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Thomas D. P. Edwards

Publications and source records attributed to Thomas D. P. Edwards.

25 records · Page 2Linked to original sources

Paleo-Detectors for Galactic Supernova Neutrinos

Paleo-detectors are a proposed experimental technique in which one would search for traces of recoiling nuclei in ancient minerals. Natural minerals on Earth are as old as $\mathcal{O}(1)\,$Gyr and, in many minerals, the damage tracks left by recoiling nuclei are also preserved for timescales long compared to 1 Gyr once created. Thus, even reading out relatively small target samples of order 100 g, paleo-detectors would allow one to search for very rare events thanks to the large exposure, $\varepsilon \sim 100\,{\rm g}\,{\rm Gyr} = 10^5\,{\rm t}\,{\rm yr}$. Here, we explore the potential of paleo-detectors to measure nuclear recoils induced by neutrinos from galactic core collapse supernovae. We find that they would not only allow for a direct measurement of the average core collapse supernova rate in the Milky Way, but would also contain information about the time-dependence of the local supernova rate over the past $\sim$1 Gyr. Since the supernova rate is thought to be directly proportional to the star formation rate, such a measurement would provide a determination of the local star formation history. We investigate the sensitivity of paleo-detectors to both a smooth time evolution and an enhancement of the core collapse supernova rate on relatively short timescales, as would be expected for a starburst period in the local group.

astro-ph.GA↗

A Unique Multi-Messenger Signal of QCD Axion Dark Matter

We propose a multi-messenger probe of QCD axion Dark Matter based on observations of black hole-neutron star binary inspirals. It is suggested that a dense Dark Matter spike may grow around intermediate mass black holes ($10^{3}-10^{5} \mathrm{\,M_{\odot}}$). The presence of such a spike produces two unique effects: a distinct phase shift in the gravitational wave strain during the inspiral and an enhancement of the radio emission due to the resonant axion-photon conversion occurring in the neutron star magnetosphere throughout the inspiral and merger. Remarkably, the observation of the gravitational wave signal can be used to infer the Dark Matter density and, consequently, to predict the radio emission. We study the projected reach of the LISA interferometer and next-generation radio telescopes such as the Square Kilometre Array. Given a sufficiently nearby system, such observations will potentially allow for the detection of QCD axion Dark Matter in the mass range $10^{-7}\,\mathrm{eV}$ to $10^{-5}\,\mathrm{eV}$.

hep-ph↗

Digging for Dark Matter: Spectral Analysis and Discovery Potential of Paleo-Detectors

Paleo-detectors are a recently proposed method for the direct detection of Dark Matter (DM). In such detectors, one would search for the persistent damage features left by DM--nucleus interactions in ancient minerals. Initial sensitivity projections have shown that paleo-detectors could probe much of the remaining Weakly Interacting Massive Particle (WIMP) parameter space. In this paper, we improve upon the cut-and-count approach previously used to estimate the sensitivity by performing a full spectral analysis of the background- and DM-induced signal spectra. We consider two scenarios for the systematic errors on the background spectra: i) systematic errors on the normalization only, and ii) systematic errors on the shape of the backgrounds. We find that the projected sensitivity is rather robust to imperfect knowledge of the backgrounds. Finally, we study how well the parameters of the true WIMP model could be reconstructed in the hypothetical case of a WIMP discovery.

hep-ph↗

Dark Matter Model or Mass, but Not Both: Assessing Near-Future Direct Searches with Benchmark-free Forecasting

Forecasting the signal discrimination power of dark matter (DM) searches is commonly limited to a set of arbitrary benchmark points. We introduce new methods for benchmark-free forecasting that instead allow an exhaustive exploration and visualization of the phenomenological distinctiveness of DM models, based on standard hypothesis testing. Using this method, we reassess the signal discrimination power of future liquid Xenon and Argon direct DM searches. We quantify the parameter regions where various non-relativistic effective operators, millicharged DM, and magnetic dipole DM can be discriminated, and where upper limits on the DM mass can be found. We find that including an Argon target substantially improves the prospects for reconstructing the DM properties. We also show that only in a small region with DM masses in the range 20-100 GeV and DM-nucleon cross sections a factor of a few below current bounds can near-future Xenon and Argon detectors discriminate both the DM-nucleon interaction and the DM mass simultaneously. In all other regions only one or the other can be obtained.

hep-ph↗

Statistical challenges in the search for dark matter

The search for the particle nature of dark matter has given rise to a number of experimental, theoretical and statistical challenges. Here, we report on a number of these statistical challenges and new techniques to address them, as discussed in the DMStat workshop held Feb 26 - Mar 3 2018 at the Banff International Research Station for Mathematical Innovation and Discovery (BIRS) in Banff, Alberta.

hep-ph↗

A Fresh Approach to Forecasting in Astroparticle Physics and Dark Matter Searches

We present a toolbox of new techniques and concepts for the efficient forecasting of experimental sensitivities. These are applicable to a large range of scenarios in (astro-)particle physics, and based on the Fisher information formalism. Fisher information provides an answer to the question what is the maximum extractable information from a given observation?. It is a common tool for the forecasting of experimental sensitivities in many branches of science, but rarely used in astroparticle physics or searches for particle dark matter. After briefly reviewing the Fisher information matrix of general Poisson likelihoods, we propose very compact expressions for estimating expected exclusion and discovery limits (equivalent counts method). We demonstrate by comparison with Monte Carlo results that they remain surprisingly accurate even deep in the Poisson regime. We show how correlated background systematics can be efficiently accounted for by a treatment based on Gaussian random fields. Finally, we introduce the novel concept of Fisher information flux. It can be thought of as a generalization of the commonly used signal-to-noise ratio, while accounting for the non-local properties and saturation effects of background and instrumental uncertainties. It is a powerful and flexible tool ready to be used as core concept for informed strategy development in astroparticle physics and searches for particle dark matter.

astro-ph.IM↗

swordfish: Efficient Forecasting of New Physics Searches without Monte Carlo

We introduce swordfish, a Monte-Carlo-free Python package to predict expected exclusion limits, the discovery reach and expected confidence contours for a large class of experiments relevant for particle- and astrophysics. The tool is applicable to any counting experiment, supports general correlated background uncertainties, and gives exact results in both the signal- and systematics-limited regimes. Instead of time-intensive Monte Carlo simulations and likelihood maximization, it internally utilizes new approximation methods that are built on information geometry. Out of the box, swordfish provides straightforward methods for accurately deriving many of the common sensitivity measures. In addition, it allows one to examine experimental abilities in great detail by employing the notion of information flux. This new concept generalizes signal-to-noise ratios to situations where background uncertainties and component mixing cannot be neglected. The user interface of swordfish is designed with ease-of-use in mind, which we demonstrate by providing typical examples from indirect and direct dark matter searches as jupyter notebooks.

hep-ph↗