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We present a 4 deg^2 weak gravitational lensing survey of subhalos in the very nearby Coma cluster using the Subaru/Suprime-Cam. The large apparent size of cluster subhalos allows us to measure the mass of 32 subhalos detected in a model-independent manner, down to the order of 10^-3 of the virial mass of the cluster. Weak-lensing mass measurements of these shear-selected subhalos enable us to investigate subhalo properties and the correlation between subhalo masses and galaxy luminosities for the first time. The mean distortion profiles stacked over subhalos show a sharply truncated feature which is well-fitted by a Navarro-Frenk-White (NFW) mass model with the truncation radius, as expected due to tidal destruction by the main cluster. We also found that subhalo masses, truncation radii, and mass-to-light ratios decrease toward the cluster center. The subhalo mass function, dn/dln M_sub, in the range of 2 orders of magnitude in mass, is well described by a single power law or a Schechter function. Best-fit power indices of 1.09_-0.32^+0.42 for the former model and 0.99_-0.23^+0.34 for the latter, are in remarkable agreement with slopes of ~0.9-1.0 predicted by the cold dark matter paradigm. The tangential distortion signals in the radial range of 0.02-2Mpc/h from the cluster center show a complex structure which is well described by a composition of three mass components of subhalos, the NFW mass distribution as a smooth component of the main cluster, and a lensing model from a large scale structure behind the cluster. Although the lensing signals are 1 order of magnitude lower than those for clusters at z~0.2, the total signal-to-noise ratio, S/N=13.3, is comparable to, or higher, because the enormous number of background source galaxies compensates for the low lensing efficiency of the low lensing efficiency of the nearby cluster.
Warm dark matter has recently become increasingly constrained by observational inferences about the low-mass end of the subhalo mass function, which would be suppressed by dark matter free streaming in the early Universe. In this work, we point out t
We investigate the possibility of applying machine learning techniques to images of strongly lensed galaxies to detect a low mass cut-off in the spectrum of dark matter sub-halos within the lens system. We generate lensed images of systems containing
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