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C&EN Global Enterprise

Upgrading the quantum computer

Katherine Bourzac

Published Apr 15, 2019• 1 citation
Publisher

Abstract

As she walks around the lab of Rigetti Computing, quantum engineer Sabrina Hong strains to make her voice heard over a loud pumping noise. It’s the heartbeat of helium refrigerators cooling down the Berkeley, California–based start-up’s quantum computers. To perform optimally, these machines need to run below –273.14 °C (10 mK)—colder than outer space. Whoosh, supercold liquid helium is pumped in. Whoosh, warmed helium is pushed out. “I love that sound,” Hong says. It means the company’s two commercial quantum computers are up and running, at the ready for customers. Rigetti and other firms in the quantum computing business, including IBM and Google, allow customers to access their machines over the cloud and perform calculations. The pumping sound also means that the machines are ready for Hong and other engineers on the Rigetti team. She wants to improve quantum computers’ performance and would like to try out some test chips

DOI
10.1021/cen-09715-cover

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As she walks around the lab of Rigetti Computing, quantum engineer Sabrina Hong strains to make her voice heard over a loud pumping noise. It’s the heartbeat of helium refrigerators cooling down the Berkeley, California–based start-up’s quantum computers. To perform optimally, these machines need to run below –273.14 °C (10 mK)—colder than outer space. Whoosh, supercold liquid helium is pumped in. Whoosh, warmed helium is pushed out. “I love that sound,” Hong says. It means the company’s two commercial quantum computers are up and running, at the ready for customers. Rigetti and other firms in the quantum computing business, including IBM and Google, allow customers to access their machines over the cloud and perform calculations. The pumping sound also means that the machines are ready for Hong and other engineers on the Rigetti team. She wants to improve quantum computers’ performance and would like to try out some test chips
Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame
Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame.
Abstract Quantum computing leverages fundamental quantum-mechanical phenomena—most notably superposition, entanglement, and quantum tunneling—to perform computations in ways that differ fundamentally from classical digital processing. Compared to conventional computing architectures, quantum systems promise significant reductions in computational time and potentially lower energy consumption for specific classes of problems. These advantages, combined with advances in nanoscale engineering and the slowing of traditional hardware scaling trends such as Moore’s Law, have led to substantial commercial and national-security-driven investments in quantum technologies over the past decade. A major milestone was reached when Google announced the experimental demonstration of “quantum supremacy,” showing that a quantum processor could execute a specific computational task infeasible for a classical supercomputer within practical time constraints. Although the demonstrated problem had no immediate practical application, this achievement marked a crucial step toward the development of quantum systems capable of delivering real-world computational advantages and provided a more precise technical framing of the concept of quantum advantage. Despite the fact that the mathematical foundations, programming models, and principal quantum algorithms were established in the 1990s, quantum computing remained largely confined to a specialized research community for decades. Today, the increasing accessibility of cloud-based quantum hardware calls for a broader dissemination of implementation-oriented knowledge among researchers and practitioners in computer science, software engineering, and related fields. The quantum programming paradigm differs fundamentally from classical programming models and often relies on physical and algebraic notations that may pose barriers to traditionally trained computer scientists. This series of articles provides a self-contained and concise introduction to quantum computing and its core algorithms, with a strong emphasis on practical implementation. Given that real quantum processors—such as those accessible via the IBM quantum ecosystem—are now available as cloud services, experimental validation can be conducted both on simulators and on actual hardware for small-scale inputs. While other platforms such as Rigetti and IonQ also offer cloud-based quantum computing services, this review focuses exclusively on the IBM quantum computing ecosystem.
Grand engineering challenges often require an epic level of patience. that's certainly true for quantum computing. For a good 20 years now, we've known that quantum computers could, in principle, be staggeringly powerful, taking just a few minutes to work out problems that would take an ordinary computer longer than the age of the universe to solve. But the effort to build such machines has barely crossed the starting line. In fact, we're still trying to identify the best materials for the job. Today, the leading contenders are all quite exotic: There are superconducting circuits printed from materials such as aluminum and cooled to one-hundredth of a degree above absolute zero, floating ions that are made to hover above chips and are interrogated with lasers, and atoms such as nitrogen trapped in diamond matrices.
The quantum revolution is still in the slow lane. The first head-to-head speed test of the D-Wave Two, the commercial quantum computer recently purchased by Google, suggests that the machine performs no better than an ordinary PC. In theory, quantum computers are capable of calculating answers to problems much faster than standard PCs. Instead of storing information in bits as either 0s or 1s, quantum machines use quantum bits, or qubits, that can be both 0 and 1 at the same time. So far, however, the quantum devices built in labs can only support a handful of qubits, which limits their speed. Now a team led by Matthias Troyer of ETH Zurich in Switzerland has tested a D-Wave Two computer against a conventional machine running an optimized algorithm and found no evidence of superior performance in the quantum device.