When it comes to building a fully functional “fault-tolerant” quantum computer, companies and government labs all over the world are rushing to be the first over the finish line. But a truly useful universal quantum computer capable of running complex algorithms would have to entangle millions of coherent qubits, which are extremely fragile. Because of environmental factors such as temperature, interference from other electronic systems in hardware, and even errors in measurement, today’s devices would fail under an avalanche of errors long before reaching that point.

So the problem of error correction is a key issue for the future of the market. It arises because errors in qubits can’t be corrected simply by keeping multiple copies, as they are in classical computers: quantum rules forbid the copying of qubit states while they are still entangled with others, and are thus unknown. To run quantum circuits with millions of gates, we therefore need new tricks to enable quantum error correction (QEC).

Protected states

The general principle of QEC is to spread the information over many qubits so that an error in any one of them doesn’t matter too much. “The essential idea of quantum error correction is that if we want to protect a quantum system from damage then we should encode it in a very highly entangled state,” says John Preskill, director of the Institute for Quantum Information and Matter at the California Institute of Technology in Pasadena.

There is no unique way of achieving that spreading, however. Different error-correcting codes can depend on the connectivity between qubits – whether, say, they are coupled only to their nearest neighbours or to all the others in the device – which tends to be determined by the physical platform being used. However error correction is done, it must be done fast. “The mechanisms for error correction need to be running at a speed that is commensurate with that of the gate operations,” says Michael Cuthbert, founding director of the UK’s National Quantum Computing Centre (NQCC). “There’s no point in doing a gate operation in a nanosecond if it then takes 100 microseconds to do the error correction for the next gate operation.”

At the moment, dealing with errors is largely about compensation rather than correction: patching up the problems of errors in retrospect, for example by using algorithms that can throw out some results that are likely to be unreliable (an approach called “post-selection”). It’s also a matter of making better qubits that are less error-prone in the first place.

According to Maria Maragkou, commercial vice-president of quantum software company Riverlane, the goal of full QEC has ramifications for the design of the machines all the way from hardware to workflow planning. “The shift to support error correction has a profound effect on the way quantum processors themselves are built, the way we control and operate them, through a robust software stack on top of which the applications can be run,” she explains. The “stack” includes everything from programming languages to user interfaces and servers.

With genuinely fault-tolerant qubits, errors can be kept under control and prevented from proliferating during a computation. Such qubits might be made in principle by combining many physical qubits into a single “logical qubit” in which errors can be corrected (see figure 1). In practice, though, this creates a large overhead: huge numbers of physical qubits might be needed to make just a few fault-tolerant logical qubits. The question is then whether errors in all those physical qubits can be checked faster than they accumulate (see figure 2).

That overhead has been steadily reduced over the past several years, and at the end of last year researchers at Google announced that their 105-qubit Willow quantum chip passed the break-even threshold at which the error rate gets smaller, rather than larger, as more physical qubits are used to make a logical qubit. This means that in principle such arrays could be scaled up without errors accumulating.

Fault-tolerant quantum computing is the ultimate goal, says Jay Gambetta, director of IBM research at the company’s centre in Yorktown Heights, New York. He believes that to perform truly transformative quantum calculations, the system must go beyond demonstrating a few logical qubits – instead, you need arrays of at least a 100 of them, that can perform more than 100 million quantum operations (10⁸ QuOps). “The number of operations is the most important thing,” he says.

It sounds like a tall order, but Gambetta is confident that IBM will achieve these figures by 2029. By building on what has been achieved so far with error correction and mitigation, he feels “more confident than I ever did before that we can achieve a fault-tolerant computer.” Jerry Chow, previous manager of the Experimental Quantum Computing group at IBM, shares that optimism. “We have a real blueprint for how we can build [such a machine] by 2029,” he says (see figure 3).

Others suspect the breakthrough threshold may be a little lower: Steve Brierly, chief executive of Riverlane, believes that the first error-corrected quantum computer, with around 10 000 physical qubits supporting 100 logical qubits and capable of a million QuOps (a megaQuOp), could come as soon as 2027. Following on, gigaQuOp machines (10⁹ QuOps) should be available by 2030–32, and teraQuOps (10¹² QuOp) by 2035–37.

Platform independent

Error mitigation and error correction are just two of the challenges for developers of quantum software. Fundamentally, to develop a truly quantum algorithm involves taking full advantage of the key quantum-mechanical properties such as superposition and entanglement. Often, the best way to do that depends on the hardware used to run the algorithm. But ultimately the goal will be to make software that is not platform-dependent and so doesn’t require the user to think about the physics involved.

“At the moment, a lot of the platforms require you to come right down into the quantum physics, which is a necessity to maximize performance,” says Richard Murray of photonic quantum-computing company Orca. Try to generalize an algorithm by abstracting away from the physics and you’ll usually lower the efficiency with which it runs. “But no user wants to talk about quantum physics when they’re trying to do machine learning or something,” Murray adds. He believes that ultimately it will be possible for quantum software developers to hide those details from users – but Brierly thinks this will require fault-tolerant machines.

“In due time everything below the logical circuit will be a black box to the app developers”, adds Maragkou over at Riverlane. “They will not need to know what kind of error correction is used, what type of qubits are used, and so on.” She stresses that creating truly efficient and useful machines depends on developing the requisite skills. “We need to scale up the workforce to develop better qubits, better error-correction codes and decoders, write the software that can elevate those machines and solve meaningful problems in a way that they can be adopted.” Such skills won’t come only from quantum physicists, she adds: “I would dare say it’s mostly not!”

Yet even now, working on quantum software doesn’t demand a deep expertise in quantum theory. “You can be someone working in quantum computing and solving problems without having a traditional physics training and knowing about the energy levels of the hydrogen atom and so on,” says Ashley Montanaro, who co-founded the quantum software company Phasecraft.

On the other hand, insights can flow in the other direction too: working on quantum algorithms can lead to new physics. “Quantum computing and quantum information are really pushing the boundaries of what we think of as quantum mechanics today,” says Montanaro, adding that QEC “has produced amazing physics breakthroughs.”

Early adopters?

Once we have true error correction, Cuthbert at the UK’s NQCC expects to see “a flow of high-value commercial uses” for quantum computers. What might those be?

In this arena of quantum chemistry and materials science, genuine quantum advantage – calculating something that is impossible using classical methods alone – is more or less here already, says Chow. Crucially, however, quantum methods needn’t be used for the entire simulation but can be added to classical ones to give them a boost for particular parts of the problem.

For example, last year researchers at IBM teamed up with scientists at several RIKEN institutes in Japan to calculate the minimum energy state for the iron sulphide cluster (4Fe-4S) at the heart of the bacterial nitrogenase enzyme that fixes nitrogen. This cluster is too big and complex to be accurately simulated using the classical approximations of quantum chemistry. The researchers used a combination of both quantum computing (with IBM’s 72-qubit Heron chip) and RIKEN’s Fugaku high performance computing (HPC). This idea of “improving classical methods by injecting quantum as a subroutine” is likely to be a more general strategy, says Gambetta. “The future of computing is going to be heterogeneous accelerators [of discovery] that include quantum.”

Likewise, Montanaro says that Phasecraft is developing “quantum-enhanced algorithms”, where a quantum computer is used, not to solve the whole problem, but just to help a classical computer in some way. “There are only certain problems where we know quantum computing is going to be useful,” he says. “I think we are going to see quantum computers working in tandem with classical computers in a hybrid approach. I don’t think we’ll ever see workloads that are entirely run using a quantum computer.” Among the first important problems that quantum machines will solve, according to Montanaro, are the simulation of new materials – to develop, for example, clean-energy technologies (see figure 4).

“For a physicist like me,” says Preskill, “what is really exciting about quantum computing is that we have good reason to believe that a quantum computer would be able to efficiently simulate any process that occurs in nature.”

Montanaro believes another likely near-term goal for useful quantum computing is solving optimization problems – both here and in quantum simulation, “we think genuine value can be delivered already in this NISQ era with hundreds of qubits.” (NISQ, a term coined by Preskill, refers to noisy intermediate-scale quantum computing, with relatively small numbers of rather noisy, error-prone qubits.)

One further potential benefit of quantum computing is that it tends to require less energy than classical high-performance computing, which is notoriously high. If the energy cost could be cut by even a few percent, it would be worth using quantum resources for that reason alone. “Quantum has real potential for an energy advantage,” says Chow. One study in 2020 showed that a particular quantum-mechanical calculation carried out on a HPC used many orders of magnitude more energy than when it was simulated on a quantum circuit. Such comparisons are not easy, however, in the absence of an agreed and well-defined metric for energy consumption.

Building the market

Right now, the quantum computing market is in a curious superposition of states itself – it has ample proof of principle, but today’s devices are still some way from being able to perform a computation relevant to a practical problem that could not be done with classical computers. Yet to get to that point, the field needs plenty of investment.

The fact that quantum computers, especially if used with HPC, are already unique scientific tools should establish their value in the immediate term, says Gambetta. “I think this is going to accelerate, and will keep the funding going.” It is why IBM is focusing on utility-scale systems of around 100 qubits or so and more than a thousand gate operations, he says, rather than simply trying to build ever bigger devices.

Montanaro sees a role for governments to boost the growth of the industry “where it’s not the right fit for the private sector”. One role of government is simply as a customer. For example, Phasecraft is working with the UK national grid to develop a quantum algorithm for optimizing the energy network. “Longer-term support for academic research is absolutely critical,” Montanaro adds. “It would be a mistake to think that everything is done in terms of the underpinning science, and governments should continue to support blue-skies research.”

It’s not clear, though, whether there will be a big demand for quantum machines that every user will own and run. Before 2010, “there was an expectation that banks and government departments would all want their own machine – the market would look a bit like HPC,” Cuthbert says. But that demand depends in part on what commercial machines end up being like. “If it’s going to need a premises the size of a football field, with a power station next to it, that becomes the kind of infrastructure that you only want to build nationally.” Even for smaller machines, users are likely to try them first on the cloud before committing to installing one in-house.

According to Cuthbert , the real challenge in the supply-chain development is that many of today’s technologies were developed for the science community – where, say, achieving millikelvin cooling or using high-power lasers is routine. “How do you go from a specialist scientific clientele to something that starts to look like a washing machine factory, where you can make them to a certain level of performance,” while also being much cheaper, and easier to use?

But Cuthbert is optimistic about bridging this gap to get to commercially useful machines, encouraged in part by looking back at the classical computing industry of the 1970s. “The architects of those systems could not imagine what we would use our computation resources for today. So I don’t think we should be too discouraged that you can grow an industry when we don’t know what it’ll do in five years’ time.”

Montanaro too sees analogies with those early days of classical computing. “If you think what the computer industry looked like in the 1940s, it’s very different from even 20 years later. But there are some parallels. There are companies that are filling each of the different niches we saw previously, there are some that are specializing in quantum hardware development, there are some that are just doing software.” Cuthbert thinks that the quantum industry is likely to follow a similar pathway, “but more quickly and leading to greater market consolidation more rapidly.”

However, while the classical computing industry was revolutionized by the advent of personal computing in the 1970s and 80s, it seems very unlikely that we will have any need for quantum laptops. Rather, we might increasingly see apps and services appear that use cloud-based quantum resources for particular operations, merging so seamlessly with classical computing that we don’t even notice.

That, perhaps, would be the ultimate sign of success: that quantum computing becomes invisible, no big deal but just a part of how our answers are delivered.

• In the first instalment of this two-part article, Philip Ball explores the latest developments in the quantum-computing industry

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Female university students do much better in introductory physics exams if they have the option of retaking the tests. That’s according to a new analysis of almost two decades of US exam results for more than 26 000 students. The study’s authors say it shows that female students benefit from lower-stakes assessments – and that the persistent “gender grade gap” in physics exam results does not reflect a gender difference in physics knowledge or ability.

The study has been carried out by David Webb from the University of California, Davis, and Cassandra Paul from San Jose State University. It builds on previous work they did in 2023, which showed that the gender gap disappears in introductory physics classes that offer the chance for all students to retake the exams. That study did not, however, explore why the offer of a retake has such an impact.

In the new study, the duo analysed exam results from 1997 to 2015 for a series of introductory physics classes at a public university in the US. The dataset included 26 783 students, mostly in biosciences, of whom about 60% were female. Some of the classes let students retake exams while others did not, thereby letting the researchers explore why retakes close the gender gap.

When Webb and Paul examined the data for classes that offered retakes, they found that in first-attempt exams female students slightly outperformed their male counterparts. But male students performed better than female students in retakes.

This, the researchers argue, discounts the notion that retakes close the gender gap by allowing female students to improve their grades. Instead, they suggest that the benefit of retakes is that they lower the stakes of the first exam.

The team then compared the classes that offered retakes with those that did not, which they called high-stakes courses. They found that the gender gap in exam results was much larger in the high-stakes classes than the lower-stakes classes that allowed retakes.

“This suggests that high-stakes exams give a benefit to men, on average, [and] lowering the stakes of each exam can remove that bias ” Webb told Physics World. He thinks that as well as allowing students to retake exams, physics might benefit from not having comprehensive high-stakes final exams but instead “use final exam time to let students retake earlier exams”.

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Improving the efficiency of solar cells will likely be one of the key approaches to achieving net zero emissions in many parts of the world. Many types of solar cells will be required, with some of the better performances and efficiencies expected to come from multi-junction solar cells. Multi-junction solar cells comprise a vertical stack of semiconductor materials with distinct bandgaps, with each layer converting a different part of the solar spectrum to maximize conversion of the Sun’s energy to electricity.

When there are no constraints on the choice of materials, triple-junction solar cells can outperform double-junction and single-junction solar cells, with a power conversion efficiency (PCE) of up to 51% theoretically possible. But material constraints – due to fabrication complexity, cost or other technical challenges – mean that many such devices still perform far from the theoretical limits.

Perovskites are one of the most promising materials in the solar cell world today, but fabricating practical triple-junction solar cells beyond 1 cm² in area has remained a challenge. A research team from Australia, China, Germany and Slovenia set out to change this, recently publishing a paper in Nature Nanotechnology describing the largest and most efficient triple-junction perovskite–perovskite–silicon tandem solar cell to date.

When asked why this device architecture was chosen, Anita Ho-Baillie, one of the lead authors from The University of Sydney, states: “I am interested in triple-junction cells because of the larger headroom for efficiency gains”.

Addressing surface defects in perovskite solar cells

Solar cells formed from metal halide perovskites have potential to be commercially viable, due to their cost-effectiveness, efficiency, ease of fabrication and their ability to be paired with silicon in multi-junction devices. The ease of fabrication means that the junctions can be directly fabricated on top of each other through monolithic integration – which leads to only two terminal connections, instead of four or six. However, these junctions can still contain surface defects.

To enhance the performance and resilience of their triple-junction cell (top and middle perovskite junctions on a bottom silicon cell), the researchers optimized the chemistry of the perovskite material and the cell design. They addressed surface defects in the top perovskite junction by replacing traditional lithium fluoride materials with piperazine-1,4-diium chloride (PDCl). They also replaced methylammonium – which is commonly used in perovskite cells – with rubidium. “The rubidium incorporation in the bulk and the PDCl surface treatment improved the light stability of the cell,” explains Ho-Baillie.

To connect the two perovskite junctions, the team used gold nanoparticles on tin oxide. Because the gold was in a nanoparticle form, the junctions could be engineered to maximize the flow of electric charge and light absorption by the solar cell.

“Another interesting aspect of the study is the visualization of the gold nanoparticles [using transmission electron microscopy] and the critical point when they become a semi-continuous film, which is detrimental to the multi-junction cell performance due to its parasitic absorption,” says Ho-Baillie. “The optimization for achieving minimal particle coverage while achieving sufficient ohmic contact for vertical carrier flow are useful insights”.

Record performance for a large-scale perovskite triple-junction cell

Using these design strategies, Ho-Baillie and colleagues developed a 16 cm² triple-junction cell that achieved an independently certified steady-state PCE of 23.3% – the highest reported for a large-area device. While triple-junction perovskite solar cells have exhibited higher PCEs – with all-perovskite triple-junction cells reaching 28.7% and perovskite–perovskite–silicon devices reaching 27.1% – these were all achieved on a 1 cm² cell, not a large-area cell.

In this study, the researchers also developed a 1 cm² cell that was close to the best, with a PCE of 27.06%, but it is the large-area cell that’s the record breaker. The 1 cm² cell also passed the International Electrotechnical Commission’s (IEC) 61215 thermal cycling test, which exposes the cell to 200 cycles under extreme temperature swings, ranging from –40 to 85°C. During this test, the 1 cm² cell retained 95% of its initial efficiency after 407 h of continuous operation.

The combination of the successful thermal cycling test combined with the high efficiencies on a larger cell shows that there could be potential for this triple-junction architecture in real-world settings in the near future, even though they are still far away from their theoretical limits.

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It’s rare to come across someone who’s been responsible for enabling a seismic shift in society that has affected almost everyone and everything. Tim Berners-Lee, who invented the World Wide Web, is one such person. His new memoir This is for Everyone unfolds the history and development of the Web and, in places, of the man himself.

Berners-Lee was born in London in 1955 to parents, originally from Birmingham, who met while working on the Ferranti Mark 1 computer and knew Alan Turing. Theirs was a creative, intellectual and slightly chaotic household. His mother could maintain a motorbike with fence wire and pliers, and was a crusader for equal rights in the workplace. His father – brilliant and absent minded – taught Berners-Lee about computers and queuing theory. A childhood of camping and model trains, it was, in Berners-Lee’s view, idyllic.

Berners-Lee had the good fortune to be supported by a series of teachers and managers who recognized his potential and unique way of working. He studied physics at the University of Oxford (his tutor “going with the flow” of Berners-Lee’s unconventional notation and ability to approach problems from oblique angles) and built his own computer. After graduating, he married and, following a couple of jobs, took a six-month placement at the CERN particle-physics lab in Geneva in 1985.

This placement set “a seed that sprouted into a tool that shook up the world”. Berners-Lee saw how difficult it was to share information stored in different languages in incompatible computer systems and how, in contrast, information flowed easily when researchers met over coffee, connected semi-randomly and talked. While at CERN, he therefore wrote a rough prototype for a program to link information in a type of web rather than a structured hierarchy.

Back at CERN, Tim Berners-Lee developed his vision of a “universal portal” to information.

The placement ended and the program was ignored, but four years later Berners-Lee was back at CERN. Now divorced and soon to remarry, he developed his vision of a “universal portal” to information. It proved to be the perfect time. All the tools necessary to achieve the Web – the Internet, address labelling of computers, network cables, data protocols, the hypertext language that allowed cross-referencing of text and links on the same computer – had already been developed by others.

Berners-Lee saw the need for a user-friendly interface, using hypertext that could link to information on other computers across the world. His excitement was “uncontainable”, and according to his line manager “few of us if any could understand what he was talking about”. But Berners-Lee’s managers supported him and freed his time away from his actual job to become the world’s first web developer.

Having a vision was one thing, but getting others to share it was another. People at CERN only really started to use the Web properly once the lab’s internal phone book was made available on it. As a student at the time, I can confirm that it was much, much easier to use the Web than log on to CERN’s clunky IBM mainframe, where phone numbers had previously been stored.

Wider adoption relied on a set of volunteer developers, working with open-source software, to make browsers and platforms that were attractive and easy to use. CERN agreed to donate the intellectual property for web software to the public domain, which helped. But the path to today’s Web was not smooth: standards risked diverging and companies wanted to build applications that hindered information sharing.

Feeling the “the Web was outgrowing my institution” and “would be a distraction” to a lab whose core mission was physics, Berners-Lee moved to the Massachusetts Institute of Technology in 1994. There he founded the World Wide Web Consortium (W3C) to ensure consistent, accessible standards were followed by everyone as the Web developed into a global enterprise. The progression sounds straightforward although earlier accounts, such as James Gillies and Robert Caillau’s 2000 book How the Web Was Born, imply some rivalry between institutions that is glossed over here.

Initially inclined to advise people to share good things and not search for bad things, Berners-Lee had reckoned without the insidious power of “manipulative and coercive” algorithms on social networks

The rest is history, but not quite the history that Berners-Lee had in mind. By 1995 big business had discovered the possibilities of the Web to maximize influence and profit. Initially inclined to advise people to share good things and not search for bad things, Berners-Lee had reckoned without the insidious power of “manipulative and coercive” algorithms on social networks. Collaborative sites like Wikipedia are closer to his vision of an ideal Web; an emergent good arising from individual empowerment. The flip side of human nature seems to come as a surprise.

The rest of the book brings us up to date with Berners-Lee’s concerns (data, privacy, misuse of AI, toxic online culture), his hopes (the good use of AI), a third marriage and his move into a data-handling business. There are some big awards and an impressive amount of name dropping; he is excited by Order of Merit lunches with the Queen and by sitting next to Paul McCartney’s family at the opening ceremony to the London Olympics in 2012. A flick through the index reveals names ranging from Al Gore and Bono to Lucien Freud. These are not your average computing technology circles.

There are brief character studies to illustrate some of the main players, but don’t expect much insight into their lives. This goes for Berners-Lee too, who doesn’t step back to particularly reflect on those around him, or indeed his own motives beyond that vision of a Web for all enabling the best of humankind. He is firmly future focused.

Still, there is no-one more qualified to describe what the Web was intended for, its core philosophy, and what caused it to develop to where it is today. You’ll enjoy the book whether you want an insight into the inner workings that make your web browsing possible, relive old and forgotten browser names, or see how big tech wants to monetize and monopolize your online time. It is an easy read from an important voice.

The book ends with a passionate statement for what the future could be, with businesses and individuals working together to switch the Web from “the attention economy to the intention economy”. It’s a future where users are no longer distracted by social media and manipulated by attention-grabbing algorithms; instead, computers and services do what users want them to do, with the information that users want them to have.

Berners-Lee is still optimistic, still an incurable idealist, still driven by vision. And perhaps still a little naïve too in believing that everyone’s values will align this time.

• 2025 Macmillan 400pp £25.00/$30.00hb

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This talk shows how integrating p-type NiO to form NiO/Ga_₂O_₃ heterojunction rectifiers overcomes that barrier, enabling record-class breakdown and Ampere-class operation. It will cover device structure/process optimization, thermal stability to high temperatures, and radiation response – with direct ties to today’s priorities: EV fast charging, AI data‑center power systems, and aerospace/space‑qualified power electronics.

An interactive Q&A session follows the presentation.

 

Jian-Sian Li received the PhD in chemical engineering from the University of Florida in 2024, where his research focused on NiO/β-Ga_₂O_₃ heterojunction power rectifiers, includes device design, process optimization, fast switching, high-temperature stability, and radiation tolerance (γ, neutron, proton). His work includes extensive electrical characterization and microscopy/TCAD analysis supporting device physics and reliability in harsh environments. Previously, he completed his BS and MS at National Taiwan University (2015, 2018), with research spanning phoretic/electrokinetic colloids, polymers for OFETs/PSCs, and solid-state polymer electrolytes for Li-ion batteries. He has since transitioned to industry at Micron Technology.

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A new integrated “snapshot spectroscopy” system developed in China can determine the spectral and spatial composition of light from an object with much better precision than other existing systems. The instrument uses randomly textured lithium niobate and its developers have used it for astronomical imaging and materials analysis – and they say that other applications are possible.

Spectroscopy is crucial to analysis of all kinds of objects in science and engineering, from studying the radiation emitted by stars to identifying potential food contaminants. Conventional spectrometers – such as those used on telescopes – rely on diffractive optics to separate incoming light into its constituent wavelengths. This makes them inherently large, expensive and inefficient at rapid image acquisition as the light from each point source has to be spatially separated to resolve the wavelength components.

In recent years researchers have combined computational methods with advanced optical sensors to create computational spectrometers with the potential to rival conventional instruments. One such approach is hyperspectral snapshot imaging, which captures both spectral and spatial information in the same image. There are currently two main snapshot-imaging techniques available. Narrowband-filtered snapshot spectral imagers comprise a mosaic pattern of narrowband filters and acquire an image by taking repeated snapshots at different wavelengths. However, these trade spectral resolution with spatial resolution, as each extra band requires its own tile within the mosaic. A more complex alternative design – the broadband-modulated snapshot spectral imager – uses a single, broadband detector covered with a spatially varying element such as a metasurface that interacts with the light and imprints spectral encoding information onto each pixel. However, these are complex to manufacture and their spectral resolution is limited to the nanometre scale.

Random thicknesses

In the new work, researchers led by Lu Fang at Tsinghua University in Beijing unveil a spectroscopy technique that utilizes the nonlinear optical properties of lithium niobate to achieve sub-Ångström spectral resolution in a simply fabricated, integrated snapshot detector they call RAFAEL. A lithium niobate layer with random, sub-wavelength thickness variations is surrounded by distributed Bragg reflectors, forming optical cavities. These are integrated into a stack with a set of electrodes. Each cavity corresponds to a single pixel. Incident light enters  from one side of a cavity, interacting with the lithium niobate repeatedly before exiting and being detected. Because lithium niobate is nonlinear, its response varies with the wavelength of the light.

The researchers then applied a bias voltage using the electrodes. The nonlinear optical response of lithium niobate means that this bias alters its response to light differently at different wavelengths. Moreover, the random variation of the lithium niobate’s thickness around the surface means that the wavelength variation is spatially specific.

The researchers designed a machine learning algorithm and trained it to use this variation of applied bias voltage with resulting wavelength detected at each point to reconstruct the incident wavelengths on the detector at each point in space.

“The randomness is useful for making the equations independent,” explains Fang; “We want to have uncorrelated equations so we can solve them.”

Thousands of stars

The researchers showed that they could achieve 88 Hz snapshot spectroscopy on a grid of 2048×2048 pixels with a spectral resolution of 0.5 Å (0.05 nm) between wavelengths of 400–1000 nm. They demonstrated this by capturing the full atomic absorption spectra of up to 5600 stars in a single snapshot. This is a two to four orders of magnitude improvement in observational efficiency over world-class astronomical spectrometers. They also demonstrated other applications, including a materials analysis challenge involving the distinction of a real leaf from a fake one. The two looked identical at optical wavelengths, but, using its broader range of wavelengths, RAFAEL was able to distinguish between the two.

The researchers are now attempting to improve the device further: “I still think that sub-Ångstrom is not the ending – it’s just the starting point,” says Fu. “We want to push the limit of our resolution to the picometre.” In addition, she says, they are working on further integration of the device – which requires no specialized lithography – for easier use in the field. “We’ve already put this technology on a drone platform,” she reveals. The team is also working with astronomical observatories such as Gran Telescopio Canarias in La Palma, Spain.

The research is described in Nature.

Computational imaging expert David Brady of Duke University in North Carolina is impressed by the instrument. “It’s a compact package with extremely high spectral resolution,” he says; “Typically an optical instrument, like a CMOS sensor that’s used here, is going to have between 10,000 and 100,000 photo-electrons per pixel.  That’s way too many photons for getting one measurement…I think you’ll see that with spectral imaging as is done here, but also with temporal imaging. People are saying you don’t need to go at 30 frames second, you can go at a million frames per second and push closer to the single photon limit, and then that would require you to do computation to figure out what it all means.”

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Physicists have developed a novel imaging technique for detecting and characterizing objects hidden within opaque, highly scattering material. The researchers, from France and Austria, showed that their new mathematical approach, which utilizes the fact that hidden objects generate their own complex scattering pattern, or “fingerprint”, can work on biological tissue.

Viewing the inside of the human body is challenging due to the scattering nature of tissue. With ultrasound, when waves propagate through tissue they are reflected, bounce around and scatter chaotically, creating noise that obscures the signal from the object that the medical practitioner is trying to see. The further you delve into the body the more incoherent the image becomes.

There are techniques for overcoming these issues, but as scattering increases – in more complex media or as you push deeper through tissue – they struggle and unpicking the required signal becomes too complex.

The scientists behind the latest research, from the Institut Langevin in Paris, France and TU Wien in Vienna, Austria, say that rather than compensating for scattering, their technique instead relies on detecting signals from the hidden object in the disorder.

Objects buried in a material create their own complex scattering pattern, and the researchers found that if you know an object’s specific acoustic signal it’s possible to find it in the noise created by the surrounding environment.

“We cannot see the object, but the backscattered ultrasonic wave that hits the microphones of the measuring device still carries information about the fact that it has come into contact with the object we are looking for,” explains Stefan Rotter, a theoretical physicist at TU Wien.

Rotter and his colleagues examined how a series of objects scattered ultrasound waves in an interference-free environment. This created what they refer to as fingerprint matrices: measurements of the specific, characteristic way in which each object scattered the waves.

The team then developed a mathematical method that allowed them to calculate the position of each object when hidden in a scattering medium, based on its fingerprint matrix.

“From the correlations between the measured reflected wave and the unaltered fingerprint matrix, it is possible to deduce where the object is most likely to be located, even if the object is buried,” explains Rotter.

The team tested the technique in three different scenarios. The first experiment trialled the ultrasound imaging of metal spheres in a dense suspension of glass beads in water. Conventional ultrasound failed in this setup and the spheres were completely invisible, but with their novel fingerprint method the researchers were able to accurately detect them.

Next, to examine a medical application for the technique, the researchers embedded lesion markers often used to monitor breast tumours in a foam designed to mimic the ultrasound scattering of soft tissue. These markers can be challenging to detect due to scatterers randomly distributed in human tissue. With the fingerprint matrix, however, the researchers say that the markers were easy to locate.

Finally, the team successfully mapped muscle fibres in a human calf using the technique. They claim this could be useful for diagnosing and monitoring neuromuscular diseases.

According to Rotter and his colleagues, their fingerprint matrix method is a versatile and universal technique that could be applied beyond ultrasound to all fields of wave physics. They highlight radar and sonar as examples of sensing techniques where target identification and detection in noisy environments are long-standing challenges.

“The concept of the fingerprint matrix is very generally applicable – not only for ultrasound, but also for detection with light,” Rotter says. “It opens up important new possibilities in all areas of science where a reflection matrix can be measured.”

The researchers report their findings in Nature Physics.

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Radiation treatment for patients with lung cancer represents a balancing act, particularly if malignant lesions are centrally located near to critical structures. The radiation may destroy the tumour, but vital organs may be seriously damaged as well.

The standard treatment for non-small cell lung cancer (NSCLC) is stereotactic ablative body radiotherapy (SABR), which delivers intense radiation doses in just a few treatment sessions and achieves excellent local control. For ultracentral lung legions, however – defined as having a planning target volume (PTV) that abuts or overlaps the proximal bronchial tree, oesophagus or pulmonary vessels – the high risk of severe radiation toxicity makes SABR highly challenging.

A research team at GenesisCare UK, an independent cancer care provider operating nine treatment centres in the UK, has now demonstrated that stereotactic MR-guided adaptive radiotherapy (SMART)-based SABR may be a safer and more effective option for treating ultracentral metastatic lesions in patients with histologically confirmed NSCLC. They report their findings in Advances in Radiation Oncology.

SMART uses diagnostic-quality MR scans to provide real-time imaging, 3D multiplanar soft-tissue tracking and automated beam control of an advanced linear accelerator. The idea is to use daily online volume adaptation and plan re-optimization to account for any changes in tumour size and position relative to organs-at-risk (OAR). Real-time imaging enables treatment in breath-hold with gated beam delivery (automatically pausing delivery if the target moves outside a defined boundary), eliminating the need for an internal target volume and enabling smaller PTV margins.

The approach offers potential to enhance treatment precision and target coverage while improving sparing of adjacent organs compared with conventional SABR, first author Elena Moreno-Olmedo and colleagues contend.

A safer treatment option

The team conducted a study to assess the incidence of SABR-related toxicities in patients with histologically confirmed NSCLC undergoing SMART-based SABR. The study included 11 patients with 18 ultracentral lesions, the majority of whom had oligometastatic or olioprogressive disease.

Patients received five to eight treatment fractions, to a median dose of 40 Gy (ranging from 30 to 60 Gy). The researchers generated fixed-field SABR plans with dosimetric aims including a PTV V_100% (the volume receiving at least 100% of the prescription dose) of 95% or above, a PTV V_95% of 98% or above and a maximum dose of between110% and 140%. PTV coverage was compromised where necessary to meet OAR constraints, with a minimum PTV V_100% of at least 70%.

SABR was performed using a 6 MV 0.35 T MRIdian linac with gated delivery during repeated breath-holds, under continuous MR guidance. Based on daily MRI scans, online plan adaptation was performed for all of the 78 delivered fractions.

The researchers report that both the PTV volume and PTV overlap with ultracentral OARs were reduced in SMART treatments compared with conventional SABR. The median SMART PTV was 10.1 cc, compared with 30.4 cc for the simulated SABR PTV, while the median PTV overlap with OARs was 0.85 cc for SMART (8.4% of the PTV) and 4.7 cc for conventional SABR.

In terms of treatment-related side effects for SMART, the rates of acute and late grade 1–2 toxicities were 54% and 18%, respectively, with no grade 3–5 toxicities observed. This demonstrates the technique’s increased safety compared with non-adaptive SABR treatments, which have exhibited severe rates of toxicity, including treatment-related deaths, in ultracentral tumours.

Two-thirds of patients were alive at the median follow-up point of 28 months, and 93% were free from local progression at 12 months. The median progression-free survival was 5.8 months and median overall survival was 20 months.

Acknowledging the short follow-up time frame, the researchers note that additional late toxicities may occur. However, they are hopeful that SMART will be considered as a favourable treatment option for patients with ultracentral NSCLC lesions.

“Our analysis demonstrates that hypofractionated SMART with daily online adaptation for ultracentral NSCLC achieved comparable local control to conventional non-adaptive SABR, with a safer toxicity profile,” they write. “These findings support the consideration of SMART as a safer and effective treatment option for this challenging subgroup of thoracic tumours.”

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Researchers in the United Arab Emirates have designed a new catheter that can deliver drugs to entire regions of the brain. Developed by Batoul Khlaifat and colleagues at New York University Abu Dhabi, the catheter’s helical structure and multiple outflow ports could make it both safer and more effective for treating a wide range of neurological disorders.

Modern treatments for brain-related conditions including Parkinson’s disease, epilepsy, and tumours often involve implanting microfluidic catheters that deliver controlled doses of drug-infused fluids to highly localized regions of the brain. Today, these implants are made from highly flexible materials that closely mimic the soft tissue of the brain. This makes them far less invasive than previous designs.

However, there is still much room for improvement, as Khlaifat explains. “Catheter design and function have long been limited by the neuroinflammatory response after implantation, as well as the unequal drug distribution across the catheter’s outlets,” she says.

A key challenge with this approach is that each of the brain’s distinct regions has highly irregular shapes, which makes it incredibly difficult to target via single drug doses. Instead, doses must be delivered either through repeated insertions from a single port at the end of a catheter, or through single insertions across multiple co-implanted catheters. Either way, the approach is highly invasive, and runs the risk of further trauma to the brain.

Multiple ports

In their study, Khlaifat’s team explored how many of these problems stem from existing catheter designs. They tend to be simple tubes with single input and output ports at either end. Using fluid dynamics simulations, they started by investigating how drug outflow would change when multiple output ports are positioned along the length of the catheter.

To ensure this outflow is delivered evenly, they carefully adjusted the diameter of each port to account for the change in fluid pressure along the catheter’s length – so that four evenly spaced ports could each deliver roughly one quarter of the total flow. Building on this innovation, the researchers then explored how the shape of the catheter itself could be adjusted to optimize delivery even further.

“We varied the catheter design from a straight catheter to a helix of the same small diameter, allowing for a larger area of drug distribution in the target implantation region with minimal invasiveness,” explains team member Khalil Ramadi. “This helical shape also allows us to resist buckling on insertion, which is a major problem for miniaturized straight catheters.”

Helical catheter

Based on their simulations, the team fabricated a helical catheter the call Strategic Precision Infusion for Regional Administration of Liquid, or SPIRAL. In their first set of experiments, they tested their simulations in controlled lab conditions. They verified their prediction of even outflow rates across the catheter’s outlets.

“Our helical device was also tested in mouse models alongside its straight counterpart to study its neuroinflammatory response,” Khlaifat says. “There were no significant differences between the two designs.”

Having validated the safety of their approach, the researchers are now hopeful that SPIRAL could pave the way for new and improved methods for targeted drug delivery within the brain. With the ability to target entire regions of the brain with smaller, more controlled doses, this future generation of implanted catheters could ultimately prove to be both safer and more effective than existing designs.

“These catheters could be optimized for each patient through our computational framework to ensure only regions that require dosing are exposed to therapy, all through a single insertion point in the skull,” describes team member Mahmoud Elbeh. “This tailored approach could improve therapies for brain disorders such as epilepsy and glioblastomas.”

The research is described in the Journal of Neural Engineering.

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From quantum utility today to quantum advantage tomorrow: incumbent technology companies – among them Google, Amazon, IBM and Microsoft – and a wave of ambitious start-ups are on a mission to transform quantum computing from applied research endeavour to mainstream commercial opportunity. The end-game: quantum computers that can be deployed at-scale to perform computations significantly faster than classical machines while addressing scientific, industrial and commercial problems beyond the reach of today’s high-performance computing systems.

Meanwhile, as technology translation gathers pace across the quantum supply chain, government laboratories and academic scientists must maintain their focus on the “hard yards” of precompetitive research. That means prioritizing foundational quantum hardware and software technologies, underpinned by theoretical understanding, experimental systems, device design and fabrication – and pushing out along all these R&D pathways simultaneously.

Bringing order to disorder

Equally important is the requirement to understand and quantify the relative performance of quantum computers from different manufacturers as well as across the myriad platform technologies – among them superconducting circuits, trapped ions, neutral atoms as well as photonic and semiconductor processors. A case study in this regard is a broad-scope UK research collaboration that, for the past four years, has been reviewing, collecting and organizing a holistic taxonomy of metrics and benchmarks to evaluate the performance of quantum computers against their classical counterparts as well as the relative performance of competing quantum platforms.

Funded by the National Quantum Computing Centre (NQCC), which is part of the UK National Quantum Technologies Programme (NQTP), and led by scientists at the National Physical Laboratory (NPL), the UK’s National Metrology Institute, the cross-disciplinary consortium has taken on an endeavour that is as sprawling as it is complex. The challenge lies in the diversity of quantum hardware platforms in the mix; also the emergence of two different approaches to quantum computing – one being a gate-based framework for universal quantum computation, the other an analogue approach tailored to outperforming classical computers on specific tasks.

“Given the ambition of this undertaking, we tapped into a deep pool of specialist domain knowledge and expertise provided by university colleagues at Edinburgh, Durham, Warwick and several other centres-of-excellence in quantum,” explains Ivan Rungger, a principal scientist at NPL, professor in computer science at Royal Holloway, University of London, and lead scientist on the quantum benchmarking project. That core group consulted widely within the research community and with quantum technology companies across the nascent supply chain. “The resulting study,” adds Rungger, “positions transparent and objective benchmarking as a critical enabler for trust, comparability and commercial adoption of quantum technologies, aligning closely with NPL’s mission in quantum metrology and standards.”

Not all metrics are equal – or mature

For context, a number of performance metrics used to benchmark classical computers can also be applied directly to quantum computers, such as the speed of operations, the number of processing units, as well as the probability of errors to occur in the computation. That only goes so far, though, with all manner of dedicated metrics emerging in the past decade to benchmark the performance of quantum computers – ranging from their individual hardware components to entire applications.

Complexity reigns, it seems, and navigating the extensive literature can prove overwhelming, while the levels of maturity for different metrics varies significantly. Objective comparisons aren’t straightforward either – not least because variations of the same metric are commonly deployed; also the data disclosed together with a reported metric value is often not sufficient to reproduce the results.

“Many of the approaches provide similar overall qualitative performance values,” Rungger notes, “but the divergence in the technical implementation makes quantitative comparisons difficult and, by extension, slows progress of the field towards quantum advantage.”

The task then is to rationalize the metrics used to evaluate the performance for a given quantum hardware platform to a minimal yet representative set agreed across manufacturers, algorithm developers and end-users. These benchmarks also need to follow some agreed common approaches to fairly and objectively evaluate quantum computers from different equipment vendors.

With these objectives in mind, Rungger and colleagues conducted a deep-dive review that has yielded a comprehensive collection of metrics and benchmarks to allow holistic comparisons of quantum computers, assessing the quality of hardware components all the way to system-level performance and application-level metrics.

Drill down further and there’s a consistent format for each metric that includes its definition, a description of the methodology, the main assumptions and limitations, and a linked open-source software package implementing the methodology. The software transparently demonstrates the methodology and can also be used in practical, reproducible evaluations of all metrics.

“As research on metrics and benchmarks progresses, our collection of metrics and the associated software for performance evaluation are expected to evolve,” says Rungger. “Ultimately, the repository we have put together will provide a ‘living’ online resource, updated at regular intervals to account for community-driven developments in the field.”

From benchmarking to standards

Innovation being what it is, those developments are well under way. For starters, the importance of objective and relevant performance benchmarks for quantum computers has led several international standards bodies to initiate work on specific areas that are ready for standardization – work that, in turn, will give manufacturers, end-users and investors an informed evaluation of the performance of a range of quantum computing components, subsystems and full-stack platforms.

What’s evident is that the UK’s voice on metrics and benchmarking is already informing the collective conversation around standards development. “The quantum computing community and international standardization bodies are adopting a number of concepts from our approach to benchmarking standards,” notes Deep Lall, a quantum scientist in Rungger’s team at NPL and lead author of the study. “I was invited to present our work to a number of international standardization meetings and scientific workshops, opening up widespread international engagement with our research and discussions with colleagues across the benchmarking community.”

He continues: “We want the UK effort on benchmarking and metrics to shape the broader international effort. The hope is that the collection of metrics we have pulled together, along with the associated open-source software provided to evaluate them, will guide the development of standardized benchmarks for quantum computers and speed up the progress of the field towards practical quantum advantage.”

That’s a view echoed – and amplified – by Cyrus Larijani, NPL’s head of quantum programme. “As we move into the next phase of NPL’s quantum strategy, the importance of evidence-based decision making becomes ever-more critical,” he concludes. “By grounding our strategic choices in robust measurement science and real-world data, we ensure that our innovations not only push the boundaries of quantum technology but also deliver meaningful impact across industry and society.”

Further reading

Deep Lall et al. 2025 A  review and collection of metrics and benchmarks for quantum computers: definitions, methodologies and software https://arxiv.org/abs/2502.06717

End note: NPL retains copyright on this article.

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The microelectronics sector is known for its relentless drive for innovation, continually delivering performance and efficiency gains within ever more compact form factors. Anyone aspiring to build a career in this fast-moving field needs not just a thorough grounding in current tools and techniques, but also an understanding of the next-generation materials and structures that will propel future progress.

That’s the premise behind a Master’s programme in microelectronics technology and materials at the Hong Kong Polytechnic University (PolyU). Delivered by the Department for Applied Physics, globally recognized for its pioneering research in technologies such as two-dimensional materials, nanoelectronics and artificial intelligence, the aim is to provide students with both the fundamental knowledge and practical skills they need to kickstart their professional future – whether they choose to pursue further research or to find a job in industry.

“The programme provides students with all the key skills they need to work in microelectronics, such as circuit design, materials processing and failure analysis,” says programme leader Professor Zhao Jiong, who research focuses on 2D ferroelectrics. “But they also have direct access to more than 20 faculty members who are actively investigating novel materials and structures that go beyond silicon-based technologies.”

The course in also unusual in providing a combined focus on electronics engineering and materials science, providing students with a thorough understanding of the underlying semiconductors and device structures as well as their use in mass-produced integrated circuits. That fundamental knowledge is reinforced through regular experimental work, providing the students with hands-on experience of fabricating and testing electronic devices. “Our cleanroom laboratory is equipped with many different instruments for microfabrication, including thin-film deposition, etching and photolithography, as well as advanced characterization tools for understanding their operating mechanisms and evaluating their performance,” adds Zhao.

In a module focusing on thin-film materials, for example, students gain valuable experience from practical sessions that enable them to operate the equipment for different growth techniques, such as sputtering, molecular beam epitaxy, and both physical and chemical vapour deposition. In another module on materials analysis and characterization, the students are tasked with analysing the layered structure of a standard computer chip by making cross-sections that can be studied with a scanning electron microscope.

That practical experience extends to circuit design, with students learning how to use state-of-the-art software tools for configuring, simulating and analysing complex electronic layouts. “Through this experimental work students gain the technical skills they need to design and fabricate integrated circuits, and to optimize their performance and reliability through techniques like failure analysis,” says Professor Dai Jiyan, PolyU Associate Dean of Students, who also teaches the module on thin-film materials. “This hands-on experience helps to prepare them for working in a manufacturing facility or for continuing their studies at the PhD level.”

Also integrated into the teaching programme is the use of artificial intelligence to assist key tasks, such as defect analysis, materials selection and image processing. Indeed, PolyU has established a joint laboratory with Huawei to investigate possible applications of AI tools in electronic design, providing the students with early exposure to emerging computational methods that are likely to shape the future of the microelectronics industry. “One of our key characteristics is that we embed AI into our teaching and laboratory work,” says Dai. “Two of the modules are directly related to AI, while the joint lab with Huawei helps students to experiment with using AI in circuit design.”

Now in its third year, the Master’s programme was designed in collaboration with Hong Kong’s Applied Science and Technology Research Institute (ASTRI), established in 2000 to enhance the competitiveness of the region through the use of advanced technologies. Researchers at PolyU already pursue joint projects with ASTRI in areas like chip design, microfabrication and failure analysis. As part of the programme, these collaborators are often invited to give guest lectures or to guide the laboratory work. “Sometimes they even provide some specialized instruments for the students to use in their experiments,” says Zhao. “We really benefit from this collaboration.”

Once primed with the knowledge and experience from the taught modules, the students have the opportunity to work alongside one of the faculty members on a short research project. They can choose whether to focus on a topic that is relevant to present-day manufacturing, such as materials processing or advanced packaging technologies, or to explore the potential of emerging materials and devices across applications ranging from solar cells and microfluidics to next-generation memories and neuromorphic computing.

“It’s very interesting for the students to get involved in these projects,” says Zhao. “They learn more about the research process, which can make them more confident to take their studies to the next level. All of our faculty members are engaged in important work, and we can guide the students towards a future research field if that’s what they are interested in.”

There are also plenty of progression opportunities for those who are more interested in pursuing a career in industry. As well as providing support and advice through its joint lab in AI, Huawei arranges visits to its manufacturing facilities and offers some internships to interested students. PolyU also organizes visits to Hong Kong’s Science Park, home to multinational companies such as Infineon as well as a large number of start-up companies in the microelectronics sector. Some of these might support a student’s research project, or offer an internship in areas such as circuit design or microfabrication.

The international outlook offered by PolyU has made the Master’s programme particularly appealing to students from mainland China, but Zhao and Dai believe that the forward-looking ethos of the course should make it an appealing option for graduates across Asia and beyond. “Through the programme, the students gain knowledge about all aspects of the microelectronics industry, and how it is likely to evolve in the future,” says Dai. “The knowledge and technical skills gained by the students offer them a competitive edge for building their future career, whether they want to find a job in industry or to continue their research studies.”

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NASA’s Jet Propulsion Laboratory (JPL) is to lay off some 550 employees as part of a restructuring that began in July. The action affects about 11% of JPL’s employees and represents the lab’s third downsizing in the past 20 months. When the layoffs are complete by the end of the year, the lab will have roughly 4500 employees, down from about 6500 at the start of 2024. A further 4000 employees have already left NASA during the past six months via sacking, retirement or voluntary buyouts.

Managed by the California Institute of Technology in Pasadena, JPL oversees scientific missions such as the Psyche asteroid probe, the Europa Clipper and the Perseverance rover on Mars. The lab also operates the Deep Space Network that keeps Earth in communication with unmanned space missions. JPL bosses already laid off about 530 staff – and 140 contractors – in February last year followed by another 325 people in November 2024.

JPL director Dave Gallagher insists, however, that the new layoffs are not related to the current US government shutdown that began on 1 October. “[They are] essential to securing JPL’s future by creating a leaner infrastructure, focusing on our core technical capabilities, maintaining fiscal discipline, and positioning us to compete in the evolving space ecosystem,” he says in a message to employees.

Judy Chu, Democratic Congresswoman for the constituency that includes JPL, is less optimistic. “Every layoff devastates the highly skilled and uniquely talented workforce that has made these accomplishments possible,” she says. “Together with last year’s layoffs, this will result in an untold loss of scientific knowledge and expertise that threatens the very future of American leadership in space exploration and scientific discovery.”

John Logsdon, professor emeritus at George Washington University and founder of the university’s Space Policy Institute, says that the cuts are a direct result of the Trump administration’s approach to science and technology. “The administration gives low priority to robotic science and exploration, and has made draconic cuts to the science budget; that budget supports JPL’s work,” he told Physics World. “With these cuts, there is not enough money to support a JPL workforce sized for more ambitious activities. Ergo, staff cuts.”

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I hugely enjoyed physics when I was a youngster. I had the opportunity both at home and school to create my own projects, which saw me make electronic circuits, crazy flying models like delta-wings and autogiros, and even a gas chromatograph with a home-made chart recorder. Eventually, this experience made me good enough to repair TV sets, and work in an R&D lab in the holidays devising new electronic flow controls.

That enjoyment continued beyond school. I ended up doing a physics degree at the University of Oxford before working on the discovery of the gluon at the DESY lab in Hamburg for my PhD. Since then I have used physics in industry – first with British Oxygen/Linde and later with Air Products & Chemicals – to solve all sorts of different problems, build innovative devices and file patents.

While some students have a similarly positive school experience and subsequent career path, not enough do. Quite simply, physics at school is the key to so many important, useful developments, both within and beyond physics. But we have a physics education problem, or to put it another way – a “future of physics” problem.

There are just not enough school students enjoying and learning physics. On top of that there are not enough teachers enjoying physics and not enough students doing practical physics. The education problem is bad for physics and for many other subjects that draw on physics. Alas, it’s not a new problem but one that has been developing for years.

Problem solving

Many good points about the future of physics learning were made by the Institute of Physics in its 2024 report Fundamentals of 11 to 19 Physics. The report called for more physics lessons to have a practical element and encouraged more 16-year-old students in England, Wales and Northern Ireland to take AS-level physics at 17 so that they carry their GCSE learning at least one step further.

Doing so would furnish students who are aiming to study another science or a technical subject with the necessary skills and give them the option to take physics A-level. Another recommendation is to link physics more closely to T-levels – two-year vocational courses in England for 16–19 year olds that are equivalent to A-levels – so that students following that path get a background in key aspects of physics, for example in engineering, construction, design and health.

But do all these suggestions solve the problem? I don’t think they are enough and we need to go further. The key change to fix the problem, I believe, is to have student groups invent, build and test their own projects. Ideally this should happen before GCSE level so that students have the enthusiasm and background knowledge to carry them happily forward into A-level physics. They will benefit from “pull learning” – pulling in knowledge and active learning that they will remember for life. And they will acquire wider life skills too.

Developing skillsets

During my time in industry, I did outreach work with schools every few weeks and gave talks with demonstrations at the Royal Institution and the Franklin Institute. For many years I also ran a Saturday Science club in Guildford, Surrey, for pupils aged 8–15.

Based on this, I wrote four Saturday Science books about the many playful and original demonstrations and projects that came out of it. Then at the University of Surrey, as a visiting professor, I had small teams of final-year students who devised extraordinary engineering – designing superguns for space launches, 3D printers for full-size buildings and volcanic power plants inter alia. A bonus was that other staff working with the students got more adventurous too.

But that was working with students already committed to a scientific path. So lately I’ve been working with teachers to get students to devise and build their own innovative projects. We’ve had 14–15-year-old state-school students in groups of three or four, brainstorming projects, sketching possible designs, and gathering background information. We help them and get A-level students to help too (who gain teaching experience in the process). Students not only learn physics better but also pick up important life skills like brainstorming, team-working, practical work, analysis and presentations.

We’ve seen lots of ingenuity and some great projects such as an ultrasonic scanner to sense wetness of cloth; a system to teach guitar by lighting up LEDs along the guitar neck; and measuring breathing using light passing through a band of Lycra around the patient below the ribs. We’ve seen the value of failure, both mistakes and genuine technical problems.

Best of all, we’ve also noticed what might be dubbed the “combination bonus” – students having to think about how they combine their knowledge of one area of physics with another.  A project involving a sensor, for example, will often involve electronics as well the physics of the sensor and so student knowledge of both areas is enhanced.

Some teachers may question how you mark such projects. The answer is don’t mark them! Project work and especially group work is difficult to mark fairly and accurately, and the enthusiasm and increased learning by students working on innovative projects will feed through into standard school exam results.

Not trying to grade such projects will mean more students go on to study physics further, potentially to do a physics-related extended project qualification – equivalent to half an A-level where students research a topic to university level – and do it well. Long term, more students will take physics with them into the world of work, from physics to engineering or medicine, from research to design or teaching.

Such projects are often fun for students and teachers. Teachers are often intrigued and amazed by students’ ideas and ingenuity. So, let’s choose to do student-invented project work at school and let’s finally solve the future of physics problem.

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As a teenager in her native Rio Grande do Sul, a state in Southern Brazil, Thaisa Storchi Bergmann enjoyed experimenting in an improvised laboratory her parents built in their attic. They didn’t come from a science background – her father was an accountant, her mother a primary school teacher – but they encouraged her to do what she enjoyed. With a friend from school, Storchi Bergmann spent hours looking at insects with a microscope and running experiments from a chemistry toy kit. “We christened the lab Thasi-Cruz after a combination of our names,” she chuckles.

At the time, Storchi Bergmann could not have imagined that one day this path would lead to cosmic discoveries and international recognition at the frontiers of astrophysics. “I always had the curiosity inside me,” she recalls. “It was something I carried since adolescence.”

That curiosity almost got lost to another discipline. By the time Storchi Bergmann was about to enter university, she was swayed by a cousin living with her family who was passionate about architecture. By 1974 she began studying architecture at the Federal University of Rio Grande do Sul (UFRGS). “But I didn’t really like technical drawing. My favourite part of the course were physics classes,” she says. Within a semester, she switched to physics.

There she met Edemundo da Rocha Vieira, the first astrophysicist UFRGS ever hired – who later went on to structure the university’s astronomy department. He nurtured Storchi Bergmann’s growing fascination with the universe and introduced her to research.

In 1977, newly married after graduation, Storchi Bergmann followed her husband to Rio de Janeiro, where she did a master’s degree and worked with William Kunkel, an American astronomer who was in Rio to help establish Brazil’s National Astrophysics Laboratory. She began working on data from a photometric system to measure star radiation. “But Kunkel said galaxies were a lot more interesting to study, and that stuck in my head,” she says.

Three years after moving to Rio, she returned to Porto Alegre, in Rio Grande do Sul, to start her doctoral research and teach at UFRGS. Vital to her career was her decision to join the group of Miriani Pastoriza, one of the pioneers of extragalactic astrophysics in Latin America. “She came from Argentina, where [in the late 1970s and early 1980s] scientists were being strongly persecuted [by the country’s military dictatorship] at the time,” she recalls. Pastoriza studied galaxies with “peculiar nuclei” – objects later known to harbour supermassive black holes. Under Pastoriza’s guidance, she moved from stars to galaxies, laying the foundation for her career.

Between 1986 and 1987, Storchi Bergmann often travelled to Chile to make observations and gather data for her PhD, using some of the largest telescopes available at the time. Then came a transformative period – a postdoc fellowship in Maryland, US, just as the Hubble Space Telescope was launched in 1990. “Each Thursday, I would drive to Baltimore for informal bag-lunch talks at the Space Telescope Science Institute, absorbing new results on active galactic nuclei (AGN) and supermassive black holes,” Storchi Bergmann recalls.

Discoveries and insights

In 1991, during an observing campaign, she and a collaborator saw something extraordinary in the galaxy NGC 1097: gas moving at immense speeds, captured by the galaxy’s central black hole. The work, published in 1993, became one of the earliest documented cases of what are now called “tidal disruption events”, in which a star or cloud gets too close to a black hole and is torn apart.

Her research also contributed to one of the defining insights of the Hubble era: that every massive galaxy hosts a central black hole. “At first, we didn’t know if they were rare,” she explains. “But gradually it became clear: these objects are fundamental to galaxy evolution.”

Another collaboration brought her into contact with Daniela Calzetti, whose work on the effects of interstellar dust led to the formulation of the widely used “Calzetti law”. These and other contributions placed Storchi Bergmann among the most cited scientists worldwide, recognition of which came in 2015 when she received the L’Oréal-UNESCO Award for Women in Science.

Her scientific achievements, however, unfolded against personal and structural obstacles. As a young mother, she often brought her baby to observatories and conferences so she could breastfeed. This kind of juggling is no stranger to many women in science.

“It was never easy,” Storchi Bergmann reflects. “I was always running, trying to do 20 things at once.” The lack of childcare infrastructure in universities compounded the challenge. She recalls colleagues who succeeded by giving up on family life altogether. “That is not sustainable,” she insists. “Science needs all perspectives – male, female and everything in-between. Otherwise, we lose richness in our vision of the universe.”

When she attended conferences early in her career, she was often the only woman in the room. Today, she says, the situation has greatly improved, even if true equality remains distant.

Now a tenured professor at UFRGS and a member of the Brazilian Academy of Sciences, Storchi Bergmann continues to push at the cosmic frontier. Her current focus is the Legacy Survey of Space and Time (LSST), about to begin at the Vera Rubin Observatory in Chile.

Her group is part of the AGN science collaboration, developing methods to analyse the characteristic flickering of accreting black holes. With students, she is experimenting with automated pipelines and artificial intelligence to make sense of and manage the massive amounts of data.

Challenges ahead

Yet this frontier science is not guaranteed. Storchi Bergmann is frustrated by the recent collapse in research scholarships. Historically, her postgraduate programme enjoyed a strong balance of grants from both of Brazil’s federal research funding agencies, CNPq (from the Ministry of Science) and CAPES (from the Ministry of Education). But cuts at CNPq, she says, have left students without support, and CAPES has not filled the gap.

“The result is heartbreaking,” she says. “I have brilliant students ready to start, including one from Piauí (a state in north-eastern Brazil), but without a grant, they simply cannot continue. Others are forced to work elsewhere to support themselves, leaving no time for research.”

She is especially critical of the policy of redistributing scarce funds away from top-rated programmes to newer ones without expanding the overall budget. “You cannot build excellence by dismantling what already exists,” she argues.

For her, the consequences go beyond personal frustration. They risk undermining decades of investment that placed Brazil on the international astrophysics map. Despite these challenges, Storchi Bergmann remains driven and continues to mentor master’s and PhD students, determined to prepare them for the LSST era.

At the heart of her research is a question as grand as any in cosmology: which came first – the galaxy or its central black hole? The answer, she believes, will reshape our understanding of how the universe came to be. And it will carry with it the fingerprint of her work: the persistence of a Brazilian scientist who followed her curiosity from a home-made lab to the centres of galaxies, overcoming obstacles along the way.

The post ‘Science needs all perspectives – male, female and everything in-between’: Brazilian astronomer Thaisa Storchi Bergmann appeared first on Physics World.

Homes and cities around the world are this week celebrating Diwali or Deepavali – the Indian “festival of lights”. For Indian physicist Rupamanjari Ghosh, who is the former vice chancellor of Shiv Nadar University Delhi-NCR, this festival sheds light on the quantum world. Known for her work on nonlinear optics and entangled photons, Ghosh finds a deep resonance between the symbolism of Diwali and the ongoing revolution in quantum science.

“Diwali comes from Deepavali, meaning a ‘row of lights’. It marks the triumph of light over dark; good over evil; and knowledge over ignorance,” Ghosh explains. “In science too, every discovery is a Diwali –  a victory of knowledge over ignorance.”

With 2025 being marked by the International Year of Quantum Science and Technology, a victory of knowledge over ignorance couldn’t ring truer. “It has taken us a hundred years since the birth of quantum mechanics to arrive at this point, where quantum technologies are poised to transform our lives,” says Ghosh.

Ghosh has another reason to celebrate, having been named as this year’s Institute of Physics (IOP) Homi Bhabha lecturer. The IOP and the Indian Physical Association (IPA) jointly host the Homi Bhabha and Cockcroft Walton bilateral exchange of lecturers. Running since 1998, these international programmes aim to promote dialogue on global challenges through physics and provide physicists with invaluable opportunities for global exposure and professional growth. Ghosh’s online lecture, entitled “Illuminating quantum frontiers: from photons to emerging technologies”, will be aired at 3 p.m. GMT on Wednesday 22 October.

From quantum twins to quantum networks

Ghosh’s career in physics took off in the mid-1980s, when she and American physicist Leonard Mandel – who is often referred to as one of the founding fathers of quantum optics – demonstrated a new quantum source of twin photons through spontaneous parametric down-conversion: a process where a high-energy photon splits into two lower-energy, correlated photons (Phys. Rev. Lett. 59, 1903).

“Before that,” she recalls, “no-one was looking for quantum effects in this nonlinear optical process. The correlations between the photons defied classical explanation. It was an elegant early verification of quantum nonlocality.”

Those entangled photon pairs are now the building blocks of quantum communication and computation. “We’re living through another Diwali of light,” she says, “where theoretical understanding and experimental innovation illuminate each other.”

Entangled light

During Diwali, lamps unite households in a shimmering network of connection,  and so too does entanglement of photons. “Quantum entanglement reminds us that connection transcends locality,” Ghosh says. “In the same way, the lights of Diwali connect us across borders and cultures through shared histories.”

Her own research extends that metaphor further. Ghosh’s team has worked on mapping quantum states of light onto collective atomic excitations. These “slow-light” techniques –  using electromagnetically induced transparency or Raman interactions –  allow photons to be stored and retrieved, forming the backbone of long-distance quantum communication (Phys. Rev. A. 88 023852, EPL 105 44002)

“Symbolically,” she adds, “it’s like passing the flame from one diya (lamp) to another. We’re not just spreading light –  we’re preserving, encoding and transmitting it. Success comes through connection and collaboration.”

The dark side of light

Ghosh is quick to note that in quantum physics, “darkness” is far from empty. “In quantum optics, even the vacuum is rich –  with fluctuations that are essential to our understanding of the universe.”

Her group studies the transition from quantum to classical systems, using techniques such as error correction, shielding and coherence-preserving materials. “Decoherence –  the loss of quantum behaviour through environmental interaction –  is a constant threat. To build reliable quantum technologies, we must engineer around this fragility,” Ghosh explains.

There are also human-engineered shadows: some weaknesses in quantum communication devices aren’t due to the science itself – they come from mistakes or flaws in how humans built them. Hackers can exploit these “side channels” to get around security. “Security,” she warns, “is only as strong as the weakest engineering link.”

Beyond the lab, Ghosh finds poetic meaning in these challenges. “Decoherence isn’t just a technical problem –  it helps us understand the arrows of time, why the universe evolves irreversibly. The dark side has its own lessons.”

Lighting every corner

For Ghosh, Diwali’s illumination is also a call for inclusivity in science. “No corner should remain dark,” she says. “Science thrives on diversity. Diverse teams ask broader questions and imagine richer answers. It’s not just morally right – it’s good for science.”

She argues that equity is not sameness but recognition of uniqueness. “Innovation doesn’t come from conformity. Gender diversity, for example, brings varied cognitive and collaborative styles – essential in a field like quantum science, where intuition is constantly stretched.”

The shadows she worries most about are not in the lab, but in academia itself. “Unconscious biases in mentorship or gatekeeping in opportunity can accumulate to limit visibility. Institutions must name and dismantle these hidden shadows through structural and cultural change.”

Her vision of inclusion extends beyond gender. “We shouldn’t think of work and life as opposing realms to ‘balance’,” she says. “It’s about creating harmony among all dimensions of life – work, family, learning, rejuvenation. That’s where true brilliance comes from.”

As the rows of diyas are lit this Diwali, Ghosh’s reflections remind us that light –  whether classical or quantum –  is both a physical and moral force: it connects, illuminates and endures. “Each advance in quantum science,” she concludes, “is another step in the age-old journey from darkness to light.”

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