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Register a new userBayesian Forecasts for Dark Matter Substructure Searches with Mock Pulsar Timing Data
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Dark matter substructure, such as primordial black holes (PBHs) and axion miniclusters, can induce phase shifts in pulsar timing arrays (PTAs) due to gravitational effects. In order to gain a more realistic forecast for the detectability of such models of dark matter with PTAs, we propose a Bayesian inference framework to search for phase shifts generated by PBHs and perform the analysis on mock PTA data with the software texttt{enterprise}. For most PBH masses the constraints on the dark matter abundance agree with previous (frequentist) analyses (without mock data) to $mathcal{O}(1)$ factors. This further motivates a dedicated search for PBHs (and dense small scale structures) in the mass range from $10^{-8},M_{odot}$ to well above $10^2,M_{odot}$ with the Square Kilometer Array. Moreover, with a more optimistic set of timing parameters, future PTAs are predicted to constrain PBHs down to $10^{-11},M_{odot}$. Lastly, we discuss the impact of backgrounds, such as Supermassive Black Hole Mergers, on detection prospects, suggesting a future program to separate a dark matter signal from other astrophysical sources.
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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.
We examine the capability of pulsar timing arrays (PTAs) to detect very small-scale clumps of dark matter (DM), which are a natural outcome of the standard cold dark matter (CDM) paradigm. A clump streaming near the Earth or a pulsar induces an impulsive acceleration to encode residuals on pulsar timing data. We show that, assuming the standard abundance of DM clumps predicted by the CDM model, small-scale DM clumps with masses from $sim 10^{-11} M_odot$ to $sim 10^{-8} M_odot$ can be detectable by a PTA observation for a few decades with ${cal O}(100)$ of pulsars with a timing noise of ${cal O}(10)$ ns located at $gtrsim 3$ kpc away from the Galactic center, as long as these mass scales are larger than the cutoff scale of the halo mass function that is determined by the particle nature of DM. Our result suggests that PTAs can provide a unique opportunity for testing one of the most fundamental predictions of the CDM paradigm. In addition, the detections and non-detections can constrain the cutoff mass scale inherent to the DM model.
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.
We use cosmological simulations to study the effects of self-interacting dark matter (SIDM) on the density profiles and substructure counts of dark matter halos from the scales of spiral galaxies to galaxy clusters, focusing explicitly on models with cross sections over dark matter particle mass sigma/m = 1 and 0.1 cm^2/g. Our simulations rely on a new SIDM N-body algorithm that is derived self-consistently from the Boltzmann equation and that reproduces analytic expectations in controlled numerical experiments. We find that well-resolved SIDM halos have constant-density cores, with significantly lower central densities than their CDM counterparts. In contrast, the subhalo content of SIDM halos is only modestly reduced compared to CDM, with the suppression greatest for large hosts and small halo-centric distances. Moreover, the large-scale clustering and halo circular velocity functions in SIDM are effectively identical to CDM, meaning that all of the large-scale successes of CDM are equally well matched by SIDM. From our largest cross section runs we are able to extract scaling relations for core sizes and central densities over a range of halo sizes and find a strong correlation between the core radius of an SIDM halo and the NFW scale radius of its CDM counterpart. We construct a simple analytic model, based on CDM scaling relations, that captures all aspects of the scaling relations for SIDM halos. Our results show that halo core densities in sigma/m = 1 cm^2/g models are too low to match observations of galaxy clusters, low surface brightness spirals (LSBs), and dwarf spheroidal galaxies. However, SIDM with sigma/m ~ 0.1 cm^2/g appears capable of reproducing reported core sizes and central densities of dwarfs, LSBs, and galaxy clusters without the need for velocity dependence. (abridged)
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