The National Academies of Science, Engineering, and Medicine yesterday released a report – Quantum Computing: Progress and Prospects – whose optimism about quantum computing’s potential is matched by its cautionary tone on QC’s near-term prospects. After a webinar to introduce the report, one questioner asked the presenting panel if the report’s finding that practical, error-corrected quantum computers won’t be built for a decade or longer wasn’t too disappointing.
“I think we need to be careful to remember that there’s a range of quantum computers that the report was discussing. [It] is the case the fully error-corrected quantum computers that can crack modern cyphers are quite far off, over a decade off,” answered Mark Horowitz, chair of the NASEM committee that prepared the report and a Stanford University professor, “but there are a number of groups working to build these noisy intermediate scale quantum computers (NISQ). The committee thinks that those are likely to be deployed relatively quickly, in the early 2020s, and the capabilities of those machines is still a little bit uncertain so, yes there are many challenges to build the ultimate quantum computer but I think there are opportunities for quantum computers much sooner than when those larger machines are built.”
In many ways one could argue this latest report is a needed dose of realism in today’s hyperventilating quantum computing environment. Make no mistake, the report argues that quantum computing has formidable potential and the swelling investments in QC and its surging research activities are fully justified. Indeed more is required given the brewing global race, contends the report. Nevertheless, the caveat is a substantial one; many problems remain to be solved perhaps error correction preeminent among them.
Even the worry over quantum computing’s potential to crack current cryptographic algorithms – part of the reason the report was commissioned by director of National Intelligence – is premature says the report.
Quick excerpt: “The committee (Committee on Technical Assessment of the Feasibility and Implications of Quantum Computing) focused on understanding the current state of quantum computing hardware, software, and algorithms, and what advances would be needed to create a scalable, gate-based quantum computer capable of deploying Shor’s algorithm. Early in this process, it became clear that the current engineering approaches could not directly scale to the size needed to create this scalable, fully error corrected quantum computer.”
John Martinis, another member of the committee and prominent quantum computing researcher at Google said during the webinar Q&A, “Progress in the field has been quite good in the last few years, and people have been able not just to do basics physics experiments but [also] to start building quantum computing systems. I think there’s a lot more optimism that people can build things and get it to work properly. Of course there’s lot of work to be done to get them to work well and match them to problems but the pace [of progress] has picked up and there’s interesting things that have come out. I think that in the next year or two, [we] won’t get to solving actual problems yet but there will be a lot better machines out there.”
You get the picture. Quantum computing is important, perhaps vastly so for some classes of problems including security, but it’s not here yet and will only arrive with continued investment and patience according to this study. The study seems designed to temper near-term expectations while steeling interested parties for a longer-term effort.
The report is a broad and accessible compilation of the key aspects of quantum computing technology as they exist today. For those less familiar with QC, the summary section is a good overview. For long-time quantum watchers, while most of the material won’t be new, the core of the report is substantive if not tutorial. It’s divided into seven chapters:
- Progress in Computing (chapter 1) provides background and context on the field of computing, introducing the computational advantage of a quantum computer. It takes a careful look at why and how classical computing technologies scaled in performance for over half a century.
- Quantum Computing: A New Paradigm (chapter 2) introduces the principles of quantum mechanics that make quantum computing different, exciting, and challenging to implement, and compares them with operations of the computers deployed today, which process information according to classical laws of physics—known in the quantum computing community as “classical computers.” It introduces the three different types of quantum computing studied in this report: analog quantum, digital noisy intermediate-scale quantum (digital NISQ), and fully error corrected quantum computers.
- Quantum Algorithms and Applications (chapter 3) looks at quantum algorithms in more depth. The chapter starts with known foundational algorithms for fully error corrected machines but then shows that the overhead for error correction is quite large—that is, it takes many physical qubits and physical gate operations to emulate an error-free, so-called logical qubit that can be used in complex algorithms. “Such machines are therefore unlikely to exist for a number of years.”
- Quantum Computing’s Implications for Cryptography (chapter 4) discusses the classical cryptographic ciphers currently used to protect electronic data and communications, how a large quantum computer could defeat these systems, and what the cryptography community should do now (and has begun to do) to address these vulnerabilities.
- Chapters 5 (hardware) and 6 (software) discuss general architectures and progress to date in building the necessary hardware and software components, respectively, required for quantum computing.
- Feasibility and Time Frames of Quantum Computing (chapter 7) provides the committee’s assessment of the technical progress and other factors required to make significant progress in quantum computing, tools for assessing and reassessing the possible time frames and implications of such developments, and an outlook for the future of the field.
The report hits all the right topics in an overview fashion. Quantum subsystems (which are quite challenging), software, quantum sensing and metrology, the necessity of blending classical computing with quantum processors to build functional quantum computers, etc. As an example, quantum storage has turned out to be tricky.
“Quantum storage is challenging because of a fundamental characteristic of quantum systems. It’s the no cloning theory, which says that you can’t have quantum information and then copy it some place and leave the original version the same. As a result if you talk about quantum storage you typically are talking about a thing that is referred to as QRAM which actually has some classical storage [that quickly encodes] that classical storage into quantum state. We talk a little bit about that in the report. That’s a technology which is much less developed than current qubit technology,” noted Bob Blakley, a committee member and the Global Head of Information Security Innovation at Citigroup.
Martinis said, “The idea of breaking the quantum computer into the different subsystems is of course important and you want to think about that. But because of this no cloning, no copying [rule], it means that the interfaces between all the different components are fundamentally different because you can’t just send the information in a box like you can for a classical computer. That means you have to have a much higher degree of system integration as you build complex quantum computers system. So it’s possible to do all of this. It just makes it more difficult.”
In tackling the problem, the report broadly classifies quantum computers into three general categories: “(1) Analog quantum computers” directly manipulate the interactions between qubits without breaking these actions into primitive gate operations. Examples of analog machines include quantum annealers, adiabatic quantum computers, and direct quantum simulators. (2) Digital NISQ computers operate by carrying out an algorithm of interest using primitive gate operations on physical qubits. Noise is present in both of these types of machine, which means that the quality (measured by error rates and qubit coherence times) will limit the complexity of the problems that these machines can solve. (3) Fully error-corrected quantum computers” are a version of gate-based QCs made more robust through deployment of quantum error correction (QEC), which enables noisy physical qubits to emulate stable logical qubits so that the computer behaves reliably for any computation.”
Most of the discussion is of systems built from superconducting qubits or trapped ions which seem to be the most advanced qubit technologies at present. Error correcting, not surprisingly, received a fair amount of discussion. “QEC incurs significant overheads in terms of both the number of physical qubits required to emulate a more robust and stable qubit, called a ‘logical qubit,’ and the number of primitive qubit operations that must be performed on physical qubits to emulate a quantum operation on this logical qubit,” notes the report. (See table below)
The notions of quantum supremacy and quantum advantage are also addressed: “Demonstration of ‘quantum supremacy’—that is, completing a task that is intractable on a classical computer, whether or not the task has practical utility—is one. While several teams have been focused on this goal, it has not yet been demonstrated (as of mid-2018). Another major milestone is creating a commercially useful quantum computer, which would require a QC that carries out at least one practical task more efficiently than any classical computer. While this milestone is in theory harder than achieving quantum supremacy—since the application in question must be better and more useful than available classical approaches—proving quantum supremacy could be difficult, especially for analog QC. Thus, it is possible that a useful application could arise before quantum supremacy is demonstrated.”
The new report echoes the notion that quantum computers will be special purpose devices.
“Quantum computing is not likely to take over for classical computing,” said Horowitz during Q&A. “It is rather more likely to be used as an accelerator attached to conventional computing to help in certain kinds of computations. In many kinds of computations quantum computers would not actually be better than a classical computer; the classical computer would be better and certainly cheaper.”
Martinis agreed and suggested an internet or cloud-based access model is what is likely to emerge in terms of gaining access and indeed IBM, Rigetti Computing, and D-Wave all offer quantum clouds now.
Asked if there might ever be a quantum laptop, he said “I think you want to imagine a quantum computer being like a supercomputer which are traditionally very big machines and that’s what people are building right now. The various implementations are 3m x 3m x 3m kinds of machines looking at all the hardware. And of course in the beginning [they are] perhaps a little bit large because you kind of brute force it and don’t have all the technologies scaled down to do everything. But as you want to scale up the number of qubits, it’s probably going to stay large.
“So I think it’s going to be a large, a special purpose machine for next few years and who knows what’s going to happen in the future. I think one of the interesting things that’s happened is these machines are now available on cloud access so you’re remotely accessing that. So although it is nice to think about having a quantum computer in your own lab or space, it works just fine for the quantum computer to be remotely somewhere and use the internet and cloud computing to access that. [If] you think about your cell phone right now, that’s basically what you are doing. Your cellphone is an interface device and all the big computing is done in a datacenters. We think that’s probably the right model in going forward in the future.”
The report is best read directly and is available as a free PDF. It will be interesting to monitor how closely this report hits or misses the mark.
Member of the Academies’ Committee on Technical Assessment of the Feasibility and Implications of Quantum Computing, which prepared the report: Mark A. Horowitz, NAE, Stanford University, chair; Alán Aspuru-Guzik, University of Toronto; David D. Awschalom, NAS/NAE, University of Chicago; Bob Blakley, Citigroup; Dan Boneh, NAE, Stanford University; Susan N. Coppersmith, NAS, University of Wisconsin, Madison; Jungsang Kim, Duke University; John M. Martinis, Google; Margaret Martonosi, Princeton University; Michele Mosca, University of Waterloo; William D. Oliver, Massachusetts Institute of Technology; Krysta Svore, Microsoft Research; Umesh V. Vazirani, NAS, University of California, Berkeley
Images/Figures Source: Quantum Computing: Progress and Prospects report from the National Academies of Science, Engineering, and Medicine, 12/3/18