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In the direct searches for Weakly Interacting Massive Particles (WIMPs) as Dark Matter candidates, the sensitivity of the detector to the incom- ing particle direction could provide a smoking gun signature for an interesting event. The SCENE collaboration firstly suggested the possible directional de- pendence of a dual-phase argon Time Projection Chamber through the columnar recombination effect. The Recoil Directionality project (ReD) within the Global Argon Dark Matter Collaboration aims to characterize the light and charge re- sponse of a liquid Argon dual-phase TPC to neutron-induced nuclear recoils to probe for the hint by SCENE. In this work, the directional sensitivity of the de- tector in the energy range of interest for WIMPs (20-100 keV) is investigated with a data-driven analysis involving a Machine Learning algorithm. 

The IceCube Neutrino Observatory located at the geographic South Pole is composed of two detectors. One is the in-ice optical array, which measures high-energy muons from air showers and charged particles produced by the interaction of high-energy neutrinos in the ice. The other is an array of ice-Cherenkov tanks at the surface, called IceTop, which is used both as veto for the in-ice neutrino measurements and for detecting cosmic-ray air showers. In the next decade, the IceCube-Gen2 extension will increase the surface coverage including surface radio antennas and scintillator panels on the footprint of an extended optical array in the ice. The combination of the current surface and in-ice detectors can be exploited for the study of cosmic rays and the search for PeV gamma rays. The in-ice detector measures the high-energy muonic component of air showers, whereas the signal in IceTop is dominated by the electromagnetic component. The relative size of the muonic and electromagnetic components is different for gamma-and hadron-induced air showers. Thus, the gamma-hadron separation of cosmic rays is attempted using machine learning techniques including deep learning. Here, different approaches are presented. Finally, the prospects for the detection of PeV photons with IceCube-Gen2 will be discussed. 

The sources of the astrophysical neutrino flux discovered by IceCube remain for the most part unresolved. Extragalactic core-collapse supernovae (CCSNe) have been suggested as potentially able to produce high-energy neutrinos. In recent years, the Zwicky Transient Facility has discovered a population of exceptionally luminous supernovae, whose powering mechanisms have not yet been fully established. A fraction of these objects fall in the broader category of type IIn CCSNe, showing signs of interaction with a dense circumstellar medium. Theoretical models connect the supernova photometric properties to the dynamics of a shock-powered emission, predicting particle acceleration. In this contribution, we outline the plan for a search of high-energy neutrinos targeting the population of superluminous and type IIn supernovae with the IceCube Neutrino Observatory.