Machine Learning-Based Classification of Vector Vortex Beams.

Structured light is attracting significant attention for its diverse applications in both classical and quantum optics. The so-called vector vortex beams display peculiar properties in both contexts due to the nontrivial correlations between optical polarization and orbital angular momentum. Here we demonstrate a new, flexible experimental approach to the classification of vortex vector beams.

Sub-GeV dark matter in superfluid He-4: an effective theory approach.

We employ an effective field theory to study the detectability of sub-GeV dark matter through its interaction with the gapless excitations of superfluid He. In a quantum field theory language, the possible interactions between the dark matter and the superfluid phonon are solely dictated by symmetry. We compute the rate for the emission of one and two phonons, and show that these two observables combined allow for a large exclusion region for the dark matter masses.