arXiv subjects

Mike McDonald

Publications and source records attributed to Mike McDonald.

4 recordsLinked to original sources

arXiv2019

Probing Macro-Scale Gas Motions and Turbulence in Diffuse Cosmic Plasmas

Clusters of galaxies, the largest collapsed structures in the Universe, are located at the intersection of extended filaments of baryons and dark matter. Cosmological accretion onto clusters through large scale filaments adds material at cluster outskirts. Kinetic energy in the form of bulk motions and turbulence due to this accretion provides a form of pressure support against gravity, supplemental to thermal pressure. Significant amount of non-thermal pressure support could bias cluster masses derived assuming hydrostatic equilibrium, the primary proxy for cluster cosmology studies. Sensitive measurements of Doppler broadening and shift of astrophysical lines, and the relative fluctuations in thermodynamical quantities (e.g., density, pressure, and entropy) are primary diagnostic tools. Forthcoming planned and proposed X-ray (with large etendue, throughput, and high spectral resolution) and SZ observatories will provide crucial information on the assembly and virialisation processes of clusters, involving turbulent eddies cascading at various spatial scales and larger gas bulk motions in their external regions to the depth or their potential wells.

astro-ph.CO↗

arXiv2017

Uniform Contribution of Supernova Explosions to the Chemical Enrichment of Abell 3112 out to R200

The spatial distribution of the metals residing in the intra-cluster medium (ICM) of galaxy clusters records all the information on a cluster's nucleosynthesis and chemical enrichment history. We present measurements from a total of 1.2 Ms Suzaku XIS and 72 ks Chandra observations of the cool-core galaxy cluster Abell 3112 out its virial radius (~ 1470 kpc). We find that the ratio of the observed supernova type Ia explosions to the total supernova explosions has a uniform distribution at a level of 12-16% out to the cluster's virial radius. The observed fraction of type Ia supernova explosions is in agreement with the corresponding fraction found in our Galaxy and the chemical enrichment of our Galaxy. The non-varying supernova enrichment suggests that the ICM in cluster outskirts was enriched by metals at an early stage before the cluster itself was formed during the period of intense star formation activity. Additionally, we find that the 2D delayed detonation model CDDT produces significantly worse fits to the X-ray spectra compared to simple 1D W7 models. This is due to the relative overestimate of Si, and underestimate of Mg, in these models with respect to the measured abundances.

astro-ph.HE↗

arXiv2016

Multisensor--Multitarget Bearing--Only Sensor Registration

Bearing--only estimation is one of the fundamental and challenging problems in target tracking. As in the case of radar tracking, the presence of offset or position biases can exacerbate the challenges in bearing--only estimation. Modeling various sensor biases is not a trivial task and not much has been done in the literature specifically for bearing--only tracking. This paper addresses the modeling of offset biases in bearing--only sensors and the ensuing multitarget tracking with bias compensation. Bias estimation is handled at the fusion node to which individual sensors report their local tracks in the form of associated measurement reports (AMR) or angle-only tracks. The modeling is based on a multisensor approach that can effectively handle a time--varying number of targets in the surveillance region. The proposed algorithm leads to a maximum likelihood bias estimator. The corresponding Cram\'er--Rao Lower Bound to quantify the theoretical accuracy that can be achieved by the proposed method or any other algorithm is also derived. Finally, simulation results on different distributed tracking scenarios are presented to demonstrate the capabilities of the proposed approach. In order to show that the proposed method can work even with false alarms and missed detections, simulation results on a centralized tracking scenario where the local sensors send all their measurements (not AMRs or local tracks) are also presented.

stat.ME↗

arXiv2016

A Practical Bias Estimation Algorithm for Multisensor--Multitarget Tracking

Bias estimation or sensor registration is an essential step in ensuring the accuracy of global tracks in multisensor-multitarget tracking. Most previously proposed algorithms for bias estimation rely on local measurements in centralized systems or tracks in distributed systems, along with additional information like covariances, filter gains or targets of opportunity. In addition, it is generally assumed that such data are made available to the fusion center at every sampling time. In practical distributed multisensor tracking systems, where each platform sends local tracks to the fusion center, only state estimates and, perhaps, their covariances are sent to the fusion center at non-consecutive sampling instants or scans. That is, not all the information required for exact bias estimation at the fusion center is available in practical distributed tracking systems. In this paper, a new algorithm that is capable of accurately estimating the biases even in the absence of filter gain information from local platforms is proposed for distributed tracking systems with intermittent track transmission. Through the calculation of the Posterior Cramér--Rao lower bound and various simulation results, it is shown that the performance of the new algorithm, which uses the tracklet idea and does not require track transmission at every sampling time or exchange of filter gains, can approach the performance of the exact bias estimation algorithm that requires local filter gains.

stat.ME↗