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We consider machine learning techniques associated with the application of a boosted decision tree (BDT) to searches at the Large Hadron Collider (LHC) for pair-produced lepton partners which decay to leptons and invisible particles. This scenario can arise in the minimal supersymmetric Standard Model (MSSM), but can be realized in many other extensions of the Standard Model (SM). We focus on the case of intermediate mass splitting ( $\sim 30\mathrm{GeV}$) between the dark matter (DM) and the scalar. For these mass splittings, the LHC has made little improvement over LEP due to large electroweak backgrounds. We find that the use of machine learning techniques can push the LHC well past discovery sensitivity for a benchmark model with a lepton partner mass of $\sim 110\mathrm{GeV}$, for an integrated luminosity of $300{\mathrm{fb}}^{-1}$, with a signal-to-background ratio of $\sim 0.3$. The LHC could exclude models with a lepton partner mass as large as $\sim 160\mathrm{GeV}$with the same luminosity. The use of machine learning techniques in searches for scalar lepton partners at the LHC could thus definitively probe the parameter space of the MSSM in which scalar muon mediated interactions between SM muons and Majorana singlet DM can both deplete the relic density through dark matter annihilation and satisfy the recently measured anomalous magnetic moment of the muon. We identify several machine learning techniques which can be useful in other LHC searches involving large and complex backgrounds. Published by the American Physical Society2024 

Abstract Any dark matter spikes surrounding black holes in our Galaxy are sites of significant dark matter annihilation, leading to a potentially detectable neutrino signal. In this paper we examine 10 - 10 5 M ⊙ black holes associated with dark matter spikes that formed in early minihalos and still exist in our Milky Way Galaxy today, in light of neutrino data from the ANTARES [1] and IceCube [2] detectors. In various regions of the sky, we determine the minimum distance away from the solar system that a dark matter spike must be in order to have not been detected as a neutrino point source for a variety of representative dark matter annihilation channels. Given these constraints on the distribution of dark matter spikes in the Galaxy, we place significant limits on the formation of the first generation of stars in early minihalos — stronger than previous limits from gamma-ray searches in Fermi Gamma-Ray Space Telescope data. The larger black holes considered in this paper may arise as the remnants of Dark Stars after the dark matter fuel is exhausted; thus neutrino observations may be used to constrain the properties of Dark Stars. The limits are particularly strong for heavier WIMPs. For WIMP masses ∼ 5TeV, we show that ≲ 10 % of minihalos can host first stars that collapse into BHs larger than 10 3 M ⊙ . 

Paleo-detectors are a proposed experimental technique to search for dark matter (DM). In lieu of the conventional approach of operating a tonne-scale real-time detector to search for DM-induced nuclear recoils, paleo-detectors take advantage of small samples of naturally occurring rocks on Earth that have been deep underground (≳5 km), accumulating nuclear damage tracks from recoiling nuclei for O(1)Gyr. Modern microscopy techniques promise the capability to read out nuclear damage tracks with nanometer resolution in macroscopic samples. Thanks to their O(1)Gyr integration times, paleo-detectors could constitute nuclear recoil detectors with keV recoil energy thresholds and 100 kilotonne-yr exposures. This combination would allow paleo-detectors to probe DM-nucleon cross sections orders of magnitude below existing upper limits from conventional direct detection experiments. In this article, we use improved background modeling and a new spectral analysis technique to update the sensitivity forecast for paleo-detectors. We demonstrate the robustness of the sensitivity forecast to the (lack of) ancillary measurements of the age of the samples and the parameters controlling the backgrounds, systematic mismodeling of the spectral shape of the backgrounds, and the radiopurity of the mineral samples. Specifically, we demonstrate that even if the uranium concentration in paleo-detector samples is 10−8 (per weight), many orders of magnitude larger than what we expect in the most radiopure samples obtained from ultra basic rock or marine evaporite deposits, paleo-detectors could still probe DM-nucleon cross sections below current limits. For DM masses ≲ 10 GeV/c2, the sensitivity of paleo-detectors could still reach down all the way to the conventional neutrino floor in a Xe-based direct detection experiment.