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We examine the signals produced by dark matter interactions with electrons, which play a crucial role in direct detection experiments employing heavy target materials, particularly in many well-motivated sub-GeV dark matter scenarios. When…
A common setting for scientific inference is the ability to sample from a high-fidelity forward model (simulation) without having an explicit probability density of the data. We propose a simulation-based maximum likelihood deconvolution…
The current and upcoming generation of Very Large Volume Neutrino Telescopes---collecting unprecedented quantities of neutrino events---can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the…
An overview of non-directional direct detection methods is given. The currently leading experiments for spin independent WIMPs interactions are using simultaneous measurement of two quantities for event-by-event background discrimination in…
This paper proposes a novel method for testing observability in Gaussian models using discrete density approximations (deterministic samples) of (multivariate) Gaussians. Our notion of observability is defined by the existence of the…
Mixture models are regularly used in density estimation applications, but the problem of estimating the mixing distribution remains a challenge. Nonparametric maximum likelihood produce estimates of the mixing distribution that are…
Inferring the input parameters of simulators from observations is a crucial challenge with applications from epidemiology to molecular dynamics. Here we show a simple approach in the regime of sparse data and approximately correct models,…
Next-generation dark matter direct detection experiments will explore several orders of magnitude in the dark matter--nucleus scattering cross section below current upper limits. In case a signal is discovered the immediate task will be to…
In the direct detection of the galactic dark matter, experiments using cryogenic solid-state detectors or noble liquids play for years a very relevant role, with increasing target mass and more and more complex detection systems. But…
Liquid xenon and liquid argon detectors are leading the direct dark matter search and are expected to be the candidate technology for the forthcoming generation of ultra-sensitive large-mass detectors. At present, the scintillation light…
Complex computer simulations are commonly required for accurate data modelling in many scientific disciplines, making statistical inference challenging due to the intractability of the likelihood evaluation for the observed data.…
We show that dark matter direct detection experiments are sensitive to the existence of particles with a small effective charge (for instance, via couplings to a kinetically mixed, low-mass dark photon). Our forecasts do not depend on these…
We propose a new method for estimating rare event probabilities when independent samples are available. It is assumed that the underlying probability measures satisfy a large deviations principle with a scaling parameter $\varepsilon$ that…
Dark matter detectors that utilize liquid xenon have now achieved tonne-scale targets, giving them sensitivity to all flavours of supernova neutrinos via coherent elastic neutrino-nucleus scattering. Considering for the first time a…
Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper…
The nonlinear space-charge effects in a high intensity or high brightness accelerator can have a significant impact on the beam properties through the accelerator. These effects are included in the accelerator design via self-consistent…
We derive estimators of the density of the event times of current status data. The estimators are derived for the situations where the distribution of the observation times is known and where this distribution is unknown. The density…
We discuss a discrete-event simulation approach, which has been shown to give a unified cause-and-effect description of many quantum optics and single-neutron interferometry experiments. The event-based simulation algorithm does not require…
This paper provides a review of Approximate Bayesian Computation (ABC) methods for carrying out Bayesian posterior inference, through the lens of density estimation. We describe several recent algorithms and make connection with traditional…
We provide a general method to analyze the asymptotic properties of a variety of estimators of continuous time diffusion processes when the data are not only discretely sampled in time but the time separating successive observations may…