Researchers at the SLAC National Accelerator Laboratory in the US have produced the world’s most powerful ultrashort electron beam to date, concentrating petawatt-level peak powers into femtosecond-long pulses at an energy of 10 GeV and a current of around 0.1 MA. According to officials at SLAC’s Facility for Advanced Accelerator Experimental Tests (FACET-II), the new beam could be used to study phenomena in materials science, quantum physics and even astrophysics that were not accessible before.
High-energy electron beams are routinely employed as powerful probes in several scientific fields. To produce them, accelerator facilities like SLAC use strong electric fields to accelerate, focus and compress bunches of electrons. This is not easy, because as electrons are accelerated and compressed, they emit radiation and lose energy, causing the beam’s quality to deteriorate.
An optimally compressed beam
To create their super-compressed ultrashort beam, researchers led by Claudio Emma at FACET-II used a laser to shape the electron bunch’s profile with millimetre-scale precision in the first 10 metres of the accelerator, when the beam’s energy is lowest. They then took this modulated electron beam and boosted its energy by a factor of 100 in a kilometre-long stretch of downstream accelerating cavities. The last step was to compress the beam by a factor of 1000 by using magnets to turn the beam’s millimetre-scale features into a micron-sized long current spike.
One of the biggest challenges, Emma says, was to optimise the laser-based modulation of the beam in tandem with the accelerating cavity and magnetic fields of the magnets to obtain the optimally compressed beam at the end of the accelerator. “This was a large parameter space to work in with lots of knobs to turn and it required careful iteration before an optimum was found,” Emma says.
Measuring the ultra-short electron bunches was also a challenge. “These are typically so intense that if you intercept them with, for example, scintillating screens (a typical technique used in accelerators to diagnose properties of the beam like its spot size or bunch length), the beam fields are so strong they can melt these screens,” Emma explains. “To overcome this, we had to use a series of indirect measurements (plasma ionisation and beam-based radiation) along with simulations to diagnose just how strongly compressed and powerful these beams were.”
Beam delivery
According to Emma, generating extremely compressed electron beams is one of the most important challenges facing accelerator and beam physicists today. “It was interesting for us to tackle this challenge at FACET-II, which is a facility designed specifically to do this kind of research on extreme beam manipulation,” he says.
The team has already delivered the new high-current beams to experimenters who work on probing and optimising the dynamics of plasma-based accelerators. Further down the line, they anticipate much wider applications. “In the future we imagine that we will attract interest from users in multiple fields, be they materials scientists, strong-field quantum physicists or astrophysicists, who want to use the beam as a strong relativistic ‘hammer’ to study and probe a variety of natural interactions with the unique tool that we can provide,” Emma tells Physics World.
The researchers’ next step will be to increase the beam’s current by another order of magnitude. “This additional leap will require the use of a different plasma-based compression technique, rather than the current laser-based approach, which we hope to demonstrate at FACET-II in the near future,” Emma reveals.
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Classical vs quantum Mpemba: a) In the classical strong Mpemba effect (sME), the overlap with the slowest decay mode (SDM) drops as the temperature increases until it reaches zero at Ts, the point at which the Mpemba effect is maximized. The overlap then increases as the temperature increases further. With a weak ME, if the overlap between the SDM and the initial state with high temperature TH is smaller than the overlap with the lower-temperature state Tc, the system can reach equilibrium faster. When the ME is strong, the overlap between Ts and SMD is zero, and the system reaches the equilibrium exponentially faster. With no ME, the overlap between the TH state and SDM is at a maximum; therefore, the system reaches the equilibrium more slowly. b) Paths taken by the system when reaching the stationary state. While the system decaying from the normal or weak ME states reaches the stationary state, decay from the sME state follows a straight line to reach equilibrium, implying this is the fastest path. c) Three-energy-level system involved in obtaining the sME. d) Distance vs time on a logarithmic scale. States |2> and |0> exhibit similar slow relaxation rates, whereas the sME state exhibits a fast exponential decay rate when reaching equilibrium. (Courtesy: Hui Jing)
Researchers from China, the UK and Singapore have demonstrated for the first time that choosing the right set of initial conditions can speed up the relaxation process in quantum systems. Their experiments using single trapped ions are a quantum analogue of the classical Mpemba effect, in which hot water can, under certain circumstances, cool faster than cold water. By showing that it is possible to exponentially accelerate the relaxation of a pure state into a stationary state – the hallmark of the so-called strong Mpemba effect – they also provide strategies for designing and analysing open quantum systems such as those used in quantum batteries.
In both the classical and the quantum worlds, the difference between the relaxation process of a system in a strong Mpemba effect (sME) state and any other state is that the decay rate of a sME state is greater than the others. This naturally leads to the conclusion that initial conditions influence the speed at which a system will reach equilibrium. However, the mathematics of the quantum and classical sME are different. While in the classical world an open system is described by the Fokker-Planck equation, with the temperature as the key variable, in the quantum world the Lindblad master equation applies, and the energy of the sME state is what matters.
Paths and overlap
To understand why a quantum system in a particular initial state reaches a steady state faster than any other, we should think about the possible paths that a system can take. One key path is known as the slowest decay mode (SDM), which is the path that takes the system the most time to decay. At the other extreme, the fastest relaxation path is the one taken by a system in the sME initial state. This relaxation path must avoid any overlap with the SDM’s path.
Hui Jing, a physicist at China’s Hunan Normal University who co-led the study, points out that a fundamental characteristic of the quantum sME is that its relaxation path includes the so-called Liouvillian exceptional point (LEP). At this point, an eigenvalue of the dynamical generator, which is the Liovillian superoperator that describes the time evolution of the open quantum system through the Lindblad master equation, changes from real to complex. When the eigenvalue of the SDM is real, the system is successfully prepared in the sME. When the eigenvalue of the SDM acquires an imaginary part, the overlap between the prepared sME state and the SDM is no longer zero. The LEP therefore signals the transition from strong to weak Mpemba effect.
Experimental set-up
To create a pure state that presents zero overlap with the SDM in an open quantum system, Jing and colleagues trapped a 40Ca+ ion and coupled three of its energy levels through laser interactions. The first laser beam, with a wavelength of 729 nm, coupled the ground state with the two excited states with coupling strengths characterized by Rabi frequencies Ω1 and Ω2. A second, circularly polarized laser beam at 854 nm controlled the decay between the first excited state and the ground state.
By tuning the Rabi frequencies, researchers were able to explore different relaxation regimes of the system. When the ratio between the Rabi frequencies was much smaller or bigger than the LEP, they observed the sME and weak ME, respectively. When the ratio equalled the LEP, the transition from sME to weak ME took place.
This work, which is described in Nature Communications, marks the first experimental realization of the quantum strong Mpemba effect. According to Jing, the team’s methods offer an experimental alternative to existing ways of increasing the ion cooling rate or enhancing the efficiency of quantum batteries. Now, the group plans to study how the quantum Mpemba effect behaves at the LEP, since this point could lead to faster decay rates.
“Fusion is now within reach” and represents “one of the economic opportunities of the century”. Not the words of an optimistic fusion scientist but from Kerry McCarthy, parliamentary under-secretary of state at the UK’s Department for Energy Security and Net Zero.
She was speaking on Tuesday at the inaugural Fusion Fest by Economist Impact. Held in London, the day-long event featured 400 attendees and more than 60 speakers from around the world.
McCarthy outlined several initiatives to keep the UK at the “forefront of fusion”. That includes investing £20m into Starmaker One, a £100m endeavour announced in early April to kickstart UK investment fusion fund.
The usual cliché is that fusion is always being 20 years away, perhaps not helped by large international projects such as the ITER experimental fusion reactor that is currently being built in Cadarache, France, which has struggling with delays and cost hikes.
Yet many delegates at the meeting were optimistic that significant developments are within reach with private firms racing to demonstrate “breakeven” – generating more power out than needed to fuel the reaction. Some expect “a few” private firms to announce breakeven by 2030.
And these aren’t small ventures. Commonwealth Fusion Systems, based in Massachusetts, US, for example, has 1300 people. Yet large international companies are, for the moment, only dipping their toe into the fusion pool.
While some $8bn has already been spent by private firms on fusion, many expect the funding floodgates to open once breakeven has been achieved in a private lab.
Most stated that a figure of about $50-60bn, however, would be needed to make fusion a real endeavour in terms of delivering power to the grid, something that could happen in the 2040s. But it was reiterated throughout the day that fusion must provide energy at a price that consumers would be willing to pay.
On target
It is not only private firms that are making progress. Many will point out that ITER has laid much of the groundwork in terms of fostering a fusion “ecosystem” – a particular buzzword of the day – that was demonstrated, in part, by the significant attendence at the event.
In a recent shot, she said that the device had produced 7 MJ with about 2 MJ having been delivered to the small capsule target. This represents a gain of about 3.4 – much more than its previous record of 2.4.
NIF, which is based on inertial confinement fusion rather than magnetic confinement, is currently undergoing refurbishment and upgrades. It is hoped that this will increase the energy input to about 2.6 MJ but gains of between 10-15 will be demonstrated if the technique can go anywhere.
Despite the number of fusion firms ballooning from a handful in the early 2010s to some 30 today, the general feeling at the meeting was that only a few will likely go on to build power plants, with the remainder using fusion for other sectors.
The issue is that no-one knew what technology would likely succeed, so all to play for.
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This episode of the Physics World Weekly podcast features an interview with Panicos Kyriacou, who is chief scientist at the UK-based start-up Crainio. The company has developed a non-invasive way of using light to measure the pressure inside the skull. Knowing this intracranial pressure is crucial when diagnosing traumatic brain injury, which a leading cause of death and disability. Today, the only way to assess intracranial pressure is to insert a sensor into the patient’s brain, so Crainio’s non-invasive technique could revolutionize how brain injuries are diagnosed and treated.
Kyriacou tells Physics World’s Tami Freeman why it is important to assess a patient’s intracranial pressure as soon as possible after a head injury. He explains how Crainio’s optical sensor measures blood flow in the brain and then uses machine learning to deduce the intracranial pressure.
Kyriacou is also professor of engineering at City St George’s University of London, where the initial research for the sensor was done. He recalls how Crainio was spun out of the university and how it is currently in a second round of clinical trials.
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Andrew Martin, skills policy lead at the UK’s Department for Science, Innovation and Technology (DSIT), flashed up a slide. Speaking at the ninth Careers in Quantum event in Bristol last week, he listed the eight skills that the burgeoning quantum-technology sector wants. Five are various branches of engineering, including electrical and electronics, mechanical, software and systems. A sixth is materials science and chemistry, with a seventh being quality control.
Quantum companies, of course, do also want “quantum specialists”, which was the eighth skill identified by Martin. But it’s a sign of how mature the sector has become that being a hotshot quantum physicist is no longer the only route in. That point was underlined by Carlos Faurby, a hardware integration engineer at Sparrow Quantum in Denmark, which makes single-photon sources for quantum computers. “You don’t need a PhD in physics to work at Sparrow,” Faurby declared.
Quantum tech certainly has a plethora of career options, with the Bristol event featuring a selection of firms from across the quantum ecosystem. Some are making prototype quantum computers (Quantum Motion, Quantinuum, Oxford Ionics) or writing the algorithms to run on quantum computers (Phasecraft). Others are building quantum networks (BT, Toshiba), working on quantum error correction (Riverlane) or developing quantum cryptography (KETS Quantum). Businesses building hardware such as controllers and modems were present too.
With the 2025 International Year of Quantum Science and Technology (IYQ) now in full swing, the event underlined just how thriving the sector is, with lots of career choices for physicists – whether you have a PhD or not. But competition to break in is intense. Phasecraft says it gets 50–100 applicants for each student internship it offers, with Riverlane receiving almost 200 applications for two summer placements.
That’s why it’s vital for physics students to develop their “soft skills” – or “professional skills” as several speakers preferred to call them. Team working, project management, collaboration and communication are all essential for jobs in the quantum industry, as indeed they are for all careers. Sadly, many physicists don’t realize soon enough just how crucial soft skills are.
Reflecting on his time at Light Trace Photonics, which he co-founded in 2021, Dominic Sulway joked in a panel discussion that he’d “enjoyed developing all the skills people told me I’d need for my PhD”. Of course, if you really want to break into the sector, why not follow his lead and start a business yourself? It’s a rewarding experience, I was told, and there doesn’t seem to be any slow-down in the number of quantum firms starting up.
For more information on career options for physicists, check out the free-to-read 2025 Physics World Careers guide
A quantum computer has been used for the first time to generate strings of certifiably random numbers. The protocol for doing this, which was developed by a team that included researchers at JPMorganChase and the quantum computing firm Quantinuum, could have applications in areas ranging from lotteries to cryptography – leading Quantinuum to claim it as quantum computing’s first commercial application, though other firms have made similar assertions. Separately, Quantinuum and its academic collaborators used the same trapped-ion quantum computer to explore problems in quantum magnetism and knot theory.
Genuinely random numbers are important in several fields, but classical computers cannot create them. The best they can do is to generate apparently random or “pseudorandom” numbers. Randomness is inherent in the laws of quantum mechanics, however, so quantum computers are naturally suited to random number generation. In fact, random circuit sampling – in which all qubits are initialized in a given state and allowed to evolve via quantum gates before having their states measured at the output – is often used to benchmark their power.
Of course, not everyone who wants to produce random numbers will have their own quantum computer. However, in 2023 Scott Aaronson of the University of Texas at Austin, US and his then-PhD student Shi-Han Hungsuggested that a client could send a series of pseudorandomly chosen “challenge” circuits to a central server. There, a quantum computer could perform random circuit sampling before sending the readouts to the client.
If these readouts are truly the product of random circuit sampling measurements performed on a quantum computer, they will be truly random numbers. “Certifying the ‘quantumness’ of the output guarantees its randomness,” says Marco Pistoia, JPMorganChase’s head of global technology applied research.
Importantly, this certification is something a classical computer can do. The way this works is that the client samples a subset of the bit strings in the readouts and performs a test called cross-entropy benchmarking. This test measures the probability that the numbers could have come from a non-quantum source. If the client is satisfied with this measurement, they can trust that the samples were genuinely the result of random circuit sampling. Otherwise, they may conclude that the data could have been generated by “spoofing” – that is, using a classical algorithm to mimic a quantum computer. The degree of confidence in this test, and the number of bits they are willing to settle for to achieve this confidence, is up to the client.
High-fidelity quantum computing
In the new work, Pistoia, Aaronson, Hung and colleagues sent challenge circuits to the 56-qubit Quantinuum H2-1 quantum computer over the Internet. The attraction of the Quantinuum H2-1, Pistoia explains, is its high fidelity: “Somebody could say ‘Well, when it comes to randomness, why would you care about accuracy – it’s random anyway’,” he says. “But we want to measure whether the number that we get from Quantinuum really came from a quantum computer, and a low-fidelity quantum computer makes it more difficult to ascertain that with confidence… That’s why we needed to wait all these years, because a low-fidelity quantum computer wouldn’t have given us the certification part.”
The team then certified the randomness of the bits they got back by performing cross-entropy benchmarking using four of the world’s most powerful supercomputers, including Frontier at the US Department of Energy’s Oak Ridge National Laboratory. The results showed that it would have been impossible for a dishonest adversary with similar classical computing power to spoof a quantum computer – provided the client set a short enough time limit.
One drawback is that at present, the computational cost of verifying that random numbers have not been spoofed is similar to the computational cost of spoofing them. “New work is needed to develop approaches for which the certification process can run on a regular computer,” Pistoia says. “I think this will remain an active area of research in the future.”
A more important difference, Foss-Feig argues, is that whereas the other groups used a partly analogue approach to simulating their quantum magnetic system, with all quantum gates activated simultaneously, Quantinuum’s approach divided time into a series of discrete steps, with operations following in a sequence similar to that of a classical computer. This digitization meant the researchers could perform a discrete gate operation as required, between any of the ionic qubits in their lattice. “This digital architecture is an extremely convenient way to compile a very wide range of physical problems,” Foss-Feig says. “You might think, for example, of simulating not just spins, for example, but also fermions or bosons.”
While the researchers say it would be just possible to reproduce these simulations using classical computers, they plan to study larger models soon. A 96-qubit version of their device, called Helios, is slated for launch later in 2025.
“We’ve gone through a shift”
Quantum information scientist Barry Sanders of the University of Calgary, Canada is impressed by all three works. “The real game changer here is Quantinuum’s really nice 56-qubit quantum computer,” he says. “Instead of just being bigger in its number of qubits, it’s hit multiple important targets.”
In Sanders’ view, the computer’s fully digital architecture is important for scalability, although he notes that many in the field would dispute that. The most important development, he adds, is that the research frames the value of a quantum computer in terms of its accomplishments.
“We’ve gone through a shift: when you buy a normal computer, you want to know what that computer can do for you, not how good is the transistor,” he says. “In the old days, we used to say ‘I made a quantum computer and my components are better than your components – my two-qubit gate is better’… Now we say, ‘I made a quantum computer and I’m going to brag about the problem I solved’.”
The random number generation paper is published in Nature. The others are available on the arXiv pre-print server.
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