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Engineering Tomorrow鈥檚 Quantum Computers

Researchers have touted the revolutionary potential of quantum computers to take on otherwise intractable challenges, like modeling complex molecular behavior for drug discovery or factoring enormous numbers in use for cryptography schemes. But what would a large-scale quantum computer actually look like?

That turns out to be a difficult question to answer, even in general terms. Add parameters and specifications and it becomes even more daunting.

But with help from the 秘密直播 Applied Physics Laboratory (APL) in Laurel, Maryland, the Defense Advanced Research Projects Agency (DARPA) is attempting to do just that: define, in practical terms, what a useful quantum computer looks like and how it must be built.

, DARPA鈥檚 Underexplored Systems for Utility-Scale Quantum Computing (US2QC) program aims to evaluate less-taken roads to determine whether quantum computing at scale might be achieved in a matter of years rather than decades, as many experts predict 鈥 and if so, how. In July 2024, DARPA that US2QC will be combined with a related program to found the Quantum Benchmarking Initiative (QBI), which builds and expands upon US2QC.

Joan Hoffmann, who leads the Research and Exploratory Development Mission Area at APL, expressed excitement at the Laboratory鈥檚 role in this effort.

鈥淭he earliest computers were massive mechanical calculators, and then from there the field went to using vacuum tubes, but what ultimately pushed computers forward was the discovery of transistors,鈥 Hoffmann said. 鈥淣o one knows what the equivalent of the transistor will be for quantum computing, but it鈥檚 fascinating to dig in and try to figure that out.鈥

More Qubits, Fewer Errors

The beating heart of quantum computing is the quantum bit, or qubit. Unlike classical computer bits, which are coded as either zeros or ones, qubits can exist in multiple states at once. The combination of a qubit鈥檚 analog nature 鈥 its ability to take values other than exactly zero or one 鈥 and entanglement, which connects multiple qubits in nonintuitive ways, allows for novel and extremely efficient solutions for certain challenging problems.

But these very properties also make qubits extremely sensitive to their environment, and thus error-prone.

The quest for a utility-scale quantum computer can be summarized in four deceptively simple words: more qubits, fewer errors. Accuracy demands two more: millions more qubits, far fewer errors.

Therein lies the rub.

鈥淭he two current leading technologies 鈥 superconducting qubits and ion traps 鈥 have shown incredible performance at the single qubit level, but it鈥檚 not known whether their dominance will continue as larger fault-tolerant algorithm-scale designs become the focus of the field,鈥 said Scott Hendrickson, APL鈥檚 US2QC project manager. 鈥淭here are many hard problems that have to be solved in order to scale these technologies toward millions of qubits.鈥

The solution, ironically, may come from technologies that academics threw out long ago, such as photonics, topological quantum computing and trapped neutral atoms: approaches that were slow to mature for making systems with small numbers of qubits, Hendrickson says, but may turn out to be much better for creating systems with millions of them. And commercial companies are now picking up on that advantage.

In January 2023, DARPA and tasked them with presenting a design concept for a utility-scale quantum computer. In February, after almost two years of rigorous technical analysis of the design concepts, two of those companies to advance to the program鈥檚 validation and co-design phase; and in April, the agency that nearly 20 quantum computing companies have been chosen to participate in the initial stage of QBI, in which they will characterize their unique concepts for creating a useful, fault-tolerant quantum computer within a decade.

Engineering Not-Yet-Existent Systems

DARPA tapped APL at the very beginning of the US2QC program to leverage its world-renowned systems engineering expertise and distinguished quantum information team 鈥 qualities that uniquely position the Laboratory to create frameworks for evaluating quantum computing platforms using these previously discarded modalities.

But this effort places a paradoxical demand on that expertise, applying systems engineering principles to systems that have not yet been invented.

鈥淚f you鈥檙e building a skyscraper, it鈥檚 all about keeping everything on track, but if you鈥檙e going to the Moon for the first time, you don鈥檛 know enough at the outset to know what 鈥榦n track鈥 even looks like,鈥 said Scott Simpkins, APL鈥檚 US2QC systems engineering lead. 鈥淭he moon shot is APL鈥檚 strength, and in this context, systems engineering takes on a dynamic, proactive quality.鈥

For an effort that involves so many unknowns, Simpkins said, that means asking the right questions, which in turn means assembling the right team 鈥 in this case, systems engineers and quantum physics experts from across APL.

By combining the results-oriented skills of the former and the relentlessly inquisitive nature of the latter, the team is developing parameters, specifications and performance targets against which to measure the prototype systems being developed by commercial companies.

鈥淧hysicists like to attack the most exotic and interesting parts of the problem, but sometimes the reason the technology won鈥檛 advance is something very mundane, like not being able to engineer a certain necessary part,鈥 Hendrickson said. 鈥淏y putting the scientists and the systems engineering into conversation, you get that complete picture.鈥

Ultimately, if the companies succeed in developing their prototypes and demonstrating their scalability according to the APL-produced standards, the Laboratory team will produce documents that explain 鈥 precisely and in depth 鈥 how to build, operate and maintain utility-scale quantum computers for specific applications.

鈥淢aybe the government needs one system to be deployable, another that can process sensitive data and still another that needs to be optimized for raw computational power,鈥 Simpkins said. 鈥淚f all goes well, our work will allow them to create purpose-built systems that meet their needs, whatever they might be.鈥

Pushing the Field Forward

Colin Trout, a quantum information theorist and lead US2QC scientist at APL, said even from a purely scientific perspective, the application of systems engineering principles may be just what the field needs to move forward.

鈥淨uantum computing systems are getting larger and larger, and building a viable quantum computer is starting to look more like a systems engineering problem than it did even a few years ago,鈥 Trout said. 鈥淭he lessons we鈥檙e learning will be of tremendous value to the field as we work out how to mature these technologies and where they can make the most impact.鈥

Echoing Trout鈥檚 comments, Hendrickson said that the playbook that APL is developing for US2QC is extendable well beyond the current project, even beyond the nascent Quantum Benchmarking Initiative.

鈥淲e鈥檙e creating an efficient methodology that, if all goes well, we could repeat and apply across a broad range of emerging science and technology areas,鈥 he said.

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