There are some obvious big picture issues that stand between us and useful quantum computing. Issues like whether we can make enough high-quality hardware qubits to connect into the error-corrected logical qubits we need, and how we generate the states needed to perform universal computation on those logical qubits. But there are also many less prominent challenges that will need to be solved before we can perform calculations.
One of those challenges, which only affects some types of hardware, is calibration. For devices we manufacture, like superconducting qubits, there are always subtle variations among individual qubits. (This is not true when we use something like an atom to hold the qubit, but the lasers that control them can drift.) As a result, this hardware is put through a process called calibration, where we test different frequencies and amplitudes of the microwave pulses that control them to find the combination that produces the lowest error rates, and then save those settings for use in calculations.
However, you can't perform the typical calibration process while you're doing calculations, which means drift becomes an issue for long and complicated algorithms. Google, though, has figured out that it's possible to do calibration using the same data that's used for error correction.
Using a quantum computer alongside a supercomputer, scientists have developed a breakthrough pathway for modeling the physics inside a fusion reactor. The world-first experiment could help clear a path to developing clean, abundant nuclear power and solving the global energy crisis, the researchers said.
Using hybrid quantum computing and artificial intelligence (AI) methods, scientists with IBM and Oak Ridge National Laboratory (ORNL) have blueprinted how to make tritium, an extremely rare isotope of hydrogen that's critical to the fusion process.
Although their research — uploaded June 29 to the preprint server arXiv — has not been peer-reviewed, the researchers say it's the first time that different kinds of computing elements have come together to propose the most effective way to create this material.
Fusion reactors are experimental power sources that create energy by fusing atomic nuclei. The heat produced in the subsequent nuclear reaction is then harnessed as energy. This method produces no carbon byproducts or long-lived radioactive waste, making it one of the cleanest potential forms of mass energy production.
It's projected that, at scale, a single fusion reactor could produce about 4 million times as much energy as a coal-burning facility and around four times the amount of energy as a modern nuclear fission reactor.
Current attempts at building a viable fusion reactor have resulted in numerous laboratory experiments that prove the technology works, with magnetic confinement reactors, such as tokamaks, widely considered the front-runner. But many engineering challenges remain before the first commercial reactors could come online.
Turning seawater into fuel
The base fuel for nuclear fusion reactors is a hydrogen isotope called deuterium, which is commonly found in seawater. It's estimated that there are 33 grams of deuterium in every cubic meter of seawater.
But deuterium is only half of the equation. Nuclear fusion also requires tritium — a heavier hydrogen isotope — and the fusion released from just 1 gram (0.04 ounces) of deuterium-tritium fuel equals the energy from about 2,400 gallons (9,100 liters) of oil, according to the U.S. Department of Energy.
Unfortunately, tritium, a radioactive isotope, is extremely rare; only 44 pounds (20 kilograms) of it is produced on Earth each year, and its 12-year half-life makes it difficult to use in nuclear power plants.
Instead, scientists must painstakingly produce tritium in nuclear reactors by bombarding lithium atoms with neutrons. It's then superheated and bound with powerful magnets into a whirling ring of plasma within a tokamak, a special fusion chamber designed to shape and heat plasma using magnetic fields.
A diagram showing the process of nuclear fusion. (Image credit: Designua | Shutterstock)
Scientists add more deuterium and then bash the tritium and deuterium together, causing them to fuse into helium. The force of this reaction creates heat that's converted into energy.
The current bottleneck lies in creating enough tritium to sustain fusion long enough to produce energy. But modeling the particle physics and chemical reactions involved in the tritium-creation process has proved beyond the capabilities of classical supercomputers.
In the new study, however, scientists say they have addressed this bottleneck by simulating nine molecular configurations of a liquid salt that contains fluorine, lithium and beryllium (FLiBe) — one of the leading candidate materials for extracting tritium.
This is the first time quantum computers have been used to model reactions inside a fusion reactor. If perfected, FLiBe could provide a near-limitless source of fuel for nuclear fusion reactors, they said, but the chemistry involved is incredibly complex.
Demystifying complex chemistry
A "blanket of molten salt" made of FLiBe is wrapped around the nuclear reaction inside a fusion reactor, IBM researchers told Live Science. This provides both a fuel source and a thermal shield for the device.
To create enough tritium, the researchers had to calculate the physics involved while a process called "neutron bombardment" constantly altered the blanket's chemistry. Designing a salt that holds up under competing demands and keeps releasing tritium is a key problem in building this kind of reactor.
"If tritium grabs onto fluorine in the salt, it forms tritium fluoride, which is corrosive and stubborn to remove," the researchers explained. "If it binds to another tritium atom to form a gas, it bubbles out on its own. Predicting which way the reaction goes means modeling the interaction between tritium and the salt with high precision and accuracy that is challenging for classical methods."
Because no ordinary computer can perform the necessary calculations, the team used a combination of AI running on the Frontier supercomputer at ORNL, alongside quantum computing algorithms running on an IBM Quantum Heron quantum processing unit (QPU) in New York. The resulting workflow demonstrated a proof of concept for offloading complex chemistry computations to a quantum computer.
That workflow relied on a technique called wave-function-based embedding, which fragments the calculation into easier-to-calculate clusters, the scientists said in the study. They used classical computers to solve the smaller clusters and passed off the more difficult chunks to a quantum computer. The classical computers then stitched the molecule back together.
This is a method that study co-author Kenneth Merz, a biochemist and principal investigator at Cleveland Clinic Research, pioneered in previous research. Earlier this year, in collaboration with IBM and the Japanese national research institute RIKEN, he used quantum computers to calculate the structure of a 12,635-atom protein.
Fusing quantum and AI
In the new study, the researchers tested their model against known molecular configurations that were already solved by a nonhybrid classical system and determined that the accuracy was maintained with the addition of quantum computations.
This proof of concept should serve as a direct pathway for scaling the models used to predict tritium production within fusion reactors, potentially solving what may be the biggest hurdle to large-scale fusion energy production.
The broader workflow the scientists outlined in a technical blog post involved three stages. First, AI agents proposed and screened many candidate salts from the ORNL database, and for each candidate, calculations estimated various qualities in the tritium breeding process, including how much fuel the salt would make under neutron bombardment.
The most promising salts then went to a supercomputer, which modeled them atom by atom, using the density functional theory (DFT) process to approximate how a molecule's electrons would arrange themselves. These are expensive simulations, so the scientists used "AI stand-ins" trained to reproduce the physics to run them fast enough to be useful. The third stage brought in the quantum computer to figure out where the tritium would bind, which is a shortcoming for DFT.
In the future, the research team will model larger molten-salt systems and study more molecular configurations before evaluating whether AI can slash the time it will take to find a promising molten-salt material.
The wider aim, the scientists told Live Science, is to build a reliable computational pathway for fusion-materials discovery that can help researchers predict how well a blanket material breeds tritium, whether that tritium can be recovered, and how the material may perform in the extreme environment of a fusion reactor.
Can you match these ancient devices to their pictures? Find out with our computing quiz!
The White House is drastically shortening the deadline for government agencies and organizations to adopt new quantum-resistant encryption systems that will withstand attacks that use quantum computers, as the federal government seeks to protect decades’ worth of secrets belonging to militaries, banks, governments, and most individuals on Earth.
The executive order, titled Securing the Nation against Advanced Cryptographic Attacks, requires computing systems for “high-value assets” and “high-impact systems” to transition to post-quantum cryptographic key establishment schemes by December 31, 2030, and to quantum-safe digital signature schemes by December 31, 2031.
Heading off a significant threat
The new deadline, which for many organizations is about five years sooner than the previous one, comes on the heels of recent research showing that the resources and cost for building a cryptographically relevant quantum computer are far less than previous consensus estimates. In response, Google, Cloudflare, and other companies recently tightened their timelines for moving off vulnerable systems to 2029.
The White House is drastically shortening the deadline for government agencies and organizations to adopt new quantum-resistant encryption systems that will withstand attacks that use quantum computers, as the federal government seeks to protect decades’ worth of secrets belonging to militaries, banks, governments, and most individuals on Earth.
The executive order, titled Securing the Nation against Advanced Cryptographic Attacks, requires computing systems for “high-value assets” and “high-impact systems” to transition to post-quantum cryptographic key establishment schemes by December 31, 2030, and to quantum-safe digital signature schemes by December 31, 2031.
Heading off a significant threat
The new deadline, which for many organizations is about five years sooner than the previous one, comes on the heels of recent research showing that the resources and cost for building a cryptographically relevant quantum computer are far less than previous consensus estimates. In response, Google, Cloudflare, and other companies recently tightened their timelines for moving off vulnerable systems to 2029.
Researchers investigate how quantum time flow can be stretched, blurred, or even reversed. What if the direction of time isn’t as fixed as it seems? While our everyday experience tells us that time moves relentlessly forward, the microscopic laws governing quantum systems are far less restrictive. In fact, many of the equations of quantum mechanics [...]
Researchers have unveiled a groundbreaking advancement in the field of single-photon detection technology, introducing a novel dielectric grating design that harnesses Fano resonance to dramatically enhance the performance of superconducting nanowire single-photon detectors (SNSPDs). This transformative approach presents an ultralow-filling-factor detector that achieves unprecedented sensitivity and efficiency compared to conventional designs. Positioned at the forefront of quantum sensing and photonics research, the innovation promises sweeping impacts across quantum computing, secure communications, and fundamental physics research relying on photon detection.
SNSPDs have been critical instruments in detecting single photons with near-ideal timing resolution and low dark counts. However, their performance is inherently limited by the trade-offs in filling factor—the ratio of the active superconducting area to the total device area. Traditional nanowire designs with higher filling factors tend to maximize photon absorption but increase kinetic inductance and limit speed. Conversely, low-filling-factor designs, which offer faster recovery time and reduced device noise, often sacrifice detection efficiency due to diminished absorption cross-section.
In this pioneering study, the research team led by Zheng, Wei, Huang, and colleagues has engineered a dielectric grating structure capable of elevating photon absorption through carefully tailored Fano resonance effects. Fano resonance arises from the interference between a broad spectral continuum and a discrete resonance state, producing asymmetric and sharply peaked spectral features. By designing the grating to induce such resonance near the operational wavelength of the SNSPD, the device achieves enhanced electromagnetic field confinement and increased photon interaction with the superconducting nanowire.
The key to this enhancement lies in the subwavelength periodic patterning of the dielectric layer atop the superconducting nanowires. This grating serves as an optical antenna that channels incident photons into highly resonant modes, significantly concentrating the optical field intensity where it couples effectively to the sensor. As a result, even an ultralow filling factor, far below that used in traditional SNSPD geometries, can deliver detection efficiencies that rival or surpass current state-of-the-art devices.
From a materials science perspective, the researchers employed high-index dielectric materials with exceptionally low optical losses, ensuring minimal dissipation of resonant modes. This novel integration of dielectric gratings with superconducting films required meticulous fabrication techniques capable of producing uniform nanoscale features. The interplay between the dielectric environment and superconducting nanowire morphology was optimized through iterative electromagnetic simulations, including finite-difference time-domain (FDTD) methods, to maximize the resonance effect precisely at the targeted operational wavelengths.
The experimental validation of these devices showcases dramatically improved quantum efficiency, even at extremely low filling factors—below 20%—which is seldom achieved in commercial SNSPDs. This performance gain translates into faster detector reset times due to reduced kinetic inductance, enabling higher count rates without sacrificing sensitivity. Additionally, the refined optical design reduces polarization dependence, improving reliability in systems where photon polarization states fluctuate or remain uncontrolled.
Beyond efficiency improvements, the Fano-resonance-enhanced dielectric grating offers enhanced tunability across different wavelength regimes by adjusting the grating period and dielectric thickness. This opens pathways for customizing SNSPDs to meet the demands of emerging applications in telecommunications, where detection in the near-infrared regime is crucial, as well as in the visible spectrum for biomedical imaging and quantum optics experiments.
The implications for quantum technologies are profound. High-performance SNSPDs underpin many quantum key distribution (QKD) systems, and the ability to engineer ultralow-filling-factor detectors with enhanced absorption can significantly improve the fidelity and scalability of secure quantum communication networks. Moreover, the combination of faster operation speeds and enhanced efficiency aligns with the increasing requirements for temporal resolution and low noise in quantum computing hardware reliant on photonic qubits.
In addition to advancing photon detection, the underlying principles demonstrated by Fano resonance engineering in dielectric gratings could inspire broader innovations in photonic device design. Such resonant structures may be adapted for sensor applications where enhanced light-matter interaction is pivotal, including biosensing, nonlinear optics, and laser cavity engineering. The cross-disciplinary impact stems from achieving precise optical control using relatively simple and scalable fabrication methods.
Crucially, this research highlights the importance of synergizing optical physics concepts with materials science and nanofabrication expertise to solve pressing challenges in photodetection. By moving beyond incremental improvements to embrace fundamentally new resonance mechanisms, the study sets a new benchmark for SNSPD performance metrics, challenging the community to rethink how nanostructured elements can shape device functionalities.
Looking ahead, further optimizations could explore integrating these dielectric gratings with emerging high-temperature superconducting materials or novel two-dimensional superconductors, broadening operational regimes and simplifying cooling requirements. Additionally, combining this approach with multiplexed SNSPD arrays could revolutionize photon-counting capabilities in large-scale quantum sensor networks.
From a practical standpoint, the compatibility of these dielectric gratings with existing photonic integrated circuit platforms suggests potential for seamless incorporation into complex optical systems. This alignment accelerates the translation of laboratory breakthroughs into deployable technologies for real-world quantum instrumentation, telecommunication, and even space-based sensing where minimal detector footprint and efficiency are paramount.
The study’s comprehensive methodology, incorporating both theoretical simulations and experimental verification, provides a robust framework for future device engineering. The precise control over Fano resonance exemplified here serves as a new design paradigm, balancing light absorption and superconducting active area to unlock detector performance hitherto considered unattainable with traditional approaches.
In summary, the inventive design of Fano-resonance-enhanced dielectric gratings for ultralow-filling-factor superconducting nanowire single-photon detectors addresses a critical bottleneck in quantum photonic detection. By leveraging the subtle interference effects responsible for Fano resonance, the team achieves an elegant solution that preserves high detection efficiency while enabling faster response times and reduced detector noise. This leap forward opens exciting new avenues in photonic quantum technologies and beyond, heralding a new era of advanced optical sensing capabilities.
Subject of Research: The development and enhancement of superconducting nanowire single-photon detectors (SNSPDs) through photonic nanostructure engineering.
Article Title: Design of a Fano-resonance-enhanced dielectric grating for ultralow-filling-factor superconducting nanowire single-photon detector.
Article References:
Zheng, F., Wei, K., Huang, X. et al. Design of a Fano-resonance-enhanced dielectric grating for ultralow-filling-factor superconducting nanowire single-photon detector. Sci Rep (2026). https://doi.org/10.1038/s41598-026-58781-8
A single transistor that behaves like a brain cell in the deep freeze could help unlock the next generation of quantum computers and space exploration systems. Researchers at the University of Hong Kong (HKU) have developed a new type of brain-inspired electronic hardware that can operate at temperatures close to absolute zero. The breakthrough could [...]
Quantum computing news usually picks up near the end of the year, as companies try to provide evidence that they are hitting benchmarks on time. However, there have been interesting announcements as the summer starts this year, from incremental progress to attention-grabbing promises. As we did earlier this month, Ars has a rundown of some of the most significant announcements.
These include a promise of useful, error-corrected quantum computing as soon as 2028, details on an updated trapped ion processor, and a case in which claims of quantum supremacy have been cut back a bit thanks to advances in more traditional algorithms.
2028 is remarkably soon
Many people in the field expect that useful quantum computers are still about five to 10 years away. While there may be a few useful algorithms that can be run on existing error-prone hardware, almost all of the interesting problems that quantum computing can be applied to will require some form of error correction enabled by linking a small collection of hardware qubits together into what's called a logical qubit. Logical qubits include the redundant storage of information along with neighboring qubits that can be measured to determine when errors occur and how to fix them.
Quantum computing news usually picks up near the end of the year, as companies try to provide evidence that they are hitting benchmarks on time. However, there have been interesting announcements as the summer starts this year, from incremental progress to attention-grabbing promises. As we did earlier this month, Ars has a rundown of some of the most significant announcements.
These include a promise of useful, error-corrected quantum computing as soon as 2028, details on an updated trapped ion processor, and a case in which claims of quantum supremacy have been cut back a bit thanks to advances in more traditional algorithms.
2028 is remarkably soon
Many people in the field expect that useful quantum computers are still about five to 10 years away. While there may be a few useful algorithms that can be run on existing error-prone hardware, almost all of the interesting problems that quantum computing can be applied to will require some form of error correction enabled by linking a small collection of hardware qubits together into what's called a logical qubit. Logical qubits include the redundant storage of information along with neighboring qubits that can be measured to determine when errors occur and how to fix them.
Researchers in Sweden have developed a machine-learning approach that embeds the laws of physics directly into neural networks. A new study from Chalmers University of Technology in Sweden shows that machine learning can become far more efficient when it starts with a built-in understanding of the laws of physics. Researchers found that giving an AI [...]
A new Chinese quantum computing system pairs two independent neutral-atom arrays in one processor, aiming to boost stability, efficiency and scalability.
A novel phase of matter has been achieved by a team of American researchers, finally realizing a theoretical quantum prediction using nanoscale building blocks, a breakthrough that could pave the way for room-temperature quantum computing.
Researchers at Brown University and the University of Michigan College of Engineering revealed how they briefly stabilized the novel state of matter in a nanoparticle superlattice in a recent paper published in the journal Science. They say their work provides a new method for engineering classes of materials with custom-shaped nanoparticles, which could be applied to quantum computers and other quantum applications.
Quantum Blocks
“Our work is a little bit like kids playing with LEGO blocks,” said co-author Ou Chen, an associate professor of chemistry at Brown. “We synthesize unique nanoscale building blocks and stack them into interesting structures. In this case, we were able to stabilize these theorized transitional structures and demonstrate important quantum optical properties.”
Most metals form in one of two primary groups of crystal structures. The first is face-centered cubic (FCC), the tightest packing arrangement for spherical particles, typically forming a cube with a single particle at each corner and at the center of each face. The other type is body-centered cubic (BCC), a more loosely packed structure in which single particles are still present at the corners, but instead of each face being centered on a particle, one sits at the center of the entire arrangement.
For the most part, atoms form one of these structures as they arrange into a metal, yet at high temperatures, some metals can switch from one structure to another. When it reaches 912° Celsius, Iron will transition from BCC to FCC. One explanation proposed for the transition is the Nishiyama-Wassermann pathway, which suggests that, due to the lower symmetry of the transition phases between FCC and BCC, these phases are fleeting.
Testing the In-Between States
The American team behind the recent research decided to test this idea, fabricating one of those low symmetries in between phases with silver nanoparticles
“Materials scientists have cared about how to control the amount of FCC and BCC in their metals for a long time, but the transitions between these phases have been hard to study because they are so unstable,” said co-author Tim Moore, an assistant research scientist at the University of Michigan. “Being able to observe these structures is a fundamental breakthrough in materials science, and it gives us greater control over nanomaterial engineering.”
At the heart of the team’s work was the truncated octahedron, or “mecon,” a 14-sided polyhedron formed by cutting off the vertices of a diamond, producing an intermediate shape between a cube and sphere.
As the team synthesized silver nanoparticles, they varied the heat level during production, resulting in a spectrum of shapes ranging from cubic to spherical, which were coated with long, sticky molecules that bound the particles. They found that the sticky molecules were required for the particles to assemble themselves into the intermediate shapes predicted by the Nishiyama-Wassermann pathway.
Near Quantum Behavior
Once the particles self-assembled into variously shaped nanoparticle superlattices, the team tested their behavior with computer simulations and physical observations.
The superlattices show evidence of a process known as deep-strong light-matter coupling, in which silver electrons vibrate in unison with light waves, becoming so hybridized they could no longer be treated independently. The similarity of this state to quantum entanglement leaves the team hopeful that their superlattice can be applied to quantum work in the future.
Crucially, this action occurs at room temperature, whereas in previous instances it occurred only at very cold temperatures. This means the work could be useful for developing quantum technologies, which have been limited by the extreme cold required.
“One of the major challenges in quantum computing is maintaining coherent quantum states without requiring extremely low temperatures,” Chen told The Debrief in an email. “Our work suggests that carefully engineered nanoparticle superlattices may provide a scalable materials platform where strong and coherent light–matter interactions can persist at room temperature.”
Quantum Applications
“In the long term, such systems could potentially be used to create or manipulate quantum states for applications in quantum information science, including quantum communication, sensing, or photonic quantum technologies,” Chen said. “However, it is important to emphasize that this research is still at the fundamental physics and materials discovery stage. We are not yet building a room-temperature quantum computer, but rather exploring new material platforms that may help enable future quantum technologies.”
As research continues, the team is focused on more precisely controlling the superlattices’ quantum optical properties.
“Specifically, we are interested in: Engineering nanoparticle architectures that produce even stronger and more controllable light–matter coupling; Exploring how structural order, particle shape, and lattice symmetry influence quantum optical behavior,” Chen explained, “and Integrating these materials with photonic and optoelectronic platforms for potential quantum-device applications.
“More broadly,” Chen concluded, “we see this work as opening a new direction where nanoscale self-assembly can be used to engineer emergent quantum optical properties that do not exist in the individual nanoparticles alone.”
Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.
The Majorana 2 quantum processor is built from topological qubits, and its creators claim it can sustain quantum coherence for an average of 20 seconds — orders of magnitude longer than the milliseconds that conventional chips last.
With dozens of companies, from small startups to tech giants, pursuing quantum computing, there's a steady flow of results as they try to find a path to utility. We typically focus on new technologies and major landmarks, which can obscure the fact that any big success will inevitably have been built on a lot of incremental progress.
The past few weeks have seen two companies release progress reports on how they're trying to get the technologies closer to general use. None of these represents a major breakthrough, but all are absolutely necessary for the technology to advance. The idea here is to convey the hard work required to move us closer to something useful.
Microsoft does material science
Microsoft is one of the few companies working on topological qubits, based on the distinct physics that occurs when particles are confined. Microsoft's system relies on a thin superconducting wire placed on top of a semiconductor. In superconductors, groups of two electrons form Cooper pairs. But if the wire contains an odd number of conducting electrons—meaning there's a single unpaired electron—it will end up delocalized to both ends of the wire. (Because quantum mechanics is weird.)
O investimento de cinco anos vai financiar investigação, fabrico, aquisições e parcerias, com o objetivo de entregar o IBM Quantum Starling em 2029 e, mais tarde, o Blue Jay, que será capaz de realizar mil milhões de operações quânticas em 2.000 qubits.
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