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We present a review of the current experimental and theoretical understanding of electron transport in noble liquids. Special attention is given to recent measurements that coincide with the development of time projection chambers (TPCs)…
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…
In many fields of science, generalized likelihood ratio tests are established tools for statistical inference. At the same time, it has become increasingly common that a simulator (or generative model) is used to describe complex processes…
The XENON experiment aims at the direct detection of dark matter in the form of WIMPs (Weakly Interacting Massive Particles) via their elastic scattering off Xenon nuclei. With a fiducial mass of 1000 kg of liquid xenon, a sufficiently low…
In this thesis, I study the expected direct and indirect detection signals of dark matter. More precisely, I study three aspects of dark matter; I use hydrodynamic simulations to extract properties of weakly interacting dark matter that are…
Uncertainty quantification is a critical aspect of reinforcement learning and deep learning, with numerous applications ranging from efficient exploration and stable offline reinforcement learning to outlier detection in medical…
We study the impact of the assumed velocity distribution of galactic dark matter particles on the interpretation of results from nuclear recoil detectors. By converting experimental data to variables that make the astrophysical unknowns…
In the coming years, a new generation of sky surveys, in particular, Euclid Space Telescope (2022), and the Rubin Observatory's Legacy Survey of Space and Time (LSST, 2023) will discover more than 200,000 new strong gravitational lenses,…
We report here methods and techniques for creating and improving a model that reproduces the scintillation and ionization response of a dual-phase liquid and gaseous xenon time-projection chamber. Starting with the recent release of the…
Underground searches for dark matter involve a complicated interplay of particle physics, nuclear physics, atomic physics and astrophysics. We attempt to remove the uncertainties associated with astrophysics by developing the means to map…
We estimate the density and its derivatives using a local polynomial approximation to the logarithm of an unknown density $f$. The estimator is guaranteed to be nonnegative and achieves the same optimal rate of convergence in the interior…
Likelihood-free inference for simulator-based statistical models has recently attracted a surge of interest, both in the machine learning and statistics communities. The primary focus of these research fields has been to approximate the…
In the last few years many advances have been made in the field of dark matter direct detection. In this article I will review the progress and status of experiments that employ detection techniques that do not use noble liquids. First, I…
The landscape of dark matter direct detection has been profoundly altered by the slew of recent experiments. While some have claimed signals consistent with dark matter, others have seen few, if any, events consistent with dark matter. The…
We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-ton scale liquid Xenon-based direct detection experiment,…
We demonstrate the prompt-delayed signals induced by knockout neutrons from the quasi-elastic scattering in neutrino experiments provides a new avenue for detecting light dark matter. As an illustration, we consider the detection of…
Event-driven molecular dynamics is a valuable tool in condensed and soft matter physics when particles can be modeled as hard objects or more generally if their interaction potential can be modeled in a stepwise fashion. Hard spheres model…
Rare event simulation and rare event probability estimation are important tasks within the analysis of systems subject to uncertainty and randomness. Simultaneously, accurately estimating rare event probabilities is an inherently difficult…
A computationally simple approach to inference in state space models is proposed, using approximate Bayesian computation (ABC). ABC avoids evaluation of an intractable likelihood by matching summary statistics for the observed data with…
We present a method to calculate, without making assumptions about the local dark matter velocity distribution, the maximal and minimal number of signal events in a direct detection experiment given a set of constraints from other direct…