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Coherent light sources, such as free-electron lasers, provide bright beams for studies in biology, chemistry and physics. However, increasing the brightness of these sources requires progressively larger instruments, with the largest examples, such as the Linac Coherent Light Source at Stanford, being several kilometres long. It would be transformative if this scaling trend could be overcome so that compact, bright sources could be employed at universities, hospitals and industrial laboratories. Here we address this issue by rethinking the basic principles of radiation physics. At the core of our work is the introduction of quasiparticle-based light sources that rely on the collective and macroscopic motion of an ensemble of light-emitting charges to evolve and radiate in ways that would be unphysical for single charges. The underlying concept allows for temporal coherence and superradiance in new configurations, such as in plasma accelerators, providing radiation with intriguing properties and clear experimental signatures spanning nearly ten octaves in wavelength, from the terahertz to the extreme ultraviolet. The simplicity of the quasiparticle approach makes it suitable for experimental demonstrations at existing laser and accelerator facilities and also extends well beyond this case to other scenarios such as nonlinear optical configurations. 

Abstract Time dependent observations of point-to-point correlations of the velocity vector field (structure functions) are necessary to model and understand fluid flow around complex objects. Using thermal gradients, we observed fluid flow by recording fluorescence of$${\text{He}}_{2}^{*}$$ ${\text{He}}_2^{\ast }$excimers produced by neutron capture throughout a ~ cm³volume. Because the photon emitted by an excited excimer is unlikely to be recorded by the camera, the techniques of particle tracking (PTV) and particle imaging (PIV) velocimetry cannot be applied to extract information from the fluorescence of individual excimers. Therefore, we applied an unsupervised machine learning algorithm to identify light from ensembles of excimers (clusters) and then tracked the centroids of the clusters using a particle displacement determination algorithm developed for PTV.