Abstract: The Sun may capture asymmetric dark matter (DM), which can subsequently form bound-states through the radiative emission of a sub-GeV scalar. This process enables generation of scalars without requiring DM annihilation. In addition to DM capture on nucleons, the DM-scalar coupling responsible for bound-state formation also induces capture from self-scatterings of ambient DM particles with DM particles already captured, as well as with DM bound-states formed in-situ within the Sun. This scenario is studied in detail by solving Boltzmann equations numerically and analytically. In particular, we take into consideration that the DM self-capture rates require a treatment beyond the conventional Born approximation. We show that, thanks to DM scatterings on bound-states, the number of DM particles captured increases exponentially, leading to enhanced emission of relativistic scalars through bound-state formation, whose final decay products could be observable. We explore phenomenological signatures with the example that the scalar mediator decays to neutrinos. We find that the neutrino flux emitted can be comparable to atmospheric neutrino fluxes within the range of energies below one hundred MeV. Future facilities like Hyper-K, and direct DM detection experiments can further test such scenario.

Abstract: The XENON1T experiment uses a time projection chamber (TPC) with liquid xenon to search for weakly interacting massive particles (WIMPs), a proposed dark matter particle, via direct detection. As this experiment relies on capturing rare events, the focus is on achieving a high recall of WIMP events. Hence the ability to distinguish between WIMP and the background is extremely important. To accomplish this, we suggest using convolutional neural networks (CNNs); a machine learning procedure mainly used in image recognition tasks. To explore this technique we use XENON collaboration open-source software to simulate the TPC graphical output of dark matter signals and main backgrounds. A CNN turns out to be a suitable tool for this purpose, as it can identify features in the images that differentiate the two types of events without the need to manipulate or remove data in order to focus on a particular region of the detector. We find that the CNN can distinguish between the dominant background events (ER) and 500 GeV WIMP events with a recall of 93.4%, precision of 81.2% and an accuracy of 87.2%.

Abstract: In this article we investigate the properties of the FLRW flat cosmological models in which the cosmic expansion of the Universe is affected by a dilaton dark energy (Liouville scenario). In particular, we perform a detailed study of these models in the light of the latest cosmological data, which serves to illustrate the phenomenological viability of the new dark energy paradigm as a serious alternative to the traditional scalar field approaches. By performing a joint likelihood analysis of the recent supernovae type la data (SNIa), the differential ages of passively evolving galaxies, and the baryonic acoustic oscillations (BAOs) traced by the Sloan Digital Sky Survey (SDSS), we put tight constraints on the main cosmological parameters. Furthermore, we study the linear matter fluctuation field of the above Liouville cosmological models. In this framework, we compare the observed growth rate of clustering measured from the optical galaxies with those predicted by the current Liouville models. Performing various statistical tests we show that the Liouville cosmological model provides growth rates that match well with the observed growth rate. To further test the viability of the models under study, we use the Press-Schechter formalism to derive their expected redshift distribution of cluster-size halos that will be provided by future X-ray and Sunyaev-Zeldovich cluster surveys. We find that the Hubble flow differences between the Liouville and the LambdaCDM models provide a significantly different halo redshift distribution, suggesting that the models can be observationally distinguished.