialty, so dabbling in quantum computing research is a natural fit for the semiconductor company.

But as its management told me in a recent conversation, widespread commercialization of quantum computing is still likely many years off. And when it does start to take root, quantum computing will supplement classical computing, not replace it -- much like Nvidia GPUs have accelerated the work traditionally handled by CPUs, not replaced them. Think of quantum computing and the QPUs that power them as another (future) extension of the classical computing work already done up to this point.

And given their industry-leading performance, Nvidia GPUs are helping propel this virtuous cycle of using the most advanced technology of today to develop the cutting edge technology of tomorrow.

Given that quantum computing is in its nascent stage, most investors who want to bet on it would be best suited by sticking to long-term ownership of stocks like Nvidia at this juncture.

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Nvidia Is a Top Stock to Bet On in Quantum Computing - The Motley Fool

Enlarge / The D-Wave hardware is, quite literally, a black box.

D-Wave

Before we had developed the first qubit, theoreticians had done the work that showed that a sufficiently powerful gate-based quantum computer would be able to perform calculations that could not realistically be done on traditional computing hardware. All that is needed is to build hardware capable of implementing the theorists' work.

The situation was essentially reversed when it came to quantum annealing. D-Wave started building hardware that could perform quantum annealing without a strong theoretical understanding of how its performance would compare to standard computing hardware. And, for practical calculations, the hardware has sometimes been outperformed by more traditional algorithms.

On Wednesday, however, a team of researchers, some at D-Wave, others at academic institutions, is releasing a paper comparing its quantum annealer with different methods of simulating its behavior. The results show that actual hardware has a clear advantage over simulations, though there are two caveats: errors start to cause the hardware to deviate from ideal performance, and it's not clear how well this performance edge translates to practical calculations.

D-Wave's hardware consists of a collection of loops of superconducting wires. Current can circulate through the loops in either direction, with the direction providing a bit value. Each loop is also connected to several of its neighbors, allowing them to influence each other's behavior.

When properly configured, the system can behave as what's called a "spin glass," a physical system with complex behavior. A spin glass is easiest to think about as a grid of magnets, with each magnet influencing the behavior of its neighbors. When one magnet is in a given orientation (like spin up), it becomes more energetically favorable for its neighbors to have the opposite orientation (spin down). If you start with a disordered systema spin glassthen the influence of each magnet on its neighbors will cause spins to flip as the system tries to find a path to the lowest energy state, called the ground state.

This process is called thermal annealing, and it has some limits. In a standard spin glass, it's possible to end up in situations where every path to the ground state goes through a high-energy barrier. This can trap the system in a local minimum instead of allowing it to evolve into the ground state.

D-Wave's system, however, shows quantum behavior. This allows it to undergo tunneling, where it passes between two low-energy states without ever occupying intervening high-energy states. So, quantum annealing is expected to have better overall performance than thermal annealing.

The behavior of spin glasses has been studied separately from D-Wave's hardware because they can be used to model a variety of physical processes. But the company's business is based on the fact that it's possible to map a variety of optimization problems onto the behavior of a spin glass. In these cases, having the spin glass find its ground state is the mathematical equivalent of finding the optimal solution to a problem.

But again, we lack the theoretical understanding of whether it's possible to get these solutions in some other way that's faster or more efficient.

To get a better sense of how its hardware performed, the research team started by validating the D-Wave hardware using a small spin glass consisting of only 16 spins. "At this scale we can numerically evolve the time-dependent Schrdinger equation," the researchers write, meaning that the behavior of the system during quantum annealing could be directly calculated. That was compared to the same process running on a small corner of one of D-Wave's Advantage processors, which have roughly 5,000 individual qubits. (They actually ran 100 of these 16-spin systems in parallel on the processor.)

These results confirmed that the D-Wave processor undergoes the expected quantum annealing process. In fact, they found that the results generated by the D-Wave processor were a better match for the Schrdinger calculations than either of two ways we can model annealing: either simulated thermal annealing, or simulated quantum annealing.

With that validation in hand, the team turned to much larger spin glasses, consisting of thousands of spins. At this point, it's no longer realistic to use Schrdinger's equations: "Simulating the Schrdinger dynamics of QA with a classical computer is an unpromising optimization method, as memory requirements grow exponentially with system size." Instead, the researchers compared D-Wave's hardware to simulated annealing and simulated quantum annealing.

Both the actual hardware and the simulators all showed a similar behavior, in that the energy gap between the system and its ground state decayed exponentially as a function of annealing time. Put differently, the system starts in a relatively high-energy state, and the energy gap between that and the ground state gets smaller as a function of time raised to a power.

The key difference between the methods is the exponentthe bigger the exponent, the faster the system approaches its ground state. Simulated quantum annealing had a higher exponent than simulated thermal annealing, while the D-Wave machine had a higher exponent than either of them. And that indicates that doing quantum annealing in D-Wave's hardware will get to a solution considerably faster than simulated annealing can.

The one problem identified in the study came when the researchers explored how the system scaled with the number of spins being tracked. For both simulations, there was a consistent relationship between annealing time and the amount of energy left in the system. By contrast, the performance of the D-Wave hardware tailed off slightly, bringing it somewhat closer to the performance of the simulated quantum annealing. This is a product of a loss of coherence in the systemin essence, errors crop up and keep the hardware from behaving as a single quantum system.

The results are still closer to optimal than the ones that are produced in this time by either of the annealing simulations. But the scaling isn't as good as it is when the system retains its coherence. And D-Wave has indicated that improving coherence is a goal for its next generation of processors.

While spin glasses are interesting to physicists, D-Wave is selling time on its systems as a way to solve optimization problems more generallyspecifically those with practical implications. But it's difficult to translate the results in this paper to these practical problems, though the team suggests that's the next step: "Extending this characterization of quantum dynamics to industry-relevant optimization problems, which generally do not enable analysis via universal critical exponents or finite-size scaling, would mark an important next step in practical quantum computing."

Put more simply, Andrew King, director of performance research at D-Wave, told Ars that "industrial problems generally don't even have a well-defined notion of scaling in the same way that these spin glasses do."

"For industrial problems, I can say that problem A has more variables than problem B, but there may be other confounding factors that make problem B harder for unexpected reasons," King said. In addition, there are some cases where highly specialized algorithms can outperform a general optimization approach, at least as long as the size of the problem remains small enough.

Despite the practical uncertainty, the empirical demonstration of a scaling advantage in quantum annealing hardware would seem to settle what had been an open question about D-Wave's hardware.

Nature, 2023. DOI: 10.1038/s41586-023-05867-2 (About DOIs).

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Quantum effects of D-Waves hardware boost its performance - Ars Technica

Evidence shows computational advantage, with quantum dynamics speedup over classical in 3D spin glasses, an intractable class of optimization problems

BURNABY, British Columbia & PALO ALTO, Calif., April 19, 2023--(BUSINESS WIRE)--D-Wave Quantum Inc. (NYSE: QBTS), a leader in quantum computing systems, software, and servicesand the only provider building both annealing and gate-model quantum computers, today published a peer-reviewed milestone paper showing the performance of its 5,000 qubit Advantage quantum computer is significantly faster than classical compute on 3D spin glass optimization problems, an intractable class of optimization problems. This paper also represents the largest programmable quantum simulation reported to date.

The paper---a collaboration between scientists from D-Wave and Boston University---entitled "Quantum critical dynamics in a 5,000-qubit programmable spin glass," was published in the peer-reviewed journal Nature today and is available here. Building upon research conducted on up to 2,000 qubits last September, the study shows that the D-Wave quantum processor can compute coherent quantum dynamics in large-scale optimization problems. This work was done using D-Waves commercial-grade annealing-based quantum computer, which is accessible for customers to use today.

With immediate implications to optimization, the findings show that coherent quantum annealing can improve solution quality faster than classical algorithms. The observed speedup matches the theory of coherent quantum annealing and shows a direct connection between coherence and the core computational power of quantum annealing.

"This research marks a significant achievement for quantum technology, as it demonstrates a computational advantage over classical approaches for an intractable class of optimization problems," said Dr. Alan Baratz, CEO of D-Wave. "For those seeking evidence of quantum annealings unrivaled performance, this work offers definitive proof."

Story continues

This work supports D-Waves ongoing commitment to relentless scientific innovation and product delivery, as the company continues development on its future annealing and gate model quantum computers. To date, D-Wave has brought to market five generations of quantum computers and launched an experimental prototype of its sixth-generation machine, the Advantage2 system, in June 2022. The full Advantage2 system is expected to feature 7,000+ qubits, 20-way connectivity and higher coherence to solve even larger and more complex problems. Read more about the research in our Medium post here.

Papers Authors and Leading Industry Voices Echo Support

"This is an important advance in the study of quantum phase transitions on quantum annealers. It heralds a revolution in experimental many-body physics and bodes well for practical applications of quantum computing," said Wojciech Zurek, theoretical physicist at Los Alamos National Laboratory and leading authority on quantum theory. Dr. Zurek is widely renowned for his groundbreaking contribution to our understanding of the early universe as well as condensed matter systems through the discovery of the celebrated Kibble-Zurek mechanism. This mechanism underpins the physics behind the experiment reported in this paper. "The same hardware that has already provided useful experimental proving ground for quantum critical dynamics can be also employed to seek low-energy states that assist in finding solutions to optimization problems."

"Disordered magnets, such as spin glasses, have long functioned as model systems for testing solvers of complex optimization problems," said Gabriel Aeppli, professor of physics at ETH Zrich and EPF Lausanne, and head of the Photon Science Division of the Paul Scherrer Institut. Professor Aeppli coauthored the first experimental paper demonstrating advantage of quantum annealing over thermal annealing in reaching ground state of disordered magnets. "This paper gives evidence that the quantum dynamics of a dedicated hardware platform are faster than for known classical algorithms to find the preferred, lowest energy state of a spin glass, and so promises to continue to fuel the further development of quantum annealers for dealing with practical problems."

"As a physicist who has built my career on computer simulations of quantum systems, it has been amazing to experience first-hand the transformative capabilities of quantum annealing devices," said Anders Sandvik, professor of physics at Boston University and a coauthor of the paper. "This paper already demonstrates complex quantum dynamics on a scale beyond any classical simulation method, and I'm very excited about the expected enhanced performance of future devices. I believe we are now entering an era when quantum annealing becomes an essential tool for research on complex systems."

"This work marks a major step towards large-scale quantum simulations of complex materials," said Hidetoshi Nishimori, Professor, Institute of Innovative Research, Tokyo Institute of Technology and one of the original inventors of quantum annealing. "We can now expect novel physical phenomena to be revealed by quantum simulations using quantum annealing, ultimately leading to the design of materials of significant societal value."

"This represents some of the most important experimental work ever performed in quantum optimization," said Dr. Andrew King, director of performance research at D-Wave. "Weve demonstrated a speedup over simulated annealing, in strong agreement with theory, providing high-quality solutions for large-scale problems. This work shows clear evidence of quantum dynamics in optimization, which we believe paves the way for even more complex problem-solving using quantum annealing in the future. The work exhibits a programmable realization of lab experiments that originally motivated quantum annealing 25 years ago."

"Not only is this the largest demonstration of quantum simulation to date, but it also provides the first experimental evidence, backed by theory, that coherent quantum dynamics can accelerate the attainment of better solutions in quantum annealing," said Mohammad Amin, fellow, quantum algorithms and systems, at D-Wave. "The observed speedup can be attributed to complex critical dynamics during quantum phase transition, which cannot be replicated by classical annealing algorithms, and the agreement between theory and experiment is remarkable. We believe these findings have significant implications for quantum optimization, with practical applications in addressing real-world problems."

About D-Wave Quantum Inc.

D-Wave is a leader in the development and delivery of quantum computing systems, software, and services, and is the worlds first commercial supplier of quantum computersand the only company building both annealing quantum computers and gate-model quantum computers. Our mission is to unlock the power of quantum computing today to benefit business and society. We do this by delivering customer value with practical quantum applications for problems as diverse as logistics, artificial intelligence, materials sciences, drug discovery, scheduling, cybersecurity, fault detection, and financial modeling. D-Waves technology is being used by some of the worlds most advanced organizations, including Volkswagen, Mastercard, Deloitte, Davidson Technologies, ArcelorMittal, Siemens Healthineers, Unisys, NEC Corporation, Pattison Food Group Ltd., DENSO, Lockheed Martin, Forschungszentrum Jlich, University of Southern California, and Los Alamos National Laboratory.

Forward-Looking Statements

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, which statements are based on beliefs and assumptions and on information currently available. In some cases, you can identify forward-looking statements by the following words: "may," "will," "could," "would," "should," "expect," "intend," "plan," "anticipate," "believe," "estimate," "predict," "project," "potential," "continue," "ongoing," or the negative of these terms or other comparable terminology, although not all forward-looking statements contain these words. These statements involve risks, uncertainties, and other factors that may cause actual results, levels of activity, performance, or achievements to be materially different from the information expressed or implied by these forward-looking statements. We caution you that these statements are based on a combination of facts and factors currently known by us and our projections of the future, which are subject to a number of risks. Forward-looking statements in this press release include, but are not limited to, statements regarding the impact of the results of this study; the companys Advantage2 experimental prototype; and the potential for future problem-solving using quantum annealing. We cannot assure you that the forward-looking statements in this press release will prove to be accurate. These forward-looking statements are subject to a number of risks and uncertainties, including, among others, various factors beyond managements control, including general economic conditions and other risks, our ability to expand our customer base and the customer adoption of our solutions, and the uncertainties and factors set forth in the sections entitled "Risk Factors" and "Cautionary Note Regarding Forward-Looking Statements" in D-Wave Quantum Inc.s Form S-4 Registration Statement, as amended, previously filed with the Securities and Exchange Commission, as well as factors associated with companies, such as D-Wave, that are engaged in the business of quantum computing, including anticipated trends, growth rates, and challenges in those businesses and in the markets in which they operate; the outcome of any legal proceedings that may be instituted against us; risks related to the performance of our business and the timing of expected business or financial milestones; unanticipated technological or project development challenges, including with respect to the cost and or timing thereof; the performance of the our products; the effects of competition on our business; the risk that we will need to raise additional capital to execute our business plan, which may not be available on acceptable terms or at all; the risk that we may never achieve or sustain profitability; the risk that we are unable to secure or protect our intellectual property; volatility in the price of our securities; and the risk that our securities will not maintain the listing on the NYSE. Furthermore, if the forward-looking statements contained in this press release prove to be inaccurate, the inaccuracy may be material. In addition, you are cautioned that past performance may not be indicative of future results. In light of the significant uncertainties in these forward-looking statements, you should not place undue reliance on these statements in making an investment decision or regard these statements as a representation or warranty by any person we will achieve our objectives and plans in any specified time frame, or at all. The forward-looking statements in this press release represent our views as of the date of this press release. We anticipate that subsequent events and developments will cause our views to change. However, while we may elect to update these forward-looking statements at some point in the future, we have no current intention of doing so except to the extent required by applicable law. You should, therefore, not rely on these forward-looking statements as representing our views as of any date subsequent to the date of this press release.

View source version on businesswire.com: https://www.businesswire.com/news/home/20230419005266/en/

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D-Wave Demonstrates First-Ever Coherent Quantum Spin Glass Dynamics on More than 5,000 Qubits - Yahoo Finance

Dr. Frederik Floether, left and Dr. Numan Laanait discuss quantum computing at the HIMSS23 Global Conference in Chicago on Wednesday.

Photo: Jeff Lagasse/Healthcare Finance News

CHICAGO Quantum computing reached a milestone in 2022 when a 400-plus qubit machine was demonstrated at a time when experts were questioning the feasibility of even a 100 qubit system. The question is no longer whether quantum computing will speed up applications in the world of healthcare it's now a matter of when.

A qubit (or quantum bit) is the basic unit of information in quantum computing. The number of qubits matters, because the more qubits, the more computing power can grow exponentially. In terms of healthcare, this has emerging possibilities in the realm of machine learning.

The quantum community has discovered problems that can't be handled with classical machine learning, but are efficiently solvable on quantum computers. That means it's only a matter of time before the technology has real-world value.

Dr. Frederik Floether, lead quantum and deputy CEO of QuantumBasel, and Numan Laanait, senior director of engineering at Elevance Health, told an audience at the HIMSS23 global conference in Chicago Wednesday that quantum computers are based on a model entirely different than that of its classical counterparts.

"It's not the difference between CPU and GPU," said Laanait. "The entire computational model is different. The part that's relevant is, in a classical computer, if you increase the number of bits bya factor of 10, the amount of information you can process increases by a factor of 10. In quantum computing, it increases by 1,000, and it increases exponentially with the number of quantum bits."

According to Floether, that's the reason why there's such excitement around the technology: Quantum is the only computational model that can be exponentially faster than classical computers.

"The journey is a continuous one," he said. "Considering that this is such a fundamentally different technology, it requires time to build those skills, build those solutions and get into a quantum state of mind."

A sign of growing maturity in the field, they said, is that major companies and smaller players alike now have road maps.Intel, Microsoft and IBM are some of the heavy hitters with quantum plans. They're planning to scale the technology.IBM in particular has hit every one of its milestonesand is projected to have a 4,000 qubit machine in the coming years.

"These machines are so complex that you cannot simulate them classically," said Laanait. "They're already past that threshold."

At this point, not every problem can be solved in a quantum manner. It's critical, said Floether, to do careful mapping between potential use cases. Current problems at which quantum computing currently excels include processing data with a complex structure, simulation and optimization.

Where quantum computing can really shine is in kernel-based machine learning. A kernel, a math function applied to data, can allow people to see more structure in their data.

"If you were to project it to an even higher function, you'd see even more structure, even more patterns in your data," said Laanait. "With quantum computers you can go to a million kernels."

The software is one thing. But that software doesn't have much value unless it has the hardware that can run it, and that's where the technology still has some catching up to do. But as the tech gets better, the data will get better.

To date, said Floether, health data is about 60%to 80% accurate in terms of data classification in classical models. The early results on quantum computing are powerful, showing the ability to outperform classical results.

"Considering the youth of the technology, this is very promising," said Floether.

Additional developments are needed to match best-in-class machine learning, said Laanait, including larger feature dimensionality and noise resiliency. But he said the healthcare industry is already on the cusp of quantum computing being the mainstay, and the industry needs to jump on the technology as soon as possible.

"Nobody can do quantum computing alone, but you have to start now," said Laanait.

Twitter: @JELagasseEmail the writer:Jeff.Lagasse@himssmedia.com

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Quantum computing poised to transform healthcare - Healthcare Finance News