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Quantum computing: A cheat sheet

Cyber security TechRepublic today20/11/2020

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IBM, Honeywell, and Intel are just three companies leading the way in building quantum machines as well as the algorithms and controls to run them. Learn about possible business use cases for quantum.

Quantum computing–considered to be the next generation of high-performance computing–is a rapidly-changing field that receives equal parts attention in academia and in enterprise research labs. Honeywell, IBM, and Intel are independently developing their own implementations of quantum systems, as are startups such as D-Wave Systems. In late 2018, President Donald Trump signed the National Quantum Initiative Act that provides $1.2 billion for quantum research and development. 

TechRepublic’s cheat sheet for quantum computing is positioned both as an easily digestible introduction to a new paradigm of computing, as well as a living guide that will be updated periodically to keep IT leaders informed on advances in the science and commercialization of quantum computing.

SEE: The CIO’s guide to quantum computing (ZDNet/TechRepublic special feature) | Download the free PDF version (TechRepublic)

Executive summary

  • What is quantum computing? Quantum computing is a developing technology that scientists anticipate will provide faster computational solutions to problems currently handled by supercomputers.
  • Why does quantum computing matter? Theoretically, quantum computers could be used to crack RSA cryptography, which is commonly used across the internet. Quantum computing also has the potential to solve problems that were previously considered unsolvable. 
  • Who does quantum computing affect? Primarily researchers working in quantum physics, though advances in quantum computing are anticipated to influence other “fuzzy logic” disciplines, such as artificial intelligence (AI) and machine learning (ML).
  • What are the business opportunities related to quantum computing? All industries will benefit through different use cases because quantum computing allows data to be consumed and processed faster while using less energy. 
  • Which companies are leading the quantum computing race? AWS, Google, Honeywell, IBM, and Microsoft are developing quantum computing capabilities and services. Intel is building quantum processors. Smaller companies including 1QBit, D-Wave, IonQ, and Rigetti Computing are also working on quantum computing, including quantum devices and quantum services.  
  • What is quantum computing as a service? Both large tech companies and startups working in the quantum world have turned to the “as a service” model to make this new compute power available to a broader audience. 
  • When will quantum computers be released? Systems limited to a specific type of quantum computation called digital annealing are commercially available, though there is not yet a clear benefit compared to traditional computers.
  • How do I get a quantum computer? Several vendors offer cloud-based access to quantum computers. Even though purchasing a system outright is possible, it is likely cost prohibitive, as current systems are only useful for specialized workloads.

SEE: All of TechRepublic’s cheat sheets and smart person’s guides

What is quantum computing?

Quantum computing is an emerging technology that attempts to overcome limitations inherent to traditional, transistor-based computers. Transistor-based computers rely on the encoding of data in binary bits–either 0 or 1. Quantum computers utilize qubits, which have different operational properties. While it is possible to encode binary data in a qubit, the natural state of a qubit is essentially superposition. This property allows qubits to have values of 0 and 1 (or values between 0 and 1) simultaneously. Likewise, because of the properties of quantum physics, multiple measurements of qubits in identical states will not return identical results. Qubits can also contain up to two bits of binary data as part of a process called superdense coding.

Using quantum computation, mathematically complex tasks that are at present typically handled by supercomputers–protein folding, for example–can theoretically be performed by quantum computers at a lower energy cost than transistor-based supercomputers. While current quantum machines are essentially proof-of-concept devices, the algorithms which would be used on production-ready machines are being tested presently, to ensure that the results are predictable and reproducible. At the current stage of development, a given problem can be solved by both quantum and traditional (binary) computers. As manufacturing processes used to build quantum computers is refined, it is anticipated that they will become faster at computational tasks than traditional, binary computers.

Further, quantum supremacy is the threshold at which quantum computers are theorized to be capable of solving problems, which traditional computers would not (practically) be able to solve. Practically speaking, quantum supremacy would provide a superpolynomial speed increase over the best known (or possible) algorithm designed for traditional computers. Theoretically, this can be demonstrated using Shor’s algorithm for prime factorization, which would provide such a speed increase when performed on a quantum computer, as factoring is thought to be generally hard with traditional computers (though, this is not proven, in the scientific sense of “proof”).

SEE: Research: Quantum computing in the enterprise; key vendors, anticipated benefits, and impact (TechRepublic Premium)

Researchers use the NISQ (Noisy Intermediate-Scale Quantum Computing) label to describe all the quantum machines operating currently; this means the machines don’t have full-blown error correction. Researchers can submit their quantum queries to cloud-based services to gain experience with what quantum computers can do.

A research paper published in Science in October 2018 titled “Quantum advantage with shallow circuits” tested a variant of the Bernstein-Vazirani problem, in which researchers proved that a quantum computer with a fixed circuit depth will outperform a classical computer used to compute the same problem. While this does not itself establish quantum supremacy, it does demonstrate the potential of quantum computers as refined designs increase the number of qubits, and the length of quantum coherence, allowing for more complex calculations to be performed.

Quantum volume is another way to measure the progress of the industry, as Paul Smith-Goodson explained for Forbes. Quantum volume measures several components of a quantum computer’s performance, including coherence, calibration errors, crosstalk, spectator errors, gate fidelity, measurement, and fidelity. The calculation also takes into account design elements of each machine. A quantum volume score indicates the complexity of a problem that the computer can solve. 

IBM announced in August 2020 that it has achieved a quantum volume of 64 with a 27-qubit client-deployed system. Honeywell reported in June 2020 that it had reached a quantum volume of 64 with a 6-qubit system. 

The next milestone that is still some years in the future is quantum advantage. When quantum computers hit that milestone, the machines will be able to solve real-world problems that classical computers can’t crack. 

Additional resources:

Why does quantum computing matter?

Theoretically, advancements in quantum computing would lead to a breakthrough in integer factorization. If integer factorization became trivial to perform, the integrity of commonly used encryption systems would be shattered, allowing any individual, organization, or government with access to quantum computers the ability to brute-force decryption keys, with which locked devices or encrypted archives can be made accessible. Because of concerns in the cybersecurity community about the viability of quantum computers in breaking encryption, research into lattice-based cryptography–which is thought to not be susceptible to being broken by quantum computers–has increased.

To that end, in January 2014, reports indicated that the NSA has spent $79.7 million on a program titled “Penetrating Hard Targets.” As part of this program, research was conducted to build “a cryptologically useful quantum computer.” The documents cited in this report indicate that the NSA has not been appreciably more successful than other researchers. Likewise, the National Institute of Standards and Technology (NIST) published a request in December 2016 asking for public input on how to protect computers from the threat of quantum computers being used to crack encryption.

There is no consensus on when quantum computers will be capable of cracking encryption. In a May 2018 interview with TechRepublic, Bob Sutor, IBM Research’s vice president of cognitive, blockchain, and quantum solutions, estimated that quantum computers are 30-40 years away from breaking traditional cryptographic algorithms. The same month, IBM’s then research director and current chief executive officer Arvind Krishna warned that “Anyone that wants to make sure that their data is protected for longer than 10 years should move to alternate forms of encryption now.”

SEE: Quantum encryption: How it works (TechRepublic)

Quantum computing is also anticipated to have other meaningful impacts outside of the field of cryptography. Because of the nature of quantum computation, they are uniquely well suited to so-called “optimization problems,” where an exponential number of permutations to evaluate exist. In an interview with TechRepublic, Andy Stanford Clark, IBM CTO for UK and Ireland provided an example: “If… you’re optimizing the lengths of aircraft routes, or optimizing the layout of spare parts for a rail network, something where there’s 2n possibilities and you’ve got to try each out in order to find the optimal solution. If you had a 2100 problem, which would be basically impossible to solve on a classical computer, with a 100-qubit quantum computer, you’d be able to solve it in one operation.”

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Who does quantum computing affect?

Research into quantum computing is driving a great deal of investment from universities, IT companies, and venture capital. Multiple public-private partnerships have sprung up as businesses work with research departments in universities to find use cases where quantum computing can be applied to existing business operations.

The IBM Q Network is the largest of these, with participating universities including North Carolina State University, Melbourne University, Oxford University, and Keio University, and participating companies including Samsung, JPMorgan Chase, Mitsubishi UFJ Financial Group, Mizuho Financial Group, and Mitsubishi Chemical.

Others include a collaboration between the Australian firm Silicon Quantum Computing, and France’s national research and development (R&D) organization, the Commissariat à l’Energie Atomique et aux Energies Alternatives (CEA).

In December 2018, Trump signed into law the National Quantum Initiative Act. This established the National Quantum Initiative Program, which will devise a 10-year plan to speed up the development of quantum information science and technology. The act also directed the National Science and Technology Council, the National Institute of Standards and Technology, the National Science Foundation, and the Department of Energy to support the effort with related initiatives. The White House announced the National Quantum Initiative Advisory Committee in August 2020, which includes individuals from the University of Chicago, Intel, Google, Sandia National Laboratories, Microsoft Research, Harvard University, Duke University, and other universities and research institutes.

Also in August 2020, the White House Office of Science and Technology Policy (OSTP) and the Department of Energy announced funding up to $625 million over five years to support five quantum research centers at national labs around the country. 

Additional resources:

What are the business opportunities related to quantum computing?  

Quantum computing has the potential to solve complex problems in every industry–some of the first use cases will be in finance, chemistry, pharmaceutical research, and logistics. Quantum computers will be able to analyze an almost infinite number of possible solutions to find the most promising ones. With logistics, for example, a quantum algorithm could analyze delivery routes or transportation schedules to identify the most efficient or fastest routes. An airline that used a quantum computer for route planning could develop a strategic advantage over another that didn’t. Denise Ruffner, the head of business development at IonQ, said that the industry is nearing the end of the early adopter phase. Now is the time to understand the potential of quantum computing and its business applications.

JPMorgan Chase has been doing just that–the banking company was one of the early customers for IBM’s quantum computer. The company also has been exploring the “quantum culture” and giving senior engineer Constantin Gonciulea time to prepare the company for the quantum future. He expects quantum computing to be fully commercialized in five to 10 years and is laying the groundwork for JPMorgan Chase to be ready to take advantage of that computing power–this means reading research papers and meeting with other engineers to discuss the possibilities. The financial services company is planning a Quantum Computing Summer Associates program for 2021 to build a pipeline of employees familiar with the technology.

IBM’s research director Dario Gil said at CES 2020 that the promise of quantum computing is the power to model natural processes and understand how they work. “Quantum is the only technology we know that alters the equation of what is possible to solve versus impossible to solve,” he said.

Jeannette Garcia, senior manager for quantum applications algorithms and theory at IBM Research, shared some of the real-world problems that the company is working on: 

  • Improved nitrogen-fixation process for creating ammonia-based fertilizer
  • New classes of antibiotics to counter multidrug-resistant bacteria
  • New polymers that could replace steel-based component

Garcia’s focus is battery research, which is also the topic of a new IBM partnership with Daimler. She said researchers are using quantum computing to figure out quantum chemistry.

Gil said that the “quantum ready” era started in 2016 and the next phase will start when the technology improves enough to achieve “quantum advantage.” 

“First, a whole generation of developers is going to need to learn how to program these computers,” he said. “Then when we hit quantum advantage, we’ll be able to solve real-world problems, and it’s absolutely going to happen this decade.”

Additional resources:

Which companies are leading the quantum computing race? 

IBM gets the most attention for its work in the sector to build quantum machines and to create a community around quantum computing. IBM’s quantum work has three focus areas: Accelerate research, develop commercial applications, and educate and prepare. The company’s Q Network includes Fortune 500 companies, national research labs, universities, and startups. IBM set out a quantum roadmap in September 2020 with plans for a 1,121-qubit system in 2023.

Microsoft is developing a full-stack quantum ecosystem as well as a quantum network with partners that include businesses, researchers, academics, and developers. The company’s quantum development kit includes an open-source toolkit, development environments, and an open-source community.

Honeywell has applied its deep experience with systems control to develop a quantum computer. The company uses a trapped ion model for its quantum computing service. This model uses atomic ions trapped in a vacuum and cooled with lasers as qubits. IBM and Google use superconducting qubits in their quantum computers.

Intel’s work in quantum computing covers the full stack from qubits and algorithms development to control electronics and interconnects. Jim Clarke is the director of the quantum hardware research group within Intel and a member of the National Quantum Advisory Committee. In late 2019, Intel released a cryogenic control chip called “Horse Ridge,” after one of the coldest regions in Oregon; the company claimed this will speed up development of full-stack quantum systems in part by making it easier to control multiple qubits at once. Clarke wrote at the time that a lack of research and development focused on controls technology is going to limit progress toward a large-scale quantum system. Simplifying the control cabling required to work with thousands of qubits at a time “could take quantum practicality to the finish line much faster than is currently possible,” as Clarke wrote. Intel is working with researchers in the Netherlands to build these controls.

Google is developing quantum processors and algorithms to solve theoretical and practical problems–the focus areas are superconducting qubit processors, qubit meteorology, quantum simulation, quantum assisted optimization, and quantum neural networks. Google has built two open-source frameworks to support quantum computing: Cirq and OpenFermion. In October 2019, Google announced that its 53-qubit Sycamore quantum computer completed a calculation that couldn’t be done with a classical computer. Other scientists said the calculation was chosen to build on the strengths of a quantum computer and the weaknesses of a traditional computer. In September 2020, Google announced that a 12-qubit version of its Sycamore computer had simulated a simple chemical reaction. 

In 2018, IBM held an event for quantum computing startups. Denise Ruffner was working there at the time and said it was a struggle to find 10 companies–now there are more than 650 young companies working in the sector, she said.

D-Wave, 1Qbit, IonQ, Q-CTRL, Strangeworks, Xanadu, and Zapata Computing are all taking on a different challenge in quantum computing. On ZDNet, Esther Shein rounded up eight leading quantum computing companies to watch.

Cambridge Quantum Computing is another member of the quantum ecosystem. With IBM, the company announced in September 2020 that it had built a random number generator that uses quantum computing.

Additional resources:

What is quantum computing as a service?

Both large tech companies and startups working in the quantum world have turned to the “as a service” model to make this new compute power available to a broader audience.  

As of April 2020, IBM reported that 225,000 people are using the company’s Quantum Experience cloud service. More than 100 companies are paying for its IBM Q premium service to have access to the company’s subject matter experts in addition to its hardware.

Rigetti launched its Quantum Cloud Services in 2018. The company uses a hybrid quantum-classical approach with its cloud services to support ultra-low latency connectivity between a customer’s hardware and Rigetti’s quantum computers. Rigetti’s network APIs  provide access to core quantum operating system functions such as user authentication, system service authorization, circuit submission, circuit scheduling, memory management, and concurrency.

Microsoft also offers access to quantum computing via the cloud and Azure.

Amazon launched its quantum service, Braket, in August 2020. Amazon Braket lets customers experiment with quantum computing hardware to gain hands-on experience with the technology. It’s is a single development environment for building quantum algorithms, testing them on simulated quantum computers, and trying them on several quantum hardware architectures. The platform includes systems from D-Wave, IonQ, and Rigetti. Amazon also is exploring mass-produced quantum computers through its new Center for Quantum Computing.

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When will quantum computers be available?

More about Innovation

There are two answers to this question: Now, and substantially far in the future. The Canadian company D-Wave Systems sells a 5,000-qubit Advantage system, which Los Alamos National Laboratory planned to install this year. D-Wave’s machine is a quantum annealer. Quantum annealing is the best approach for problems that have multiple “good enough solutions,” as opposed to problems that have one ideal answer. D-Wave’s approach will not be able to break modern cryptology but it will be able to find ways to make planes fly faster.

Fujitsu offers a “quantum inspired” digital annealer, which is a traditional transistor-based computer designed for quantum annealing tasks. However, Fujitsu does not market this system as a true quantum computer, as the traditional transistor-based design allows it to operate at room temperature without requiring helium-based cooling solutions, as well as making it resistant to noise and environmental conditions which impact performance in quantum computers.

In a general sense, it is possible that quantum computing may be a viable alternative in the future to current transistor-based solutions, though non-trivial encumbrances in fabrication and mass-manufacturing must be addressed for this to become a viable technology for mass industry adoption. Among these encumbrances are the difficulty of building computers which scale to multiple qubits, the ability to initialize qubits to a predictable value, and easing the means by which qubits can be read.

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How do I get a quantum computer?

A quantum computer is not something you will find at your local big-box store. Quantum computing resources are widely available via cloud services with vendor-specific frameworks. Offerings are available from IBM Q (via Qiskit), while Google has introduced the Cirq framework, though it does not presently have a cloud offering in general availability. D-Wave Leap allows approved developers to conduct quantum experiments for free on its Leap Quantum Development Environment. Similarly, Fujitsu offers cloud access to its digital annealer system.

For buying systems outright, D-Wave’s 2000Q system costs $15 million (notable buyers include Volkswagen Group and Virginia Tech). If your workloads are more general, building and buying a POWER9 deployment is likely a better value. Oak Ridge National Laboratory’s SUMMIT supercomputer is a POWER9 and NVIDIA Volta-driven system planned at 4600 nodes, with a computational performance in excess of 40 teraflops per node.

Editor’s note: This article was updated by Veronica Combs. 

Vibrant glowing qubit

Image: sakkmesterke, Getty Images/iStockphoto

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