Daily Archives: September 2, 2022

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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

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

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

SAN SEBASTIN, SPAIN, August 26, 2022 Quantum computing company Multiverse Computing today introduced the newest version of Singularity Portfolio Optimization (v 1.2). This release includes the Multiverse Hybrid Solver, designed to combines the strength of classical and quantum computing and is specifically suited to portfolio optimization problems.

The Multiverse Hybrid Solver can optimize large portfolios of thousands of assets, finding the portfolio with the highest returns for a given risk and producing the same quality of results as industry-standard solvers in a significantly shorter amount of time.

According to John Malcolm, Financial Engineer overseeing Singularity Portfolio Optimization at Multiverse, this new release represents the next step in the ongoing evolution of the Singularity Portfolio Optimization Excel plug-in.

This latest version of Singularity provides a quantum-based solution to a simple case portfolio optimization which is competitive against classical approaches currently used in industry, said Malcolm. Exciting new developments on our roadmap will extend the applicability of this product to cover more exotic cases of portfolio optimization which classical approaches struggle with.

The tool is designed to help portfolio managers find the optimal balance between risk and reward among the range of assets under consideration, while adhering to minimum and maximum allocations per asset according to the investors preferences.

The Singularity Portfolio Optimization Excel plug-in now offers three solvers:

This particular tool from Multiverse Computing is designed for large financial institutions, such as banks, hedge funds, pension funds and insurance companies. The generic optimization library that the Portfolio Optimization app is built on top of has much broader applicability to any sector where optimization is important, such as energy, manufacturing, health and life sciences, aerospace, and more.

The Singularity Portfolio Optimization plug-in can be used to build a portfolio from scratch or to improve an existing one. It is useful for developing medium to long-term strategies or for more frequent performance improvements. The newest interface is more streamlined and allows the user to save optimization settings for convenience.

With this latest release, Singularity users also can:

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Multiverse Computing Releases New Version of Singularity SDK for Portfolio Optimization with Quantum - High-Performance Computing News Analysis |...