A research team at King’s College London, led by Professor James Millen, has demonstrated a sensing platform that levitates and tracks many microscopic glass particles at once, offering a route toward far more precise measurements of weak forces and environmental signals. Their work brings together advances in neuromorphic imaging, optical control, and particle cooling and suggests a future where sensors operate independently of external positioning systems and could even contribute to laboratory searches for dark matter.
Ren, Y., Siegel, B., Yin, R., Wu, Q., Pritchett, J., Rashid, M., & Millen, J. (2025). Neuromorphic detection and cooling of microparticles in arrays. Nature Communications, 16(1), 10658. https://doi.org/10.1038/s41467-025-65677-0
Levitated sensors have been studied for more than a decade in the context of optomechanics and precision metrology. The principle is familiar: by isolating a particle in a vacuum and keeping it suspended using electromagnetic or optical fields, its motion becomes a sensitive indicator of any small disturbance. Most existing devices measure one particle at a time. This approach provides high precision but limits the overall sensitivity because only a single object responds to the external forces.
Professor James Millen from King’s College London stated,
“In the future, our approach could help cool particles to below a thousandth of a degree above absolute zero, the lowest possible temperature allowed by quantum physics, eliminating the thermal noise and vibrations which get in the way of a sensor’s accuracy. This would produce a quantum sensor with an accuracy and sensitivity unparalleled by the classical technology we use today.”
The King’s College team has taken a different path by levitating clouds of particles rather than individual ones. Their system suspends dozens of microparticles under carefully controlled electromagnetic fields and records their motion using a camera designed around the principles of biological vision. Instead of collecting full video frames, the neuromorphic sensor records only changes in light as the particles move. This drastically reduces the data load, allowing motion to be tracked at speeds that conventional cameras struggle to achieve.
AI-based analysis then reconstructs the trajectories of each particle and the behaviour of the cloud as a whole. This combination allows researchers to understand both individual motion and collective dynamics, improving force detection in ways that earlier devices could not reach. As Professor Millen explains, the ability to work with many particles simultaneously removes the traditional trade-off between accuracy and capacity. The system responds quickly enough to provide immediate feedback, which can then be used to stabilise or manipulate the particle cloud.
This feedback loop is important because controlling particle motion is a first step toward cooling them. In levitated optomechanics, cooling refers not to lowering temperature in the everyday sense, but to reducing motion and energy until quantum mechanical effects become measurable. Other research groups, including teams in Innsbruck, Caltech, and ETH Zürich, have previously shown that individual particles can be cooled close to their motional ground state. The King’s team’s approach suggests that similar levels of control might eventually be applied to arrays rather than isolated particles.
The King’s researchers note that their system uses very little power, which opens the possibility of integrating the technology on chips. Neuromorphic cameras and AI processing units have already seen adoption in compact robotics and low-power computing, and adapting these components to levitated sensing would allow for portable or embedded devices. Applications range from navigation systems that do not rely on satellite signals to compact environmental monitors and potentially scientific instruments capable of probing weak forces in the lab.
Former postdoctoral researcher Dr. Yugang Ren, the study’s first author, observes that the efficiency of the system makes scaling realistic within the next decade. If extended to larger numbers of particles and cooled further, the platform could serve as a basis for quantum sensors that outperform current devices in sensitivity. Future versions may reach temperatures where thermal noise becomes negligible, enabling the detection of effects predicted by theories of dark matter or very small gravitational disturbances.
While the device is still in an early stage, the combination of levitation, neuromorphic imaging, AI analysis, and feedback control marks a meaningful development. Each component is already established in its own field, but their integration offers a pathway toward sensors that can operate beyond the limits of existing mechanical or optical platforms. As research continues, the potential to link classical sensing methods with quantum behaviour will likely become a central focus for groups exploring next-generation metrology.
The study, adds to the growing interest in levitated quantum systems and provides a platform that may help bridge laboratory research and engineering applications. For now, the results highlight how developments inspired by biological vision and computational efficiency can influence experimental physics and support technologies that require accurate, resource-efficient sensing.
Adrian graduated with a Masters Degree (1st Class Honours) in Chemical Engineering from Chester University along with Harris. His master’s research aimed to develop a standardadised clean water oxygenation transfer procedure to test bubble diffusers that are currently used in the wastewater industry commercial market. He has also undergone placments in both US and China primarely focused within the R&D department and is an associate member of the Institute of Chemical Engineers (IChemE).
