{"id":59844,"date":"2025-10-07T23:05:08","date_gmt":"2025-10-07T23:05:08","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/59844\/"},"modified":"2025-10-07T23:05:08","modified_gmt":"2025-10-07T23:05:08","slug":"psiquantum-supercomputer-aiming-for-a-million-qubits","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/59844\/","title":{"rendered":"PsiQuantum Supercomputer: Aiming for a Million Qubits"},"content":{"rendered":"

In an industry where timelines are often fuzzy and subject to revision, the quantum-computing company PsiQuantum<\/a> has set itself an aggressive target. The California-based startup has committed to building a fault-tolerant<\/a> quantum computer with roughly a million qubits<\/a> by 2027. And the company is now in the process of assembling its first fully fledged prototype in a warehouse in California. Crossing the million-qubit threshold could start to realize quantum computing\u2019s promise to revolutionize areas like materials science<\/a> and chemistry. <\/p>\n

Founded by a quartet of academics from British universities in 2016, the company has raised US $1.7bn to build an optical quantum computer<\/a> based on silicon photonics<\/a>. Using photons to store and manipulate quantum information raises a very different set of challenges compared with those of \u201cmatter-based\u201d approaches like superconducting qubits<\/a>, trapped ions, or neutral atoms, says chief scientific officer and cofounder Pete Shadbolt<\/a>. But the company is betting that by building on top of mature networking and photonics<\/a> technology, it can reach scale ahead of its competitors.<\/p>\n

Realizing that vision has required PsiQuantum to make breakthroughs in materials science, develop bespoke cryogenics<\/a> technology and industrialize the production of its photonic chips<\/a>. But with the key components now in place, the company has started putting them together to build its \u201cAlpha System\u201d at a new facility in Milpitas, Calif., that will officially open later this year.<\/p>\n

\u201cThis system in California will be orders of magnitude more complex than any system we\u2019ve tested previously,\u201d says Shadbolt. \u201cThis is the first time that we\u2019re building a networked system of large numbers of photon sources with real silicon and real [cryogenic] cabinets.\u201d <\/p>\n

Planning for scale from the ground up<\/p>\n

One of the key factors that differentiates PsiQuantum from its competitors, says Shadbolt, is that the company has focused from the start on building a full-scale, fault-tolerant quantum computer. There was initially hope in the industry that smaller \u201cnoisy intermediate-scale quantum\u201d<\/a> (NISQ) computers could do useful work without error correction<\/a>, but today there\u2019s growing consensus true usefulness will become possible only with full fault tolerance.<\/p>\n

Shadbolt says PsiQauntum operated on this assumption from the start, and this drove its decision to focus on optical approaches. Reaching the millions of qubits necessary to implement error correction at scale requires you to solve four key challenges\u2014cooling, control, connectivity, and manufacturability, he says\u2014all of which are easier with photonics than competing hardware.<\/p>\n

Matter-based qubits are highly sensitive to temperature fluctuations and electromagnetic radiation<\/a>, which means they need to be chilled to near-absolute zero using either dilution refrigerators or laser-based cooling systems. In contrast, photons are resistant to both heat and radiation<\/a>, which means that in principle they can operate as qubits at room temperature.<\/p>\n

In practice, PsiQuantum\u2019s hardware is still kept at cryogenic temperatures. The design relies on superconducting<\/a> photon detectors that operate between 2 and 4 kelvins, but achieving these temperatures is much easier, says Shadbolt. While the dilution refrigerators required by superconducting qubits<\/a> can house at most one or two chips, PsiQuantum has designed cryogenic cabinets the size of a server rack that can hold roughly 250. In the company\u2019s new facility, three of these cabinets will be cooled by a cryoplant made by the engineering giant Linde<\/a>.<\/p>\n

\"A The cryoplant for PsiQuantum\u2019s upcoming prototype quantum computer.Colby Macri\/PsiQuantum<\/p>\n

Photons\u2019 resistance to heat and radiation also makes it possible to pack control electronics close to the qubits, says Shadbolt, something that is proving much harder for matter-based approaches. And crucially, photons can be transmitted over standard telecom fiber, which makes networking chips together much simpler. The company recently demonstrated<\/a> the ability to transmit qubits over 250 meters of fiber with 99.7 percent fidelity, says Shadbolt.<\/p>\n

Getting ready for mass manufacturing <\/p>\n

However, says Shadbolt, one of the biggest challenges for building a large-scale quantum computer is manufacturing. Most quantum computers<\/a> are bespoke devices. But by building on top of mature silicon-photonics technology, PsiQuantum has been able to create a commercial fabrication process for its chips, detailed in a Nature paper<\/a> earlier this year, in collaboration with Global Foundries<\/a>.<\/p>\n

\u201cThe key insight that we were founded on is that you can\u2019t change the semiconductor industry<\/a> very much,\u201d says Shadbolt. \u201cIf you want to make millions of devices at a high level of maturity, you need to leverage the trillion dollars in 50 years that\u2019s gone into the semiconductor industry.\u201d<\/p>\n

Getting the company\u2019s chips production-ready wasn\u2019t simple, as it incorporated novel designs and materials, including superconducting photon detectors and ultrafast optical switches. But Global Foundries is now churning out thousands of PsiQuantum\u2019s chips at a commercial semiconductor fab in Malta, N.Y.<\/p>\n

While all the components have been independently tested, the system under construction in Milpitas will be the first true test of the company\u2019s overall architecture. Shadbolt says he hopes to have the system cold by the end of the year, ready to start experiments by early 2026.<\/p>\n

Crucially, these experiments will not involve running quantum algorithms<\/a>, says Mercedes Gimeno-Segovia<\/a>, VP for system architecture<\/a>. Companies like Google<\/a> and IBM<\/a> have used smaller prototypes to demonstrate quantum supremacy<\/a> on toy problems, but Gimeno-Segovia says NISQ machines behave so differently from fault-tolerant ones that these kinds of experiments provide little insight. Instead, PsiQuantum\u2019s Alpha System is designed to test whether the behavior of the system matches the predictions made by the company\u2019s models, which will be crucial for designing future systems.<\/p>\n

\u201cWe\u2019re not trying to impress anybody, frankly,\u201d she adds. \u201cWhat we\u2019re trying to do is say, Do we understand the system that we\u2019re building? And the telltale fact that tells us whether we do or not, is whether we can predict this behavior.\u201d<\/p>\n

The trouble of flighty photons <\/p>\n

Simon Devitt<\/a>, research director at the Centre for Quantum Software and Information at the University of Technology, Sydney, thinks PsiQuantum\u2019s focus on skipping the NISQ regime and jumping straight to full fault tolerance is a good approach. But he points out that the company had little choice.<\/p>\n

PsiQuantum\u2019s system relies on linear optics<\/a>, where photon generation is inherently nondeterministic, says Devitt, which means gate operations fail roughly 25 to 50 percent of the time. PsiQuantum has come up with clever ways to reduce this number by running many photon-generation attempts and then picking out successful ones, something known as multiplexing. But this only partly solves the problem, and remaining gate failures must be dealt with by error correction.<\/p>\n

\"Work The inside of PsiQuantum\u2019s new facility in Milpitas, Calif.Colby Macri\/PsiQuantum<\/p>\n

This means it\u2019s essentially impossible to run quantum algorithms on the hardware until fault tolerance is achieved, says Devitt. More importantly, he adds, it means a huge amount of the error-correction budget is used up fixing these gate failures. This leaves little leeway for other sources of error, such as detector inefficiencies or optical losses from coupling chips to fiber.<\/p>\n

\u201cPhotons are extremely easy to lose,\u201d says Devitt. \u201cSo that\u2019s really where a lot of the questions arise, as to whether or not they can get their devices working to the required accuracies so that they don\u2019t overwhelm the error correction.\u201d<\/p>\n

Optical loss is the biggest source of errors in PsiQuantum\u2019s system after gate errors, says Devitt. Efforts to reduce this hinge on three key components\u2014waveguides, photon detectors, and optical switches. Based on the data published in the company\u2019s recent Nature paper or shared on <\/a>X<\/a>, he says the first two appear ready, but losses on the company\u2019s switches are still too high. \u201cThe question is, is it a material-science limitation they\u2019re hitting?\u201d he adds. \u201cOr is it just about purity and fabrication?\u201d<\/p>\n

Shadbolt is confident it\u2019s the latter. He sees no major hurdles; instead, it\u2019s going to take thousands of small, incremental improvements to the design and geometry of the chips, alongside tweaks to the fabrication process. Optical loss is heavily impacted by the precision with which you can build components, Shadbolt adds, so being able to lean on Global Foundries\u2019 world-leading tools and processes gives them a major advantage.<\/p>\n

\u201cIt\u2019s very challenging to make these components with good enough performance, but we have a great track record of improving performance,\u201d he says. \u201cWe know the steps that we\u2019re going to take to close the remaining gap, and we have high confidence in our ability to do that.\u201d<\/p>\n

Paul Smith-Goodson<\/a>, principal analyst at Moor Insights & Strategy, thinks PsiQuantum has a realistic chance of meeting its lofty goals. While it still has a way to go in cutting losses, and a huge job ahead when it comes to integrating all these components at scale, he thinks the company is on track.<\/p>\n

For him, the bigger challenge may be financial rather than technical. Despite the massive sums the company has raised, this will cover only a few prototypes, and they will need to raise significantly more to build a full-scale machine. \u201cIt takes a lot of money to do what they\u2019re doing,\u201d he says.<\/p>\n

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