Running complicated algorithms on quantum computing hardware is going to require the use of logical qubits, where collections of hardware qubits are linked together in ways that allow errors to be detected and corrected. In general, the more hardware qubits you dedicate to each logical qubit, the better the chances are of identifying errors. But, given that the hardware qubits are prone to errors, adding more of them also increases the probability that errors will occur. If the hardware error rate is too high, then growing the logical qubit will only make matters worse.
Fortunately, several companies have demonstrated hardware where the error rate is not too high. Several demonstrations show logical qubits are beyond the breakeven point, where adding more qubits improves performance. The problem is that the improvement isn't very dramatic. To lower error rates to levels we'll need to run complex algorithms, we'd have to add a completely impractical number of qubits to each logical qubit.
On Monday, Quantinuum announced that its current generation of hardware is capable of scaling well beyond the breakeven point. Each step up in the size of logical qubits improved some measures of their performance by a factor of over 10.
ORCA launched its PT-3 photonic quantum computer at a Digital Realty lab in London. See what its 20% and 12x benchmarks measure and what they leave out.
Google Willow cuts magic-state errors 40x and reaches 99.99% fidelity, easing a costly bottleneck in efforts to build fault-tolerant quantum computers.
Cloudflare said Tuesday it plans to issue quantum-proof TLS certificates, making it one of the first authorities to issue such certificates, which use a form of cryptography that is widely believed to withstand attacks from quantum computers.
The Internet infrastructure provider said it will use an open source platform that issues both classic TLS certificates and a post-quantum equivalent known as Merkle Tree Certificates. The hybrid certificates will be free to both paying and non-paying users. To help build the massive system and establish ubiquity across the sprawling TLS ecosystem, Cloudflare will be acquiring an already trusted certificate root from CA GlobalSign. Cloudflare said the move will let millions of websites use post-quantum certificates at the flip of a switch and without incurring any increased performance overhead.
Fundamental architectural changes ahead
Cloudflare’s plans are part of a major overhaul in the web public key infrastructure (WebPKI) required to make website encryption and authentication safe for the coming post-quantum age. A major challenge is using quantum-proof signatures that can be easily transmitted during web requests and recorded in transparency logs to ensure counterfeit certificates aren't assigned to websites. The makeover will take years to complete, because it requires the work of an untold number of engineers who design operating systems, browsers, certificate authorities, and Internet infrastructure.
Researchers have developed a new type of interconnected architecture for quantum computing chips, and it could pave the way for machines capable of large-scale processing, including those with over a million qubits.
In a study published June 15 in the journal APL Quantum, scientists aimed to resolve a huge problem with the leading quantum processing units (QPUs): Qubits struggle to communicate and share quantum information with each other if they aren't immediate neighbors.
That's why the scientists pioneered Quantum Phononic Links (QPLs) — an approach for long-range coupling between qubits that leans on phonons — quasiparticles that carry vibration energy — to convey information. By contrast, conventional methods, like surface acoustic waves — high-frequency sound vibrations — demand complex designs and extra hardware.
"One of the key challenges in quantum computing is long-range qubit connectivity," Maksym Myronov, an associate professor of semiconductor materials and devices at the University of Warwick in the U.K. and first author of the study, said in a statement. "Our work introduces a new concept in which phonons act as a quantum bus, enabling distant qubits to exchange quantum information while remaining fully compatible with semiconductor technology."
In the study, the scientists said the most promising way to achieve a quantum computer that's capable of large-scale processing and takes advantage of QPLs would be a qubit modality known as "semiconductor hole spin qubits."
A "hole" here refers to the absence of an electron in a material, but it can act like a particle and have a spin state — a property used to encode quantum information — where the 1s and 0s of data would be represented by the direction of the particle's spin state.
To demonstrate this technology, they created a prototype QPU consisting of silicon with a thin germanium crystal layer, a specialized material they called compressively strained germanium on silicon (cs-GoS). Germanium is an especially useful material for quantum computing, the scientists said, as it has natural properties that reduce decoherence — the loss of quantum information due to external interference.
Hole spin qubits combine long quantum coherence times — how long they can retain quantum information — with the ability to communicate using electron impulses in control systems. But they struggle to form bonds and share quantum information with qubits they don't directly neighbor. In any large-scale system, for instance, enabling this "quantum coupling" between distant qubits is essential for quantum error correction techniques to work effectively across the breadth of a massive system, the scientists said.
Other proposed long-range communications approaches, such as "charge shunting" — redirecting capacitors to reduce sensitivity to charge noise, or surface acoustic waves — have fundamental limitations regarding scalability, both in terms of their size and in maintaining coherence. That's where QPLs come in.
QPLs are engineered phononic waveguides and cavities that both confine and guide acoustic modes within a compressively strained germanium "quantum well," where a quantum well is an ultrathin layer that acts as a guide.
In the study, the researchers focused on qubits using valence-band holes — the absence of electrons at absolute zero — hosted using cs-GoS. With QPLs, the scientists sent sound-like vibrations through the specialized material to carry quantum information between the distant qubits.
Spin states in this material are highly sensitive to lattice deformations, which enable precise control and the coupling of spin states with vibrational energy. Essentially, this allows the spin state to be distinguishable from its electron counterpart, enabling the phononic coupling strategies. The technique they adopted permitted direct coupling between the phonons and the hole spins.
By using a slow wave velocity (the speed of a quantum particle) and a short wavelength for acoustic excitations, the scientists used QPLs to link qubits separated by less than a micrometer (one-thousandth of a millimeter) and those up to 300 mm (11.8 inches) apart.
QPLs are not only promising for quantum computing, the scientists pointed out in the study. By utilizing phonons as the connections, this technique offers a versatile interface for hybrid quantum systems — conventional computers with quantum computing functionality. This could enable coherent interconnection of semiconductor spin qubits with other quantum platforms, such as cloud-based quantum computing.
The combination of phononic engineering and hole-spin physics makes cs-GoS a promising platform for next-generation quantum architectures, they added, since it could achieve both long-range coherent coupling and large-scale integration.
Can you match these ancient devices to their pictures? Find out with our computing quiz!
Researchers have directly observed the optical Magnus effect for the first time, revealing a tiny shift in laser interactions that could affect the precise control of qubits in quantum computers. Anyone who has watched a spinning soccer ball curve around a defensive wall has seen what happens when spin changes an object’s path through the [...]
A new invention could significantly improve electron microscopy by integrating a small quantum computer directly into the microscope. For delicate samples such as individual proteins, electron microscopy faces a fundamental tradeoff. Producing a clearer image generally requires sending more electrons through the specimen, but increasing the dose also raises the risk of damaging the very [...]
NEC was one of the first developers of quantum computers back in the 1990s, but it is now among the first companies that originally researched quantum computing technologies to quit development of quantum computing hardware, according to a Diamond Online report. However, the company will continue to investigate practical applications for quantum computers.
NEC has been involved in superconducting quantum computing research since the technology's earliest days. In 1999, NEC researchers demonstrated the world's first superconducting solid-state qubit, which became a foundation of superconducting quantum computing. Variations of this technology are now being used by Google and IBM to build their quantum computers. However, it turns out that the Japanese technology giant quietly ended development of physical quantum computing machines in March 2026, and many of its researchers subsequently moved to rival Fujitsu.
Despite its historical role, NEC has apparently concluded that developing commercial quantum computing hardware will take too long to generate adequate returns. As a result, the company quietly discontinued development of quantum computing machines at the end of March, according to Diamond. A number of researchers involved with the program — reportedly including a key research leader — have since moved to Fujitsu, which continues to invest heavily in superconducting quantum computing hardware.
Meanwhile, NEC does not formally characterize the move as a withdrawal from quantum computing. In response to Diamond, the company declined to comment on whether it had exited quantum computer development and said that it continues to evaluate practical applications and industrialization of quantum technologies as well as conduct proof-of-concept projects with customers. Therefore, the move appears to represent an exit from development of actual quantum computers rather than from quantum technology altogether. NEC can continue working on quantum applications, software, algorithms, and customer projects without assuming the cost and risks associated with designing and building quantum processors and complete quantum computing systems.
NEC's withdrawal is particularly notable because virtually none of the major corporate laboratories that pioneered quantum computing in the 1990s and remain intact today have completely abandoned quantum-computer hardware. IBM, the other major corporate participant in some of the earliest experimental quantum computers, has instead become one of the industry’s largest developers of quantum computing systems.
NEC is no stranger to leaving businesses that have significant prospects ahead but require massive capital investments immediately. In 1990, NEC ranked No. 1 globally in semiconductor sales, ahead of Toshiba, Hitachi, Motorola, Intel, and Fujitsu. Intel subsequently overtook NEC during the 1990s as the PC microprocessor market exploded, but in 1990, NEC was significantly ahead. So, NEC's 1999 superconducting-qubit breakthrough did not come out of nowhere, but from a company with a huge semiconductor R&D organization and deep expertise in solid-state devices. By then, NEC was no longer the No. 1 semiconductor supplier, but it remained one of the world's major semiconductor companies.
The demise of NEC's semiconductor business was not sudden. NEC dismantled its semiconductor business in stages over roughly a decade. NEC effectively gave up doing DRAM alone in 1999, when it spun off its DRAM operations into NEC-Hitachi Memory, which was named Elpida. In November 2002, NEC spun its remaining semiconductor operation — MCUs, system LSIs/SoCs and other devices — into a separate company called NEC Electronics and later renamed Renesas Electronics.
Now, NEC is reportedly stepping away from quantum computer hardware as its commercialization remains distant, but development costs continue to mount. Furthermore, given NEC's current business focus — IT services, enterprise systems, aerospace and defense, telecom infrastructure, and AI and security — quantum computers are not exactly a natural fit.
Qubits are delicate and often misbehave. A qubit’s advantage over an ordinary bit is that in addition to “0” or “1”, it can hold values of 0 and 1 at once, in a specific combination; that combination is what quantum algorithms actually run on. But any stray interaction with the surrounding world (a vibration, a stray field, a single errant photon) leaks out a bit of information about which state the qubit is in – and that’s enough to collapse the combination back into an ordinary, classical either/or state. Coupling to the environment leads to high decoherence, meaning high error rates, and is normally how we lose good quality qubits. As such, most of the engineering effort in quantum computing goes into avoiding this coupling.
Yet recently, a team at the Institute of Science and Technology Austria (ISTA), working with collaborators in Munich and Madrid, has defied this norm.
Writing in Physical Review X, Alejandro Andrés-Juanes, Johannes Fink and colleagues show that two superconducting transmon qubits, separated by a metre of coaxial cable, can settle into an entangled state by being exposed to the same quantum-correlated microwave field. Avoiding synchronized pulses, heralding, post-selection and feedback (techniques usually used to actively generate and verify entanglement, rather than to fix decoherence), the entanglement can be generated and maintained for as long as the field is on. In other words, the researchers have managed to exploit noise to generate entanglement, rather than losing their qubits to it.
This idea of entangling by using fields belongs to a family of techniques known as dissipation engineering. “The common understanding is that the environment is bad, and it will decohere your qubits,” Andrés-Juanes tells Physics World. “The main idea [here] is that one can engineer a specific interaction with the environment that is not detrimental but – like in this case – prepares your qubits in an interesting state without you having to actively apply any action on the system.”
The correlated environment comes from a superconducting device (a Josephson parametric converter) that splits each pump photon into a pair of photons at gigahertz frequencies. The two photons of this pair are entangled with one another and each is sent down its own coaxial cable to one of the qubits, half a metre away in either direction.
Because the noise reaching the two qubits is correlated, relaxing into it does not scramble them (specifically, it does not wash out the fixed phase relationship between them, as independent noise on each qubit would). They settle instead into a superposition, for which absorbing a photon from the field and emitting one into it interfere destructively: “the destructive interference between a photon emission event in the first waveguide and a photon absorption process at the location of the second qubit,” as the authors explain.
Once there, the qubits stop evolving and the field passes through unchanged: the entangled state is dark, invisible to the very field that created it. What the experiment does, in effect, is convert the continuous-variable (CV) entanglement carried by the two microwave beams into ordinary entanglement between two conventional transmon qubits – “we obtain qubit entanglement from CV entanglement,” Andrés-Juanes confirms – with roughly a tenth of it inherited.
Most entanglement-distribution schemes deliver entanglement as events: a pulse sequence runs, a detector clicks, a pair is announced, and the state then decays until the sequence runs again. The author’s autonomous version could enable the elimination of this machinery.
“It removes a lot of overhead on the pulse sequences you need to run to get the entanglement,” says Andrés-Juanes, an advantage that’s expected to matter most at scale, since one correlated photon source can drive many pairs at once. “Another differential feature of this protocol is that the entanglement is ‘always on’ for when you need to use it. In active protocols, you would have to reinitialize the entangled state because it would decohere after a while.”
The practical limit of this setup is temperature: “We use microwave frequencies, which are only quantum at very low temperatures,” Andrés-Juanes explains. “The real limit in the separation is how big your dilution refrigerator is”, with the longest such link so far being 30 m, at ETH Zurich. He positions the work as an intermediate-distance technology rather than a long-distance one. At optical frequencies, the constraint would lift, though achieving the same strong qubit–waveguide coupling in an atomic system would be its own problem.
For now, the numbers are modest: two qubits, entangled with a concurrence of just 0.10 (on a scale where 1 is a perfect pair), inheriting only about a tenth of the entanglement carried by the microwave beams. The group is working on a module with more than one qubit per node.
But critically, the idea is no longer theoretical. The team has now realised an entangled link that is always “there”, bringing us one step closer to distributed quantum computing (linking separate processors into one machine via entanglement), networked sensing (detectors sharing entanglement to jointly see what none could alone) and quantum repeaters (relay stations for long-distance quantum links, needed because a quantum state can’t be copied and amplified like a classical signal).
Researchers at the Flatiron Institute in New York City have used a new tensor network (TN) scheme to simulate how Ising spin glasses evolve in time. In many cases, their classical method is more accurate than the latest quantum annealers running the same problem. The results scale in two and three dimensions and raise the bar in the ongoing competition between classical and quantum computers for simulating many-particle quantum systems.
Classical versus quantum
Quantum many-particle systems provide a good way of comparing computational techniques because their complexity grows exponentially with the number of particles. In theory, quantum computers hold an advantage rooted in entanglement and superposition. In a classical computer, the spin of a particle (up or down) is encoded in bit that is either zero (down) or one (up), but never both. In a quantum computer, the spin can be encoded in a qubit holding a quantum superposition of up and down. This is a much more natural way to represent what the simulated system is actually doing.
Recently, a team of quantum computing researchers used the D-Wave’s Advantage2 quantum annealer to simulate Ising spin glass dynamics and claimed that classical computers could not match their results. But now, Joseph Tindall and colleagues at the Flatiron Institute have shown that a classical scheme can do just as well -and sometimes better- than the annealer.
In this occasion, the competition involved the simulation of the Ising spin glass model, which describes spins on a lattice pointing in random directions. This disordered state is product of different nearest-neighbor interactions for different pairs of spins. The difficulty of this famous problem grows with the system size, which makes it a good benchmark for comparing classical and quantum performance.
Tensor networks
The tensors used by Tindall and colleagues can be thought of as LEGO pieces. Just as LEGO bricks have knobs and tubes that snap together to build a bigger array, tensors have legs (bond indices) that join through a process called contraction to form networks. In a many-particle simulation, each tensor represents a site along with its physical attributes: for instance, the type of particle it hosts, which could be a spin or an electron. Connected together, the tensors form a network that encodes how those particles interact and how entangled they are. Widening the legs (increasing the bond dimension in technical terms), allows the network to capture the correlations more accurately.
In simple terms, the pattern of connections describes how particles can move or interact, and what Tindall and colleagues built is a tensor network representation of both the Ising spin glass Hamiltonian and wave function. The first specifies the interactions between spins and the second describes the state of spins. Writing quantum states this way has proved enormously useful for accessing large systems, where the sheer number of particles rules out any exact solution.
Tindall’s group used these tensor network ideas to simulate the spin glass model’s dynamics. But there is a catch: as a TN wave function evolves forward in time, entanglement builds up between different parts of the system and the bond indices must widen to keep track of the growing correlations. This increases the computational cost of finding the ground state of the system at different times, making it more difficult and sometimes impossible.
Belief propagation
To compensate for this, the team used a belief propagation (BP) message passing approach to perform the contraction. In this scheme, each tensor receives a compact summary of what the rest of the network “looks like” from its perspective (the effective environment of each tensor). This unlike the conventional approach of accounting for every single contribution exactly. As Tindall points out, their approach can be understood as a mean field approximation on each tensor’s environment since the pieces of information reaching a particular given tensor from each of its neighbours are assumed to be independent.
By implementing this TN–BP approach, their classical implementation could evolve the system to much longer times than conventional TN schemes and manage far enough to reach the regime the quantum annealer operates. Conceptually, passing messages about an effective environment lets the computation to keep pace with the entanglement inherent to the system’s time evolution. The researchers then measured how the spin at one site relates to the spin elsewhere on the lattice (the two-point correlator) at various times and system sizes on two and three-dimensional lattices with cylindrical, diamond and cubic geometries.
Starting with a cylindrical lattice, the team compared the error in the two-point correlator error from the annealer with that from the TN-BP message passing approach. Once the bond dimension was large enough, the classical error was markedly lower error than the quantum counterpart at different annealing. On the diamond lattice, the classical error obtained again came in below the annealer’s, while on the cubic lattice the error was of the same order at a fixed annealing time.
What comes next
This work, which is described in Science, shows how fast classical simulation of quantum physics is advancing and how the on-going competition between classical and quantum computation is driving this progress. In the future, Tindall and colleagues want to apply the TB-BP to interacting electronic systems such the Hubbard model. Additionally, the group is also extending their scheme to finite temperature problems as well as maintaining their open-source tensor network quantum simulator library.
Step by step: A simplified schematic of the simulation framework, showing how circuit-level Pauli errors in noisy magic-state preparation protocols can be propagated and simplified using the underlying algebraic structure, reducing the problem to efficiently simulable logical Clifford errors acting on the output magic state. (Courtesy: Yousra Farhani)
Building a useful quantum computer is not simply a matter of adding more qubits. The greater challenge is making these qubits reliable enough to perform long computations without errors overwhelming the result. Quantum error correction addresses this problem by encoding each logical qubit across many physical ones, but it comes at a cost: many of the operations required for a general-purpose or “universal” quantum computer become highly resource intensive once fault-tolerant error correction is introduced.
To address this resource challenge, researchers at the University of California, Davis, US have developed a classical simulation method that efficiently models the preparation of some of the most demanding quantum states. The method, which they describe in PRX Quantum, works even for large, high-fidelity protocols that were previously beyond reach.
Building a universal quantum computer
Logical operations in fault-tolerant (that is, error-corrected) quantum computing architectures fall into two broad categories. The first category is a set of operations known as Clifford gates that are relatively straightforward to implement and, importantly, can be simulated efficiently on a classical computer. By themselves, however, Clifford gates are not computationally universal. For that, you also need non-Clifford operations, which lie outside the set of classically-simulable gates and provide the missing ingredient for universal quantum computation.
To realize these non-Clifford operations in a fault-tolerant way, some qubits need to be in a special state known as a magic state. Preparing these magic states with sufficiently high fidelity is expected to dominate the cost of large-scale error-corrected quantum computers, so quantum computing theorists are searching intensively for more efficient preparation protocols. The problem is that this search contains a challenge of its own: how can we compare the efficiency of these approaches?
To assess a magic-state preparation protocol, we need to simulate it under realistic levels of error-inducing circuit-level noise. Yet the same non-Clifford operations that make magic states indispensable for quantum computation also make them difficult to simulate. Existing methods therefore become prohibitively expensive as protocols grow, limiting exact simulations to relatively small logical circuits.
Simplifying a difficult simulation
Rather than searching for a more efficient simulation algorithm directly, the UC Davis team of Samyak Surti, Lucas Daguerre and Isaac Kim first asked a more fundamental question: what mathematical structure do these protocols share?
Their framework for answering this question encompasses three broad classes of logical magic-state preparation protocols: code switching, magic state distillation, and Pauli-square-root Clifford (PSC) measurement-based protocols. In the first two classes, error propagation is relatively straightforward to analyse, but PSC protocols require a more sophisticated mathematical treatment. Rather than viewing these protocols simply as quantum circuits, Surti, Daguerre and Kim characterized their underlying algebraic structure, showing that Pauli errors (the fundamental types of qubit errors) propagate in a highly constrained and predictable way under sequential commutation. This commutation preserves the algebraic relationships between errors and logical operators, while anti-commuting operations exhibit predictable transformations rather than generating uncontrolled complexity.
These properties mean that commuting operations can be systematically reordered without changing the outcome, allowing much of the circuit’s complexity to be absorbed into its algebraic structure. Hence, rather than tracking an exponentially large quantum state, the simulator follows how a compact description of logical Pauli and Clifford errors evolves through the protocol.
The paper formalizes these ideas through a sequence of lemmas, propositions and theorems that establish the mathematical properties of PSC protocols. The result is a series of algorithms for simulating realistic, noisy, logical magic-state preparation protocols with a computational cost that scales polynomially with both the number of qubits and what is termed the stabilizer rank of the target magic state, which is a measure of its non-Clifford complexity. Since the standard single-qubit magic state has a stabilizer rank of only two, this complexity remains manageable even as the underlying error-correcting code grows, in marked contrast to state vector simulations that scale exponentially with qubit number. The team’s advance therefore makes large-scale logical simulations practical for the first time.
Accelerating fault-tolerant quantum computing
Although the new framework does not reduce the physical resources required to prepare logical magic states, it does change how those protocols can be analysed and designed. By exposing the algebraic structure underlying a broad class of logical magic-state preparation schemes, the UC Davis team transformed a computationally hard problem into one that admits efficient classical simulation. Researchers can therefore evaluate, compare and refine candidate preparation protocols under realistic circuit-level noise without resorting to exponentially expensive simulations or uncontrolled approximations.
“The main motivation behind our work was to speed up the development of fault-tolerant quantum computer,” Kim tells Physics World. “I believe there is a large amount of uncertainty in how we will design and optimize magic state factories, which will likely remain as a bottleneck in the foreseeable future.”
As quantum computing progresses from proof-of-principle demonstrations to large-scale fault-tolerant architectures, the ability to characterize and benchmark logical operations efficiently will become increasingly important. This work offers more than just a faster simulator; instead, it provides a new theoretical foundation for designing one of the most resource-intensive building blocks of future quantum computers. “My hope is that this line of work can help us better design the fault-tolerant quantum computers we will be getting over the next few years,” Kim says.
This episode of the Physics World Weekly podcast features Yonatan Cohen, who is co-founder and chief technology officer of Quantum Machines.
The company was started in 2018 by three physicists from Israel’s Weizmann Institute. It develops control systems for quantum computers and has about 300 employees and 500 customers worldwide.
Cohen explains why hybrid quantum–classical control systems are increasing in importance as quantum computers scale-up to include more and more qubits. He also talks about Quantum Machines’ strategy to support a wide range of qubit types – including superconducting circuits, trapped ions, neutral atoms, spins and NV centres.
We chat about some of the company’s products and its collaborations with quantum-technology companies including Rigetti Computing and Diraq. Cohen also gives career advice for physicists who want to work in the quantum sector.
A German startup has debuted the world's first diamond-based quantum computing system to exceed 10 qubits.
The machine, built by engineers at Saxon Q, is a nitrogen-vacancy (NV) quantum computer, meaning it uses defects in synthetic diamonds as quantum bits (qubits) to perform quantum operations. Qubits can be manipulated to represent the 0s and 1s of data, as well as quantum states that are superpositions of both the 0s and the 1s.
The hardware is currently available in rack-mounted systems featuring up to 128 qubits, with 512-qubit configurations available for delivery next year. According to the company's road map, the goal is to scale to 10,000 qubits and beyond after 2030.
Although the technology existed before this debut, scientists have found it difficult to build systems beyond 10 qubits due to the difficulty of creating nitrogen vacancy qubits.
Although Live Science saw a technical white paper outlining how the technology works, there didn't appear to be any published research demonstrating a functional quantum computer based on the NV architecture operating with more than 10 qubits before this launch. It's still unclear exactly how well the firm's quantum computers stack up against other platforms.
Quantum mechanics and flawed diamonds
In the 1970s, scientists discovered that certain diamonds shone with a brilliant red light when illuminated in a specific way. Subsequent research determined that the optical shift was caused by annealing radiation damage that attracted isolated substitutional nitrogen atoms. In other words, nature occasionally produces a diamond that has a nitrogen atom where a carbon atom should be.
The unintegrated nitrogen atoms are drawn to the vacancy in the otherwise perfectly ordered carbon atoms inside the diamond. Although these flawed diamonds occur rarely in nature, scientists can create diamonds with nitrogen vacancies in laboratories.
Functionally, the single nitrogen atoms inside the vacancies act as if they were "trapped," and their electrons can "spin" independently of the electrons inside the surrounding carbon atoms.
Scientists exploit this "spin" feature by using special lasers to put the nitrogen atom's electrons in a specific state they measure as "zero." They can then use microwave pulses to precisely manipulate the electrons into numerous configurations, including quantum states that binary "bits" can't achieve.
We have a fully functioning quantum computer.
Marius Grundmann, professor of experimental physics at Leipzig University and co-founder of Saxon Q,
Marius Grundmann, a professor of experimental physics at Leipzig University and co-founder of Saxon Q, said the breakthrough that allowed his firm to push past the 10-qubit barrier was a materials discovery.
When the Saxon Q team creates the vacancy inside its lab-grown diamonds, they co-implant sulfur. Per Grundman, “That's the key technology point. Because the sulfur lifts the chemical potential to a point that it's negatively charged. The sulfur supplies the electron; the sulfur also makes the vacancy attached to the nitrogen with a very high yield."
In other words, by co-implanting sulfur atoms, the Saxon Q researchers can express greater control over the individual qubits. Once the qubits are set with lasers and subjected to microwave pulses, they're ready for error correction. In a statement, Saxon Q representatives said the qubits achieved a 99.92% fidelity rate — fewer than one error per 1,000 operations — before error correction.
However, Grundmann told Live Science that the latest numbers as of July 22 showed 99.98% fidelity in single-qubit operations. That's comparable to state-of-the-art error correction results reported by other quantum computing labs, such as those from IBM and MIT, although it wasn't possible to independently verify the results.
Room-temperature quantum computing
It's difficult to compare Saxon Q's diamond-based NV systems with more established quantum computing platforms, such as superconducting qubits. Most recent research on NV systems has focused on quantum sensing applications, though at least one preprint study discusses hybrid NV/superconducting systems.
"We have a fully functioning quantum computer," Grundmann told Live Science. According to Grundmann, the company's quantum computers are on a par with those using other modalities. "We have a quantum computer that can execute quantum code that you can reach via the network, and it is a multiuser, multitasking, multicore system," he said.
If the Saxon Q systems ultimately prove comparable to existing solid-state quantum computing architectures, they'd be among the first generation of room-temperature quantum computers to reach performance similar to systems that require cryogenics and on-site monitoring.
The ease of setup is notable. Saxon Q's devices can be slotted into a standard computer rack and plugged directly into alternating-current power.
This provides a clear near-term advantage for clients who want to run algorithms on a quantum system without operating through the cloud. Grundmann said this could be especially important in edge computing scenarios, such as autonomous driving or robotics, where cloud communication could produce unacceptable latency.
Research comparing solid-state quantum systems indicates that superconducting quantum computers would typically operate faster than diamond-based NV systems. It's unclear, however, what the trade-off between processing speed and cloud latency would be or whether it could be addressed through scaling.
The current challenge to scaling diamond-based NV quantum computers beyond the 512-qubit range is the size of the chips. Saxon Q's current chips are limited to supporting either eight or 16 qubits. For more powerful systems, scientists will need to squeeze hundreds — or even thousands — of qubits onto a single array to support operations requiring hundreds of thousands or millions of qubits.
Can you match these ancient devices to their pictures? Find out with our computing quiz!
D-Wave is a bit of an oddity in the quantum computing space, having been founded back in the last century. And its initial offering wasn't a quantum computer like those being developed by IBM or Google. Instead, the company built what's now called a quantum annealer, a machine that isn't general-purpose but can solve a large class of optimization problems. While the hardware shares some similarities with the qubits used in gate-based quantum computers, it operates in a fundamentally different way.
But a few years back, D-Wave started working on gate-based hardware, apparently choosing a somewhat unusual qubit technology called fluxonium. And this year, the company acquired a startup called Quantum Circuits that spun out of Yale University and has been developing what's called a dual-rail qubit (the same technology used by Amazon), which promises to make most errors very easy to detect, simplifying error correction.
On Wednesday, the company is publishing a paper in Nature that describes a key step in validating this dual-rail technology, showing that two of the qubits can be entangled without altering their best feature: Most are a single type that is easy to detect.
Researchers demonstrated that braiding and fusing particles known as non-Abelian anyons can perform every operation required by a quantum computer. A quantum computer becomes broadly useful only when it can perform any computation rather than a limited set of specialized tasks. Physicists have now demonstrated that unusual quantum objects called non-Abelian anyons can provide that [...]
Login
