Random Light Patterns Instead of Long Scanning express
Hunting for a single glowing spot in a dark sample is like trying to find a needle in a haystack: the microscope beam crawls line by line, wasting time and light. Physicists replaced this slow sweep with random light patterns. The sample is illuminated with a broad field, but each time with a new pattern of bright and dark patches, as if random shadows from a grid were projected onto it. The camera records how much light comes from the whole area, and an algorithm then assembles the image from these fragments.
In the experiment, they used nitrogen defects in diamond — tiny defects in the crystal lattice that glow like single atoms. It turned out that about 20% of the measurements from a typical line-by-line scan are enough for a clear image. It's like assembling a puzzle with only a fifth of the pieces, but choosing them not in order, but from random positions.
The method went beyond simple glow. The scientists learned to reconstruct a map of quantum properties of light — how photons arrive one by one, not in pairs. Such a 'loneliness map' allows distinguishing a true single light source from a cluster of several, and it also requires five times less data. Rare quantum beacons can now be found faster, without burning the sample with a long beam.
Original abstract
as written by the authors arXiv:2604.10463
Optical imaging of quantum emitters is essential for a wide range of quantum applications. Conventional confocal imaging relies on point-by-point raster scanning, which is inherently time-consuming and photon-inefficient, particularly for sparse emitter distributions and photon-limited samples. Here, we demonstrate a compressive sensing-based imaging approach, where spatially structured wide-field excitation replaces raster scanning, enabling reconstruction of sparse emitters. In our implementation, random binary patterns are used to acquire compressive measurements, from which the spatial fluorescence distribution is reconstructed using a GPSR-BB algorithm. We experimentally demonstrate this approach using nitrogen-vacancy (NV) centers in diamond as a representative platform, with high-fidelity image reconstruction achieved using only approximately $$20\%$$ of the measurements required for conventional raster scanning. In addition to intensity reconstruction, we extend this framework to reconstruct spatial maps of the second-order correlation function $$g^{(2)}(0)$$ from compressive measurements. This enables identification of single-photon emitters through antibunching signatures using significantly reduced data.
A nitrogen defect in diamond is a nitrogen atom that took the place of a carbon atom, plus a vacancy next to it. Such a defect glows so stably that it is used as a tiny compass for measuring magnetic fields.