Model independent lensing sub-structure detection with multiply-imaged star clusters constellations
A broad class of dark matter (DM) models predicts the existence of sub-structures residing in DM haloes on sub-resolvable angular scales. Techniques to extract such a generic feature from diffraction-limited observations are lacking. In this work, we propose a model-independent 'super-resolving' method applicable to strong gravitational lens systems that is fully data-driven, without reference to any lens models. This method relies on a specific way of applying the optical Liouville theorem across multiple scales in the imaging data, a technique we refer to as geometrical-duality. We test this method using realistic simulations and apply it to a 'constellation' consists of 11 compact star clusters seen in two giant arcs in the lensing cluster SMACS0723 imaged by JWST as a proof-of-concept. We find reasonable self-consistency with the expectation of non-detection given the statistical sensitivity, except for one pair of star clusters. Such an outlier can be explained in the context of CDM as sub-haloes lensing in the mass range $M_{\rm sub} = 10^8 - 10^9\,M_\odot$, for which the corresponding Einstein radius is smaller than the diffraction limit of JWST.