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Register a new userDark matter searches using accelerometer-based networks
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Added by
Nataniel Leigh Figueroa
Publication date
2021
fields
Physics
and research's language is
English
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Dark matter is one of the biggest open questions in physics today. It is known that it interacts gravitationally with luminous matter, so accelerometer-based searches are inherently interesting. In this article we present recent (and future) searches for dark matter candidates such as feebly interacting matter trapped inside the Earth, scalar-matter domain walls and axion quark nuggets, with accelerometer networks and give an outlook of how new atomic-interferometry-based accelerometer networks could support dark matter searches.
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One of the major challenges of modern physics is to decipher the nature of dark matter. Astrophysical observations provide ample evidence for the existence of an invisible and dominant mass component in the observable universe, from the scales of galaxies up to the largest cosmological scales. The dark matter could be made of new, yet undiscovered elementary particles, with allowed masses and interaction strengths with normal matter spanning an enormous range. Axions, produced non-thermally in the early universe, and weakly interacting massive particles (WIMPs), which froze out of thermal equilibrium with a relic density matching the observations, represent two well-motivated, generic classes of dark matter candidates. Dark matter axions could be detected by exploiting their predicted coupling to two photons, where the highest sensitivity is reached by experiments using a microwave cavity permeated by a strong magnetic field. WIMPs could be directly observed via scatters off atomic nuclei in underground, ultra low-background detectors, or indirectly, via secondary radiation produced when they pair annihilate. They could also be generated at particle colliders such as the LHC, where associated particles produced in the same process are to be detected. After a brief motivation and an introduction to the phenomenology of particle dark matter detection, I will discuss the most promising experimental techniques to search for axions and WIMPs, addressing their current and future science reach, as well as their complementarity.
We are at the dawn of a data-driven era in astrophysics and cosmology. A large number of ongoing and forthcoming experiments combined with an increasingly open approach to data availability offer great potential in unlocking some of the deepest mysteries of the Universe. Among these is understanding the nature of dark matter (DM)---one of the major unsolved problems in particle physics. Characterizing DM through its astrophysical signatures will require a robust understanding of its distribution in the sky and the use of novel statistical methods. The first part of this thesis describes the implementation of a novel statistical technique which leverages the clumpiness of photons originating from point sources (PSs) to derive the properties of PS populations hidden in astrophysical datasets. This is applied to data from the Fermi satellite at high latitudes ($|b| > 30$deg) to characterize the contribution of PSs of extragalactic origin. We find that the majority of extragalactic gamma-ray emission can be ascribed to unresolved PSs having properties consistent with known sources such as active galactic nuclei. This leaves considerably less room for significant dark matter contribution. The second part of this thesis poses the question: what is the best way to look for annihilating dark matter in extragalactic sources? and attempts to answer it by constructing a pipeline to robustly map out the distribution of dark matter outside the Milky Way using galaxy group catalogs. This framework is then applied to Fermi data and existing group catalogs to search for annihilating dark matter in extragalactic galaxies and clusters.
Anisotropies in the electromagnetic emission produced by dark matter annihilation or decay in the extragalactic sky are a recent tool in the quest for a particle dark matter evidence. We review the formalism to compute the two-point angular power spectrum in the halo-model approach and discuss the features and the relative size of the various auto- and cross-correlation signals that can be envisaged for anisotropy studies. From the side of particle dark matter signals, we consider the full multi-wavelength spectrum, from the radio emission to X-ray and gamma-ray productions. We discuss the angular power spectra of the auto-correlation of each of these signals and of the cross-correlation between any pair of them. We then extend the search to comprise specific gravitational tracers of dark matter distribution in the Universe: weak-lensing cosmic shear, large-scale-structure matter distribution and CMB-lensing. We have shown that cross-correlating a multi-wavelength dark matter signal (which is a direct manifestation of its particle physics nature) with a gravitational tracer (which is a manifestation of the presence of large amounts of unseen matter in the Universe) may offer a promising tool to demonstrate that what we call dark matter is indeed formed by elementary particles.
This white paper describes the basic idea for indirect dark matter searches using antideuterons. Low energy antideuterons produced by dark matter annihilations/decays provide an attractive dark matter signature, due to the low astrophysical background. The current and future experiments have a strong potential to detect antideuterons from dark matter. They are complementary not only with each other, but also with other dark matter searches.
We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21cm radio observations around the epoch of reionization (EoR). We show that the axion as the dominant dark matter component has a significant impact on the reionization history due to the suppression of small scale density perturbations in the early universe. This behavior depends strongly on the mass of the axion particle. Using numerical simulations of the brightness temperature field of neutral hydrogen over a large redshift range, we construct a suite of training data. This data is used to train a convolutional neural network that can build a connection between the spatial structures of the brightness temperature field and the input axion mass directly. We construct mock observations of the future Square Kilometer Array survey, SKA1-Low, and find that even in the presence of realistic noise and resolution constraints, the network is still able to predict the input axion mass. We find that the axion mass can be recovered over a wide mass range with a precision of approximately 20%, and as the whole DM contribution, the axion can be detected using SKA1-Low at 68% if the axion mass is $M_X<1.86 times10^{-20}$eV although this can decrease to $M_X<5.25 times10^{-21}$eV if we relax our assumptions on the astrophysical modeling by treating those astrophysical parameters as nuisance parameters.
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