Machine-learning could help us use cosmic muons to peer inside large objects such as nuclear reactors. Developed by researchers in China, the technique is capable of identifying target materials such as uranium even if they are coated with other materials.
The muon is a subatomic particle that is essentially a heavier version of the electron. Huge numbers of cosmic muons are created in Earth’s atmosphere when cosmic rays collide with gas molecules. Thousands of cosmic muons per second rain down on every square metre of Earth’s surface and these particles can penetrate tens to hundreds of metres through solid materials.
As a result, cosmic muons are used to peer inside large objects such as nuclear reactors, volcanoes and ancient pyramids. This involves placing detectors next to an object and detecting muons that have passed through or scattered within the object. Detector data are then processed using a tomography algorithm to create a 3D image of the object’s interior.
Muons tend to scatter more from high-atomic-number materials, so the technique is particularly sensitive to the presence of materials such as uranium. As a result, it has been used to create systems for the detection of illicit nuclear materials hidden in freight containers.
Muon tomography is relatively straightforward when the object is of simple construction – such as a pyramid built of stone and containing voids. Producing useful images of more complex target – such as a freight container full of unknown objects – is much more difficult. The conventional computational approach is to calculate the muon-scattering physics of many different materials and combine these data with muon-tracking algorithms. This, however, tends to require huge computational resources.
Supervised machine learning has been used to reduce the computational overhead, but this requires prior knowledge of the target materials – limiting efficacy when imaging unknown and concealed materials. What is more, many materials in complex objects are coated with other materials and these coatings can affect muon scattering.
Now, Liangwen Chen at the Institute of Modern Physics of the Chinese Academy of Sciences and colleagues have used a technique called transfer learning to improve cosmic muon tomography of objects that contain coated materials. The idea of transfer learning is to begin with knowledge of the muon-scattering parameters of bare, uncoated materials and use machine learning to predict the parameters of coated materials. Chen and colleagues believe that this is the first application of transfer learning to muon tomography.
The team began by creating a database describing how cosmic muons interact with representative materials with a wide range of atomic numbers. This was done by using Geant4 to do Monte Carlo simulations of how muons interact as they pass through materials. Geant4 is the most recent incarnation of the GEANT series of computer simulations, which have been used for over 50 years to design particle detectors and interpret the data that they produce.
Chen and colleagues used Geant4 to calculate how muons are scattered within nine materials ranging from magnesium (atomic number 12) to uranium (atomic number 92). These included common elements such as aluminium, copper and iron. The geometry of the scattering involves incoming cosmic muons with energies of 1 GeV and incident angles that are typical of cosmic muons. After scattering from a material target, the simulation assumes that the muons travel though two successive detectors, which measures the scattering angles. Data were generated for bare targets of the nine materials, as well as the nine materials coated with aluminium and polyethylene. Each simulation involved 500,000 muons passing through a target.
These data were then sampled using an inverse cumulative distribution function, as well as integration and interpolation. This is done to convert the data to a form that is optimal for training a neural network.
To use these data, the team created two lightweight neural-network frameworks for transfer learning: one based on fine tuning; and the other a domain-adversarial neural network. According to the team, both frameworks were able to identify correlations between muon scattering-angle distributions and different target materials. Crucially, this was the case even when the target materials were coated in aluminium or polyethylene.
Chen explains, “Transfer learning allows us to preserve the fundamental physical characteristics of muon scattering while efficiently adapting to unknown environments under shielding”.
Chen and colleagues are now trying to apply their process to more complicated scattering geometries. The also plan to include detector effects and targets made of several materials.
“By integrating simulation, physics, and data-driven learning, this research opens new pathways for applying artificial intelligence to nuclear science and security technologies,” says Chen.
The research is described in Nuclear Science and Techniques.
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Katie Perry studied physics at the University of Surrey in the UK, staying on there to do a PhD. While at Surrey, she worked with the nuclear physicist Daphne Jackson, who was the first female physics professor in the UK. Perry later worked in science communication – both as a science writer and in public relations.
She is currently chief executive of the Daphne Jackson Trust – a charity that supports returners to research careers after a break of at least two years for family, caring or health reasons. It offers fellowships to support people to overcome the challenges of returning, ensuring that their skills, talent, training and career promise are not lost.
One of the most important skills is multitasking and working in an agile and flexible way. I’m often travelling to meetings, conferences and other events so I have to work wherever I am, whether it’s on a train, in a hotel or at the office. How I work reminds me of a moment I had towards the end of my physics degree when suddenly everything I’d been learning seemed to fit together; I could see both the detail and the bigger picture. It’s the same now. I have to switch quickly from one project or task to another, while keeping oversight of the overall direction and operation of the charity.
I am a strong advocate for part time and flexible working, not just for me, but for all my staff and the Daphne Jackson fellows. As a manager, a key skill is to see the person and their value – not just the hours they are working. Communication and networking skills are also vital as much of my role involves developing collaborations and working with stakeholders. I could be meeting a university vice chancellor, attending a networking reception, talking to our fellows or ensuring the trust complies with charity governance – all in one day.
I love my current role, and at the risk of sounding a little cheesy, it’s because of the trust’s amazing staff and the inspiring returners we support. The fact that I knew Daphne Jackson means that leading the organization is personal to me. I’m always blown away by how inspirational, dedicated, motivated and talented our fellows are and I love supporting them to return to successful research careers. It’s a privilege to lead the charity, helping to understand the challenges and barriers that returners face – and finding ways to overcome them.
Leading a small charity requires a broad set of skills. I enjoy the variety but it’s a challenge because you’re not so much a “chief executive officer” as a “chief everything officer”. I don’t have huge teams of people to help me with, say, human resources, finance or health and safety, which makes it struggle to do them as well as I’d like. It’s therefore important to have a good work-life balance, which is why I recently took up golf. I’ve yet to have a work meeting while out practising my swing, but one day my diary might say I’m “on a course”!
If I could go back in time, I’d tell myself – like I now tell my daughter – that it’s fine not to have a defined career path or plan. Sure, it helps to have an idea of what you want to do, but you have to live and work a little to discover what you like and – more importantly – don’t like. Careers these days are highly non-linear. Unexpected life events happen so you have to adapt, just as our Daphne Jackson fellows have done.
If someone had said to me in my 20s, when I was planning a career in science communication, that I’d be a charity chief executive I wouldn’t have believed them. But here I am running a charity founded in memory of the physicist who was such a great mentor to me during my PhD. When one door closes, a window often opens – so don’t be afraid to take set off in a new direction. It can be scary, but it’s often worth the effort.
I’d also tell my younger self to network like crazy. So many opportunities have opened up because I love speaking to people. You never know who you might meet at events or what making new connections can lead to. Finally, I wish I’d known that “impostor syndrome” will always be with you – and that it’s okay to feel that way provided you recognize it and manage it. Chances are, you may never defeat it completely.
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More than 250 quantum scientists have signed a “manifesto” opposing the use of quantum research for military purposes. The statement – quantum scientists for disarmament – expresses a “deep concern” about the current geopolitical situation and “categorically rejects” the militarization of quantum research or its use in population control and surveillance. The signatories now call for an open debate about the ethical implications of quantum research.
While quantum science has the potential to improve many different areas – from sensors and medicine to computing – some are concerned about its applications for military purposes. They includes quantum key distribution and cryptographic networks for communication as well as quantum clocks and sensing for military navigation and positioning.
Marco Cattaneo from the University of Helsinki in Finland, who co-authored the manifesto, says that even the potential applications of quantum technologies in warfare can be used to militarize universities and research agendas, which he says is already happening. He notes is not unusual for scientists to openly discuss military applications at conferences or to include such details in scientific papers.
“We are already witnessing restrictions on research collaborations with fellow quantum scientists from countries that are geopolitically opposed or ambiguous with respect to the European Union, such as Russia or China,” says Cattaneo. “When talking with our non-European colleagues, we also realized that these concerns are global and multifaceted.”
The idea for a manifesto originated during a quantum-information workshop that was held in Benasque in Spain between June and July 2025.
“During a session on science policy, we realized that many of us shared the same concerns about the growing militarization of quantum science and academia,” Cattaneo recalls. “As physicists, we have a strong – and terrible – historical example that can guide our actions: the development of nuclear weapons, and the way the physics community organized to oppose them and to push for their control and abolition.”
Cattaneo says that the first goal of the manifesto is to address the militarization of quantum research, which he calls “the elephant in the room”. The document also aims to raise awareness and open a debate within the community and create a forum where concerns can be shared.
“A longer-term goal is to prevent, or at least to limit and critically address, research on quantum technologies for military purposes,” says Cattaneo. He notes that “one concrete proposal” is to push public universities and research institutes to publish a database of all projects with military goals or military funding, which, he says, “would be a major step forward.”
Cattaneo claims the group is “not naïve” and understands that stopping the technology’s military application completely will not be possible. “Even if military uses of some quantum technologies cannot be completely stopped, we can still advocate for excluding them from public universities, for abolishing classified quantum research in public research institutions, and for creating associations and committees that review and limit the militarization of quantum technologies,” he adds.
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