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Baidu is the latest entrant in the quantum computing race, which has been ongoing for years among both big tech and startups. Nevertheless, quantum computing may face a trough of disillusionment as practical applications remain far from reality.

Last week, Baidu unveiled its first quantum computer, coined Qian Shi, as well as what it claimed is the worlds first all-platform integration solution, called Liang Xi. The quantum computer is based on superconducting qubits, which is one of the first types of qubits, among many techniques that have been investigated, that became widely adopted, most notably in the quantum computer which Google used to proclaim quantum supremacy.

Qian Shi has a computing power of 10 high-fidelity qubits. High fidelity refers to low error rates. According to the Department of Energys Office of Science, once the error rate is less than a certain threshold i.e., about 1% quantum error correction can, in theory, reduce it even further. Beating this threshold is a milestone for any qubit technology, according to the DOEs report.

Further, Baidu said it has also completed the design of a 36-qubit chip with couplers, which offers a way to reduce errors. Baidu said its quantum computer integrates both hardware, software and applications. The software-hardware integration allows access to quantum chips via mobile, PC and the cloud.

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Moreover, Liang Xi, Baidu claims, can be plugged into both its own and third-party quantum computers. This may include quantum chips built on other technologies, with Baidu giving a trapped ion device developed by the Chinese Academy of Sciences as an example.

With Qian Shi and Liang Xi, users can create quantum algorithms and use quantum computing power without developing their own quantum hardware, control systems or programming languages, said Runyao Duan, director of the Institute for Quantum Computing at Baidu Research. Baidus innovations make it possible to access quantum computing anytime and anywhere, even via smartphone. Baidus platform is also instantly compatible with a wide range of quantum chips.

Despite Baidus claim of being the worlds first such solution, the Liang Xi platform is reminiscent of Israels Innovation Authority approach, which is also aimed at being compatible with various types of qubits.

Although this is Baidus first quantum computer, the company has already submitted over 200 patents throughout the last four years since the founding of its quantum computing research institute. The patents span various areas of research including quantum algorithms and applications, communications and networks, encryption and security, error correction, architecture, measurement and control and chip design.

Baidu claims its offering paves the way for the industrialization of quantum computing, making it the latest company to make grandiose claims about quantum computing being on the verge of widespread adoption. Some quantum startups have already amassed staggering valuations of over $1 billion.

However, real applications for quantum computers, besides encryption, have yet to emerge. And even if they do, its expected that those will require thousands, which is far from what has anyone yet been able to achieve. For example, this scalability concern led Intel to stop pursuing the popular superconducting qubit approach in favor of the less mature silicon and silicon-germanium qubits, which are based on transistor-like structures that can be manufactured using traditional semiconductor equipment.

Nevertheless, voices are already emerging to warn of overhyping the technology. In the words of the Gartner Hype Cycle, this may mean that quantum computing may approach its trough of disillusionment.

The other main challenge in quantum computing is that real qubits tend to be too noisy, leading to decoherence This leads to the necessity of using quantum error correction, which increases the number of qubits far above the theoretical minimum for a given application. A solution called noisy intermediate scale quantum (NISQ) has been proposed as a sort of midway, but its success has yet to be shown.

The history of classical computers is filled with examples of applications that the technology enabled that had never been thought of beforehand. This makes it tempting to think that quantum computing may similarly revolutionize civilization. However, most approaches for qubits currently rely on near-absolute zero temperature. This inherent barrier implies quantum computing may remain limited to enterprises.

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How reality gets in the way of quantum computing hype - VentureBeat

It is perhaps not surprising that the big cloud providers a poor term really have jumped into quantum computing. Amazon, Microsoft Azure, Google, and their like have steadily transformed into major technology developers, no doubt in service of their large cloud services offerings. The same is true internationally. You may not know, for example, that Chinas cloud giants Baidu, Alibaba, and Tencent also all have significant quantum development initiatives.

The global cloud crowd tends to leave no technology stone unturned and quantum was no different. Now the big players are all-in. At Amazon, most of the public attention has centered on Braket, its managed quantum services offering that provides tools for learning and access to a variety of quantum computers. Less well-known are Amazons Quantum Solutions Lab, Center for Quantum Computing, and Center for Quantum Networking, the last just launched in June. These four initiatives capture the scope of AWSs wide-ranging quantum ambitions, which include building a fault-tolerant quantum computer.

HPCwire recently talked with Simone Severini, director, quantum computing, AWS, about its efforts. A quantum physicist by training, Severini has been with AWS for ~ four years. He reports to AWSs overall engineering chief, Bill Vass. Noting that theres not much evidence that NISQ era systems will provide decisive business value soon, Severini emphasized quantum computing is a long-term bet. Now is the time for watching, learning, and kicking the tires on early systems.

Amazon Braket provides a huge opportunity for doing that. Customers can keep an eye on the dynamics of the evolution of this technology. We believe theres really not a single path to quantum computing. Its very, very early, right. This is a point that I like to stress, said Severini. I come from academia and have been exposed to quantum computing, one way or another, for over two decades. Its amazing to see the interest in the space. But we also need to be willing to set the right expectations. Its definitely very, very early still in quantum computing.

Launched in 2019, AWS describes Braket as a fully managed quantum computing service designed to help speed up scientific research and software development for quantum computing. This is not unlike what most big quantum computer makers, such D-Wave, IBM and Rigetti also provide.

The premise is to provide all the quantum tools and hardware infrastructure required for new and more experienced quantum explorers to use on a pay-as-you-go basis. Indeed, in the NISQ era, many believe such portal offerings are the only realistic way to deliver quantum computing. Cloud providers (and other concierge-like service providers such Strangeworks, for example) have the advantage of being able to provide access to several different systems.

With Braket, said Severini, Users dont have to sign contracts. Just go there, and you have everything you need to see whats going on [in quantum computing], to program or to simulate, and to use quantum computers directly. We have multiple devices with different [qubit] technologies on the service. The hope is that on one side, customers can indeed keep an eye on the technology on the other side, researchers can run experiments and hopefully contribute to knowledge as well contribute to science.

Braket currently offers access to quantum computers based on superconducting, trapped ion, photonic, and quantum annealers. Presumably other qubit technologies, cold atoms for example, will be added over time.

Interestingly, Braket is also a learning tool for AWS. Its an important exercise for us as well, because in this way, we can envision how quantum computers one day, would really feed a complex, cloud based infrastructure. Today, the workloads on Braket are all experimental, but for us, its important to learn things like security or operator usability, and the management of resources that we do for customers, said Severini. This is quite interesting, because in the fullness of time, a quantum computer could be used together with a lot of other classical resources, including HPC.

On the latter point, there is growing belief that much of quantum computing may indeed become a hybrid effort with some pieces of applications best run on quantum computers and other parts best run on classical resources. Well see. While it is still early days for the pursuit of hybrid classical-quantum computing, AWS launched Amazon Braket Hybrid late year. Heres an excerpt of AWSs description:

Amazon Braket Hybrid Jobs enables you to easily run hybrid quantum-classical algorithms such as the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA), that combine classical compute resources with quantum computing devices to optimize the performance of todays quantum systems. With this new feature, you only have to provide your algorithm script and choose a target device a quantum processing unit (QPU) or quantum circuit simulator. Amazon Braket Hybrid Jobs is designed to spin up the requested classical resources when your target quantum device is available, run your algorithm, and release the instances after completion so you only pay for what you use. Braket Hybrid Jobs can provide live insights into algorithm metrics to monitor your algorithm as it progresses, enabling you to make adjustments more quickly. Most importantly, your jobs have priority access to the selected QPU for the duration of your experiment, putting you in control, and helping to provide faster and more predictable execution.

To run a job with Braket Hybrid Jobs, you need to first define your algorithm using either the Amazon Braket SDK orPennyLane. You can also use TensorFlow and PyTorch or create a custom Docker container image. Next, you create a job via the Amazon Braket API or console, where you provide your algorithm script (or custom container), select your target quantum device, and choose from a variety of optional settings including the choice of classical resources, hyper-parameter values, and data locations. If your target device is a simulator, Braket Hybrid Jobs is designed to start executing right away. If your target device is a QPU, your job will run when the device is available and your job is first in the queue. You can define custom metrics as part of your algorithm, which can be automatically reported to Amazon CloudWatch and displayed in real time in the Amazon Braket console. Upon completion, Braket Hybrid Jobs writes your results to Amazon S3 and releases your resources.

The second initiative, Amazon Quantum Solution Lab, is aimed at collaborative research programs; it is, in essence, Amazons professional quantum services group.

They engage in research project with customers. For example, they recently wrote a paper with a team of researchers at Goldman Sachs. They run a very interesting initiative together with BMW Group, something called the BMW Group quantum computing challenge. BMW proposed four areas related to their interests, like logistic, manufacturing, some stuff that related to automotive engineering, and there was a call for a proposal to crowdsource solutions that use quantum computers to address these problems, said Severini.

There were 70 teams, globally, that submitted solutions. I think this is very interesting because [its still early days] and the fact is that quantum computers are not useful in business problems today. They cant [yet] be more impactful than classical computing today. An initiative of this type can really help bridge the real world with the theory. We have several such initiatives, he said.

Building a Fault-Tolerant Computer

Amazons efforts to build a fault-tolerant quantum are based at the AWS Center for Quantum Computing, located in Pasadena, Calif., and run in conjunction with Caltech. We launched this initiative in 2019 but last year, in 2021, we opened a building that we built inside the campus of Caltech, said Severini. Its a state of the art research facility and we are doing research to build an error-corrected, fault tolerant computer, he said.

AWS has settled on semiconductor-based superconducting qubit technology, citing the deep industry knowledge of semiconductor manufacturing techniques and scalability. The challenge, of course, is achieving fault-tolerance. Todays NISQ systems are noisy and error-prone and require near-zero Kelvin temperatures. Severini said simply, There is a lot of scientific challenges still and theres a lot of engineering to be done.

We believe strongly that there are two things that need to be done at this stage. One is improving error rates at the physical level and to invest in material science to really understand on a fundamental level how to build components that have an improvement in with respect to error rates. The second point is [to develop] new qubit architectures for protecting qubits from errors, he said.

This facility includes everything [to do] that. We are doing the full stack. Were building everything ourselves from software to the architecture to the qubits, and the wiring. These are long-term investments, said Severini.

AWS has been relatively quiet in promoting its quantum computer building effort. It has vigorously embraced competing qubit technologies on Braket, and Severini noted that its still unclear how progress will unfold. Some approaches may work well for a particular application but not for others. AWS is tracking all of them, and is including some prominent quantum researchers. For example, John Preskill, the Caltech researcher who coined the term NISQ, is an Amazon Scholar. (Preskill, of course, is fittingly the Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology.)

Last February, AWS published a paper in PRX Quantum (Building a fault-tolerant quantum computer using concatenated cat codes) which outlines directional thinking. The abstract is excerpted below:

We present a comprehensive architectural analysis for a proposed fault-tolerant quantum computer based on cat codes concatenated with outer quantum error-correcting codes. For the physical hardware, we propose a system of acoustic resonators coupled to superconducting circuits with a two-dimensional layout. Using estimated physical parameters for the hardware, we perform a detailed error analysis of measurements and gates, includingcnotand Toffoli gates. Having built a realistic noise model, we numerically simulate quantum error correction when the outer code is either a repetition code or a thin rectangular surface code.

Our next step toward universal fault-tolerant quantum computation is a protocol for fault-tolerant Toffoli magic state preparation that significantly improves upon the fidelity of physical Toffoli gates at very low qubit cost. To achieve even lower overheads, we devise a new magic state distillation protocol for Toffoli states. Combining these results together, we obtain realistic full-resource estimates of the physical error rates and overheads needed to run useful fault-tolerant quantum algorithms. We find that with around 1000 superconducting circuit components, one could construct a fault-tolerant quantum computer that can run circuits, which are currently intractable for classical computers. Hardware with 18000 superconducting circuit components, in turn, could simulate the Hubbard model in a regime beyond the reach of classical computing.

The latest big piece of Amazons quantum puzzle is the AWS Center for Quantum Networking, located in Boston. AWS says major news about the new center is forthcoming soon. The quantum networking center, said Severini, is focused on hardware, software, commercial and scientific applications. That sounds like a lot and is perhaps in keeping with Amazons ambitious quantum programs overall.

The proof of all these efforts, as the saying goes, will be in the pudding.

Stay tuned.

Feature Image:A microwave package encloses the AWS quantum processor. The packaging is designed to shield the qubits from environmental noise while enabling communication with the quantum computers control systems. Source: AWS

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AWS Takes the Short and Long View of Quantum Computing - HPCwire

By Yuval Boger

When companies recognize that quantum computing has the potential to dramatically transform their business, they often seek to hire quantum information science PhDs to staff their quantum activities. The thought is that such PhDs are quantum experts and are equipped with knowledge and experience that can help accelerate a companys quantum program. But would hiring many such PhDs be a realistic approach? What might be good alternatives?

One challenge with hiring quantum PhDs is that there are not enough of them. McKinseys June 22 Quantum Technology Monitor reports that there were 851 active quantum computing job postings in Dec 21, yet annually only 290 quantum technology graduates are available to fill these positions without requiring significant training. The same report notes that only 12 universities in the US (and a total of 29 universities worldwide) offer a quantum technology masters degree, so its unlikely that the number of graduates will increase as quickly as the need for their services.

But thats not the only concern. Companies build quantum teams to explore quantum solutions to their specific challenges option pricing, chemical simulation, supply chain optimization, etc. How quickly would these quantum graduates pick up the intricacies of the business? Even if such a graduate became well-versed in high-end finance, for example, they might not have the personal relationships and interpersonal skills to navigate company politics and build organizational support for their efforts. They also often lack relationships with peers in the industry and thus might be limited in their ability to leverage lessons learned in other organizations.

An alternative could be up-skilling, providing quantum training to in-house scientists and engineers that already understand the business and are well-connected in the organization as well as in their respective industries. Quantum computing is a hot topic and, in my experience, many would be highly motivated to participate in quantum training. Many online (sometimes free) courses are available for both beginners and advanced users. Additionally, the emergence of higher-level libraries and abstraction layers makes it easier to create useful quantum software without mastering the fine details of how quantum computers are built or resorting to intricate low-level coding. Often, quantum computing efforts sometimes grow from the bottom up, not by executive edict, and motivated employees just need permission to spend more time learning and exploring. Last, up-skilling promotes employee retention and job satisfaction.

Another option is to plug the skills gap using consulting companies. Firms like BCG or Deloitte can perform two types of functions. The first educating executives, identifying promising use cases, and providing industry benchmarks can be very useful to accelerate a companys quantum program. The second actually writing quantum computing code, whether by generalist companies or those specializing in quantum computing can be a mixed blessing. They might provide trained, able consultants, but organizations sometimes worry about IP-sharing arrangements or the ability to develop their workforce when relying on outside parties.

Last, an emerging option is quantum API marketplaces. Just like Google provides an API for finding the best route between two points, quantum API marketplaces provide pay per use quantum algorithms for optimization, random number generation, and more. They potentially allow faster exploration of use cases without the burden of coding sophisticated algorithms.

Im not recommending shying away from hiring quantum PhDs but rather exploring an intelligent mix of these alternatives. Quantum computing is too important to ignore. Dont slow down the progress by exclusively relying on outside talent.

Yuval Boger is a quantum computing executive. Known as the original Qubit Guy, he most recently served as Chief Marketing Officer for Classiq.

September 1, 2022

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Is Hiring Quantum PhDs the Answer? - Quantum Computing Report

Westford, USA, Aug. 30, 2022 (GLOBE NEWSWIRE) -- Quantum computers touted as next big thing in computing. Major reliance on quantum computers could mean we're soon entering a new era of artificial intelligence, ubiquitous sensors, and more efficient drug discovery. While quantum computers are still in the earliest stages of development, growing interest in their capabilities means that they are likely to become a central part of future computing systems. This has created a growing demand for quantum computing market and software, with providers already reporting strong demand from major customers.

The promise of quantum computing is that it can solve complex problems much faster than traditional computers. This is because quantum computers are able to exploit the properties of subatomic particles such as photons, which are able to ferry information around extremely fast. So far, quantum computing market has been witnessing a demand coming mainly for scientific and research purposes.

However, this is set to change soon as there is growing demand for quantum computers market for various applications such as artificial intelligence (AI), machine learning and data analytics. Artificial intelligence (AI) is one application that could benefit greatly from the speed and accuracy of quantum computing. AI relies on algorithms that are trained on large data sets and are able to learn and improve upon their skills with repeated use. However, classical computer databases can take hours or even days to train an AI algorithm.

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Only 4 Countries are Responsible for 86% of Total Funding Since 2001

Quantum computing market is heating up. Companies like Google and IBM are racing to develop the technology, which could one day lead to massive improvements in artificial intelligence and other areas of cybersecurity. As per SkyQuests analysis, $1.9 billion public funding was announced in the second half of the year 2021, which, in turn, took the total global funding to $31 billion from year 2001. It was also observed that most of the private and public funding is coming from the US only, which account for around 49% of the private fundings, which is followed by UK (17%), Canada (14%), and China (6%).

In 2021, the global quantum computing market witnessed an investment of around $3 billion, out of which $1.9 billion came in the second of the year. All this investment is coming from both private and public domain to feast on the upcoming opportunity of generating around $41 billion revenue by the year 2040 at a CAGR of more than 30%. The market is projected to experience a significant surge in the demand for quantum sensing and Quantum communication in the years to come. As a result, investors have started pouring money to take advantage of rapidly expanding field. For instance, in 2021 alone, $1.1 billion out of $3 billion were invested in these two technologies. To be precise, $400 million and $700 million respectively.

SkyQuest has done deep study on public and private investment coming into global quantum computing market. This will help the market participants in understanding who are the major investors, what is their area of interest, what makes them to invest in the technology, investors profile analysis, investment pockets, among others.

IonQ, Rigetti, and D-Wave are Emerging Players in Global Quantum Computing Market

As quantum computing market becomes more mainstream, companies like IonQ, Rigetti and D-Wave are quickly proving they are the top emerging players in the field. IonQ is has been working on developing ionic quantum computer technology for several years now. IonQs flagship product is the IonQ One, which is a single-core quantum computer that can process quantum information.

The IonQ One has already been deployed at a number of institutions around the global quantum computing market including NASA.

Rigetti is another company that has been making significant strides in the development of quantum computing technology. Rigettis flagship product is the Rigetti Quilter, which is a scalable two-qubit quantum computer. The Rigetti Quilter is currently undergoing Phase II testing at NASAs Ames Research Center. D-Wave has also been making significant progress in the development of quantum computing technology. D-Waves flagship product is the D-Wave Two, which is a five-qubit quantum computer. The D-Wave Two was recently deployed at Google physicists to help accelerate the discovery of new phenomena in physics.

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Regetti has secured a total funding of around $298 million through 11 rounds until 2022 in the global quantum computing market. As per our analysis, the company has secured its last funding through post IPO equity. Wherein, Bessemer Venture Partners and Franklin Templeton Investments are the major investor in the company.

As per SkyQuests findings, these three organizations have collectively generated revenue of around $32 million in 2021 with market cap of more than $3 billion. However, at the same time, they are facing heavy loss. For instance, in 2021, they faced collective loss of over $150 million. Our observation also noticed that billions of dollars are poured into building the quantum computers, but most of the market players are not earning much in revenue in terms of ROI.

SkyQuest has published a report on global quantum computing market and have tracked all the current developments, market revenue, companys growth plans and strategies, their ROI, SWOT analysis, and value chain analysis. Apart from this, the provides insights about market dynamics, competitive landscape, market share analysis, opportunities, trends, among others.

Machine Learning Generated Revenue of Over $189 Million in 2021

Today, machine learning is heavily used for training artificial intelligence systems using data. Quantum computing market can help to speed up the process of training these systems by vastly increasing the amount of data that can be processed. This potential advantage of quantum computing is the ability to perform Fast Fourier Transform (FFT) calculations millions of times faster than classical computers. This is important for tasks like image processing and machine learning, which rely on fast FFT algorithms for comparing data sets.

A huge potential of quantum computing market has led to the development of several machine learning applications that use quantum computers. Some of these applications include fraud detection, drug discovery, and speech recognition. As per SkyQuest, fraud detection and drug discovery market were valued at around $25.1 billion and $75 billion, respectively. This represents a huge revenue opportunity for quantum computing market.

This technology has been used for a variety of purposes, including predicting the stock market and automating tasks such as decision making and recommendations. In machine learning, generating revenue is a major challenge through traditional processing. Wherein, traditional computer processing can only handle a small amount of data at a time. This limits how much data can be used in machine learning projects, which in turn limits the accuracy of the predictions made by the ANNs.

Quantum computing solves this problem by allowing computers to perform multiple calculations at the same time. This makes it possible to process vast amounts of data and make accurate predictions. As a result, quantum computing has already begun to revolutionize machine learning market.

SkyQuest has prepared a report on global quantum computing market. The report has segmented the market by application and done in-depth analysis of each application in revenue generation, market forecast, factors responsible for growth, and top players by applications, among others. The report would help to understand the potential of global market by application and understand how other players performing and generating revenue in each segment.

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Top Development in Global Quantum Computing Market

Top Players in Global Quantum Computing Market

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Quantum Computing Market to Expand by 500% by 2028 | 86% of Investments in Quantum Computing Comes from 4 countries - GlobeNewswire

Fujitsu and Japans Riken research institution will team to deliver Japan-made quantum computing starting next April, according to an article on the Nikkei Asia news site.The story states that Fujitsus quantum system is expected to have 64 qubits, more than the 53 qubits in Googles 2019 machine and second to IBMs 127 qubits developed in 2021, Nikkei reported, adding that Fujitsu hopes to deliver a machine with more than 1,000 qubits in 2026.

Last April, Fujitsu and Riken built a base in Saitama, Japan for joint quantum computing development, the Nikkei story stated, with approximately 20 researchers on site. The system is expected to be used for financial forecasting, new materials and medical workloads.

Fujitsu will now use technology and know-how from Riken to become the first Japanese company to build quantum computers, the story said. Like Google and IBM, Fujitsu will adopt a method of computing with a superconductive circuit that is cooled to extremely low temperatures to eliminate electrical resistance.

In other quantum, Chinese AI company Baidu announced last week its first superconducting quantum computer that fully integrates hardware, software, and applications, according to the company.

Baidu also introduced the worlds first all-platform quantum hardware-software integration solution that provides access to various quantum chips via mobile app, PC, and cloud, the company said.

Located at Baidus Quantum Computing Hardware Lab in Beijing, Qian Shi is Baidus first industry-level superconducting quantum computer. Baidu said the system incorporates its hardware platform with Baidus home-grown software stack.

Qian Shi offers high-fidelity 10 quantum bits (qubits) of power, the company said. In addition, Baidu has recently completed the design of a 36-qubit superconducting quantum chip with couplers, which demonstrates promising simulation results across key metrics.

Baidu also highlighted development of Liang Xi, which the company said is the first all-platform quantum hardware-software integration that offers quantum services through private deployment, cloud services, and hardware access. Liang Xi plugs into Qian Shi and other third-party quantum computers, including a 10-qubit superconducting quantum device and a trapped ion quantum device developed by the Chinese Academy of Sciences. Users can visit these quantum computational resources via mobile app, PC, and cloud, Baidu said.

With Qian Shi and Liang Xi, users can create quantum algorithms and use quantum computing power without developing their own quantum hardware, control systems, or programming languages, said Dr. Runyao Duan, Director of the Institute for Quantum Computing at Baidu Research. Baidus innovations make it possible to access quantum computing anytime and anywhere, even via smartphone. Baidus platform is also instantly compatible with a wide range of quantum chips, meaning plug-and-play access is now a reality.

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Fujitsu, Riken Partner to Deliver Quantum Computing in Japan Next Year - High-Performance Computing News Analysis | insideHPC - insideHPC