The future of quantum communication and quantum computing technologies may well revolve around superconducting qubits and quantum circuits, which have already been shown to improve processing capabilities over classical supercomputers – even when there is noise within the system. This scenario could be one step closer with the development of a novel quantum transducer by a team headed up at the Harvard John A Paulson School of Engineering and Applied Sciences (SEAS).

Realising this future will rely on systems having hundreds (or more) logical qubits (each built from multiple physical qubits). However, because superconducting qubits require ultralow operating temperatures, large-scale refrigeration is a major challenge – there is no technology available today that can provide the cooling power to realise such large-scale qubit systems.

Superconducting microwave qubits are a promising option for quantum processor nodes, but they currently require bulky microwave components. These components create a lot of heat that can easily disrupt the refrigeration systems cooling the qubits.

One way to combat this cooling conundrum is to use a modular approach, with small-scale quantum processors connected via quantum links, and each processor having its own dilution refrigerator. Superconducting qubits can be accessed using microwave photons between 3 and 8 GHz, thus the quantum links could be used to transmit microwave signals. The downside of this approach is that it would require cryogenically cooled links between each subsystem.

On the other hand, optical signals at telecoms frequency (around 200 THz) can be generated using much smaller form factor components, leading to lower thermal loads and noise, and can be transmitted via low-loss optical fibres. The transduction of information between optical and microwave frequencies is therefore key to controlling superconducting microwave qubits without the high thermal cost.

The large energy gap between microwave and optical photons makes it difficult to control microwave qubits with optical signals and requires a microwave–optical quantum transducer (MOQT). These MOQTs provide a coherent, bidirectional link between microwave and optical frequencies while preserving the quantum states of the qubit. A team led by SEAS researcher Marko Lončar has now created such a device, describing it in Nature Physics.

Electro-optic transducer controls superconducting qubits

Lončar and collaborators have developed a thin-film lithium niobate (TFLN) cavity electro-optic (CEO)-based MOQT (clad with silica to aid thermal dissipation and mitigate optical losses) that converts optical frequencies into microwave frequencies with low loss. The team used the CEO-MOQT to facilitate coherent optical driving of a superconducting qubit (controlling the state of the quantum system by manipulating its energy).

The on-chip transducer system contains three resonators: a microwave LC resonator capacitively coupled to two optical resonators using the electro-optic effect. The device creates hybridized optical modes in the transducer that enables a resonance-enhanced exchange of energy between the microwave and optical modes.

The transducer uses a process known as difference frequency generation to create a new frequency output from two input frequencies. The optical modes – an optical pump in a classical red-pumping regime and an optical idler – interact to generate a microwave signal at the qubit frequency, in the form of a shaped, symmetric single microwave photon.

This microwave signal is then transmitted from the transducer to a superconducting qubit (in the same refrigerator system) using a coaxial cable. The qubit is coupled to a readout resonator that enables its state to be read by measuring the transmission of a readout pulse.

The MOQT operated with a peak conversion efficiency of 1.18% (in both microwave-to-optical and optical-to-microwave regimes), low microwave noise generation and the ability to drive Rabi oscillations in a superconducting qubit. Because of the low noise, the researchers state that stronger optical-pump fields could be used without affecting qubit performance.

Having effectively demonstrated the ability to control superconducting circuits with optical light, the researchers suggest a number of future improvements that could increase the device performance by orders of magnitude. For example, microwave and optical coupling losses could be reduced by fabricating a single-ended microwave resonator directly onto the silicon wafer instead of on silica. A flux tuneable microwave cavity could increase the optical bandwidth of the transducer. Finally, the use of improved measurement methods could improve control of the qubits and allow for more intricate gate operations between qubit nodes.

The researchers suggest this type of device could be used for networking superconductor qubits when scaling up quantum systems. The combination of this work with other research on developing optical readouts for superconducting qubit chips “provides a path towards forming all-optical interfaces with superconducting qubits…to enable large scale quantum processors,” they conclude.

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Rapid technical innovation in quantum computing is expected to yield an array of hardware platforms that can run increasingly sophisticated algorithms. In the real world, however, such technical advances will remain little more than a curiosity if they are not adopted by businesses and the public sector to drive positive change. As a result, one key priority for the UK’s National Quantum Computing Centre (NQCC) has been to help companies and other organizations to gain an early understanding of the value that quantum computing can offer for improving performance and enhancing outcomes.

To meet that objective the NQCC has supported several feasibility studies that enable commercial organizations in the UK to work alongside quantum specialists to investigate specific use cases where quantum computing could have a significant impact within their industry. One prime example is a project involving the high-street bank HSBC, which has been exploring the potential of quantum technologies for spotting the signs of fraud in financial transactions. Such fraudulent activity, which affects millions of people every year, now accounts for about 40% of all criminal offences in the UK and in 2023 generated total losses of more than £2.3 bn across all sectors of the economy.

Banks like HSBC currently exploit classical machine learning to detect fraudulent transactions, but these techniques require a large computational overhead to train the models and deliver accurate results. Quantum specialists at the bank have therefore been working with the NQCC, along with hardware provider Rigetti and the Quantum Software Lab at the University of Edinburgh, to investigate the capabilities of quantum machine learning (QML) for identifying the tell-tale indicators of fraud.

“HSBC’s involvement in this project has brought transactional fraud detection into the realm of cutting-edge technology, demonstrating our commitment to pushing the boundaries of quantum-inspired solutions for near-term benefit,” comments Philip Intallura, Group Head of Quantum Technologies at HSBC. “Our philosophy is to innovate today while preparing for the quantum advantage of tomorrow.”

Another study focused on a key problem in the aviation industry that has a direct impact on fuel consumption and the amount of carbon emissions produced during a flight. In this logistical challenge, the aim was to find the optimal way to load cargo containers onto a commercial aircraft. One motivation was to maximize the amount of cargo that can be carried, the other was to balance the weight of the cargo to reduce drag and improve fuel efficiency.

“Even a small shift in the centre of gravity can have a big effect,” explains Salvatore Sinno of technology solutions company Unisys, who worked on the project along with applications engineers at the NQCC and mathematicians at the University of Newcastle. “On a Boeing 747 a displacement of just 75 cm can increase the carbon emissions on a flight of 10,000 miles by four tonnes, and also increases the fuel costs for the airline company.”

With such a large number of possible loading combinations, classical computers cannot produce an exact solution for the optimal arrangement of cargo containers. In their project the team improved the precision of the solution by combining quantum annealing with high-performance computing, a hybrid approach that Unisys believes can offer immediate value for complex optimization problems. “We have reached the limit of what we can achieve with classical computing, and with this work we have shown the benefit of incorporating an element of quantum processing into our solution,” explains Sinno.

The HSBC project team also found that a hybrid quantum–classical solution could provide an immediate performance boost for detecting anomalous transactions. In this case, a quantum simulator running on a classical computer was used to run quantum algorithms for machine learning. “These simulators allow us to execute simple QML programmes, even though they can’t be run to the same level of complexity as we could achieve with a physical quantum processor,” explains Marco Paini, the project lead for Rigetti. “These simulations show the potential of these low-depth QML programmes for fraud detection in the near term.”

The team also simulated more complex QML approaches using a similar but smaller-scale problem, demonstrating a further improvement in performance. This outcome suggests that running deeper QML algorithms on a physical quantum processor could deliver an advantage for detecting anomalies in larger datasets, even though the hardware does not yet provide the performance needed to achieve reliable results. “This initiative not only showcases the near-term applicability of advanced fraud models, but it also equips us with the expertise to leverage QML methods as quantum computing scales,” comments Intellura.

Indeed, the results obtained so far have enabled the project partners to develop a roadmap that will guide their ongoing development work as the hardware matures. One key insight, for example, is that even a fault-tolerant quantum computer would struggle to process the huge financial datasets produced by a bank like HSBC, since a finite amount of time is needed to run the quantum calculation for each data point. “From the simulations we found that the hybrid quantum–classical solution produces more false positives than classical methods,” says Paini. “One approach we can explore would be to use the simulations to flag suspicious transactions and then run the deeper algorithms on a quantum processor to analyse the filtered results.”

This particular project also highlighted the need for agreed protocols to navigate the strict rules on data security within the banking sector. For this project the HSBC team was able to run the QML simulations on its existing computing infrastructure, avoiding the need to share sensitive financial data with external partners. In the longer term, however, banks will need reassurance that their customer information can be protected when processed using a quantum computer. Anticipating this need, the NQCC has already started to work with regulators such as the Financial Conduct Authority, which is exploring some of the key considerations around privacy and data security, with that initial work feeding into international initiatives that are starting to consider the regulatory frameworks for using quantum computing within the financial sector.

For the cargo-loading project, meanwhile, Sinno says that an important learning point has been the need to formulate the problem in a way that can be tackled by the current generation of quantum computers. In practical terms that means defining constraints that reduce the complexity of the problem, but that still reflect the requirements of the real-world scenario. “Working with the applications engineers at the NQCC has helped us to understand what is possible with today’s quantum hardware, and how to make the quantum algorithms more viable for our particular problem,” he says. “Participating in these studies is a great way to learn and has allowed us to start using these emerging quantum technologies without taking a huge risk.”

Indeed, one key feature of these feasibility studies is the opportunity they offer for different project partners to learn from each other. Each project includes an end-user organization with a deep knowledge of the problem, quantum specialists who understand the capabilities and limitations of present-day solutions, and academic experts who offer an insight into emerging theoretical approaches as well as methodologies for benchmarking the results. The domain knowledge provided by the end users is particularly important, says Paini, to guide ongoing development work within the quantum sector. “If we only focused on the hardware for the next few years, we might come up with a better technical solution but it might not address the right problem,” he says. “We need to know where quantum computing will be useful, and to find that convergence we need to develop the applications alongside the algorithms and the hardware.”

Another major outcome from these projects has been the ability to make new connections and identify opportunities for future collaborations. As a national facility NQCC has played an important role in providing networking opportunities that bring diverse stakeholders together, creating a community of end users and technology providers, and supporting project partners with an expert and independent view of emerging quantum technologies. The NQCC has also helped the project teams to share their results more widely, generating positive feedback from the wider community that has already sparked new ideas and interactions.

“We have been able to network with start-up companies and larger enterprise firms, and with the NQCC we are already working with them to develop some proof-of-concept projects,” says Sinno. “Having access to that wider network will be really important as we continue to develop our expertise and capability in quantum computing.”

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Physicists at the Georgia Institute of Technology, US have introduced a novel way to generate entanglement between photons – an essential step in building scalable quantum computers that use photons as quantum bits (qubits). Their research, published in Physical Review Letters, leverages a mathematical concept called non-Abelian quantum holonomy to entangle photons in a deterministic way without relying on strong nonlinear interactions or irrevocably probabilistic quantum measurements.

Entanglement is fundamental to quantum information science, distinguishing quantum mechanics from classical theories and serving as a pivotal resource for quantum technologies. Existing methods for entangling photons often suffer from inefficiencies, however, requiring additional particles such as atoms or quantum dots and additional steps such as post-selection that eliminate all outcomes of a quantum measurement in which a desired event does not occur.

While post-selection is a common strategy for entangling non-interacting quantum particles, protocols for entangled state preparation that use post-selection are non-deterministic. This is because they rely upon making measurements, and the result of obtaining a certain state of the system after a measurement is associated with a probability, making it inevitably non-deterministic.

Non-Abelian holonomy

The new approach provides a direct and deterministic alternative. In it, the entangled photons occupy distinguishable spatial modes of optical waveguides, making entanglement more practical for real-world applications. To develop it, Georgia Tech’s Aniruddha Bhattacharya and Chandra Raman took inspiration from a 2023 experiment by physicists at Universität Rostock, Germany, that involved coupled photonic waveguides on a fused silica chip. Both works exploit a property known as non-Abelian holonomy, which is essentially a geometric effect that occurs when a quantum system evolves along a closed path in parameter space (more precisely, it is a matrix-valued generalization of a pure geometric phase).

In Bhattacharya and Raman’s approach, photons evolve in a waveguide system where their quantum states undergo a controlled transformation that leads to entanglement. The pair derive an analytical expression for the holonomic transformation matrix, showing that the entangling operation corresponds to a unitary rotation within an effective pseudo-angular momentum space. Because this process is fully unitary, it does not require measurement or external interventions, making it inherently robust.

Beyond the Hong-Ou-Mandel effect

A classic example of photon entanglement is the Hong–Ou–Mandel (HOM) effect, where two identical photons interfere at a beam splitter, leading to quantum correlations between them. The new method extends such interference effects beyond two photons, allowing deterministic entanglement of multiple photons and even higher-dimensional quantum states known as qudits (d-level systems) instead of qubits (two-level systems). This could significantly improve the efficiency of quantum information protocols.

Because state preparation and measurement are relatively straightforward in this approach, Bhattacharya and Raman say it is well-suited for quantum computing. Since the method relies on geometric principles, it naturally protects against certain types of noise, making it more robust than traditional approaches. They add that their technique could even be used to construct an almost universal set of near-deterministic entangling gates for quantum computation with light. “This innovative use of non-Abelian holonomy could shift the way we think about photonic quantum computing,” they say.

By providing a deterministic and scalable entanglement mechanism, Bhattacharya and Raman add that their method opens the door to more efficient and reliable photonic quantum technologies. The next steps will be to validate the approach experimentally and explore practical implementations in quantum communication and computation. Further in the future, it will be necessary to find ways of integrating this approach with other quantum systems, such as matter-based qubits, to enable large-scale quantum networks.

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Researchers in the Netherlands, Austria, and France have created what they describe as the first operating system for networking quantum computers. Called QNodeOS, the system was developed by a team led by Stephanie Wehner at Delft University of Technology. The system has been tested using several different types of quantum processor and it could help boost the accessibility of quantum computing for people without an expert knowledge of the field.

In the 1960s, the development of early operating systems such as OS/360 and UNIX  represented a major leap forward in computing. By providing a level of abstraction in its user interface, an operating system enables users to program and run applications, without having to worry about how to reconfigure the transistors in the computer processors. This advance laid the groundwork for the many of the digital technologies that have revolutionized our lives.

“If you needed to directly program the chip installed in your computer in order to use it, modern information technologies would not exist,” Wehner explains. “As such, the ability to program and run applications without needing to know what the chip even is has been key in making networks like the Internet actually useful.”

Quantum and classical

The users of nascent quantum computers would also benefit from an operating system that allows quantum (and classical) computers to be connected in networks. Not least because most people are not familiar with the intricacies of quantum information processing.

However, quantum computers are fundamentally different from their classical counterparts, and this means a host of new challenges faces those developing network operating systems.

“These include the need to execute hybrid classical–quantum programs, merging high-level classical processing (such as sending messages over a network) with quantum operations (such as executing gates or generating entanglement),” Wehner explains.

Within these hybrid programs, quantum computing resources would only be used when specifically required. Otherwise, routine computations would be offloaded to classical systems, making it significantly easier for developers to program and run their applications.

No standardized architecture

In addition, Wehner’s team considered that, unlike the transistor circuits used in classical systems, quantum operations currently lack a standardized architecture – and can be carried out using many different types of qubits.

Wehner’s team addressed these design challenges by creating a QNodeOS, which is a hybridized network operating system. It combines classical and quantum “blocks”, that provide users with a platform for performing quantum operations.

“We implemented this architecture in a software system, and demonstrated that it can work with different types of quantum hardware,” Wehner explains. The qubit-types used by the team included the electronic spin states of nitrogen–vacancy defects in diamond and the energy levels of individual trapped ions.

Multi-tasking operation

“We also showed how QNodeOS can perform advanced functions such as multi-tasking. This involved the concurrent execution of several programs at once, including compilers and scheduling algorithms.”

QNodeOS is still a long way from having the same impact as UNIX and other early operating systems. However, Wehner’s team is confident that QNodeOS will accelerate the development of future quantum networks.

“It will allow for easier software development, including the ability to develop new applications for a quantum Internet,” she says. “This could open the door to a new area of quantum computer science research.”

The research is described in Nature.

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Dans le cas de la réalité augmentée, les utilisateurs pourront télécharger en 5G les maps 3D traitées en temps réel depuis des infrastructure Edge Computing. D’autre part, les informations associées à ces Maps 3D proviendront d’une source de données plus éloignée : le cloud.

L’article 5G et Technologies Immersives – Nokia / Laval Virtual 2019 est apparu en premier sur Réalité Augmentée - Augmented Reality.

Last week I had the pleasure of attending the Global Physics Summit (GPS) in Anaheim California, where I rubbed shoulders with 15,0000 fellow physicists. The best part of being there was chatting with lots of different people, and in this podcast I share two of those conversations.

First up is Chetan Nayak, who is a senior researcher at Microsoft’s Station Q quantum computing research centre here in California. In February, Nayak and colleagues claimed a breakthrough in the development of topological quantum bits (qubits) based on Majorana zero modes. In principle, such qubits could enable the development of practical quantum computers, but not all physicists were convinced, and the announcement remains controversial – despite further results presented by Nayak in a packed session at the GPS.

I caught up with Nayak after his talk and asked him about the challenges of achieving Microsoft’s goal of a superconductor-based topological qubit. That conversation is the first segment of today’s podcast.

Distinctive jumping technique

Up next, I chat with Atharva Lele about the physics of manu jumping, which is a competitive aquatic sport that originates from the Māori and Pasifika peoples of New Zealand. Jumpers are judged by the height of their splash when they enter the water, and the best competitors use a very distinctive technique.

Lele is an undergraduate student at the Georgia Institute of Technology in the US, and is part of team that analysed manu techniques in a series of clever experiments that included plunging robots. He explains how to make a winning manu jump while avoiding the pain of a belly flop.

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Researchers in China have unveiled a 105-qubit quantum processor that can solve in minutes a quantum computation problem that would take billions of years using the world’s most powerful classical supercomputers. The result sets a new benchmark for claims of so-called “quantum advantage”, though some previous claims have faded after classical algorithms improved.

The fundamental promise of quantum computation is that it will reduce the computational resources required to solve certain problems. More precisely, it promises to reduce the rate at which resource requirements grow as problems become more complex. Evidence that a quantum computer can solve a problem faster than a classical computer – quantum advantage – is therefore a key measure of success.

The first claim of quantum advantage came in 2019, when researchers at Google reported that their 53-qubit Sycamore processor had solved a problem known as random circuit sampling (RCS) in just 200 seconds. Xiaobu Zhu, a physicist at the University of Science and Technology of China (USTC) in Hefei who co-led the latest work, describes RCS as follows: “First, you initialize all the qubits, then you run them in single-qubit and two-qubit gates and finally you read them out,” he says. “Since this process includes every key element of quantum computing, such as initializing the gate operations and readout, unless you have really good fidelity at each step you cannot demonstrate quantum advantage.”

At the time, the Google team claimed that the best supercomputers would take 10::000 years to solve this problem. However, subsequent improvements to classical algorithms reduced this to less than 15 seconds. This pattern has continued ever since, with experimentalists pushing quantum computing forward even as information theorists make quantum advantage harder to achieve by improving techniques used to simulate quantum algorithms on classical computers.

Recent claims of quantum advantage

In October 2024, Google researchers announced that their 67-qubit Sycamore processor had solved an RCS problem that would take an estimated 3600 years for the Frontier supercomputer at the US’s Oak Ridge National Laboratory to complete. In the latest work, published in Physical Review Letters, Jian-Wei Pan, Zhu and colleagues set the bar even higher. They show that their new Zuchongzhi 3.0 processor can complete in minutes an RCS calculation that they estimate would take Frontier billions of years using the best classical algorithms currently available.

To achieve this, they redesigned the readout circuit of their earlier Zuchongzhi processor to improve its efficiency, modified the structures of the qubits to increase their coherence times and increased the total number of superconducting qubits to 105. “We really upgraded every aspect and some parts of it were redesigned,” Zhu says.

Google’s latest processor, Willow, also uses 105 superconducting qubits, and in December 2024 researchers there announced that they had used it to demonstrate quantum error correction. This achievement, together with complementary advances in Rydberg atom qubits from Harvard University’s Mikhail Lukin and colleagues, was named Physics World’s Breakthrough of the Year in 2024. However, Zhu notes that Google has not yet produced any peer-reviewed research on using Willow for RCS, making it hard to compare the two systems directly.

The USTC team now plans to demonstrate quantum error correction on Zuchongzhi 3.0. This will involve using an error correction code such as the surface code to combine multiple physical qubits into a single “logical qubit” that is robust to errors.  “The requirements for error-correction readout are much more difficult than for RCS,” Zhu notes. “RCS only needs one readout, whereas error-correction needs readout many times with very short readout times…Nevertheless, RCS can be a benchmark to show we have the tools to run the surface code. I hope that, in my lab, within a few months we can demonstrate a good-quality error correction code.”

“How progress gets made”

Quantum information theorist Bill Fefferman of the University of Chicago in the US praises the USTC team’s work, describing it as “how progress gets made”. However, he offers two caveats. The first is that recent demonstrations of quantum advantage do not have efficient classical verification schemes – meaning, in effect, that classical computers cannot check the quantum computer’s work. While the USTC researchers simulated a smaller problem on both classical and quantum computers and checked that the answers matched, Fefferman doesn’t think this is sufficient. “With the current experiments, at the moment you can’t simulate it efficiently, the verification doesn’t work anymore,” he says.

The second caveat is that the rigorous hardness arguments proving that the classical computational power needed to solve an RCS problem grows exponentially with the problem’s complexity apply only to situations with no noise. This is far from the case in today’s quantum computers, and Fefferman says this loophole has been exploited in many past quantum advantage experiments.

Still, he is upbeat about the field’s prospects. “The fact that the original estimates the experimentalists gave did not match some future algorithm’s performance is not a failure: I see that as progress on all fronts,” he says. “The theorists are learning more and more about how these systems work and improving their simulation algorithms and, based on that, the experimentalists are making their systems better and better.”

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