Constraining the cosmic microwave background temperature evolution and the population and structure of galaxy clusters and groups from the South Pole Telescope and the Planck Surveyor

Galaxy clusters, the massive systems host hundreds of galaxies, are invaluable cosmological probes and astrophysical laboratories. Besides these fascinating galaxies, the concentration of dark matter creates a deep gravitational potential well, where even light passing by is bended and the background image is distorted. The baryonic gas falling into the potential well is heated up to more than 10^7 K that free electrons start to emitting in X-ray. Observing those phenomena leads to a throughout understanding of gravity, particle physics and hydrodynamics. In addition, residing on the top of the density perturbations, clusters are sensitive to the initial condition of the Universe, such that they are complimentary tools for cosmology studies. In this thesis we first introduce the basic framework of the Universe and supporting observational evidence. Following that, we sketch the principle to use clusters for cosmology study via their redshift and mass distribution. However cluster mass is not a direct observable, so we need to estimate it by other channels. We briefly exhibit cluster observations in optical, X-ray and microwave bands and discuss the challenges in estimating the underlying cluster mass with them. After this introduction, we present our results on three aspects of the cluster cosmology study. First, we present a study of Planck Sunyaev-Zel’dovich effect (SZE) selected galaxy cluster candidates using Panoramic Survey Telescope & Rapid Response System (Pan-STARRS) imaging data. To fulfil the strength of SZE survey, the redshifts of clusters are required. In this work we examine 237 Planck cluster candidates that have no redshift in the Planck source catalogue. Among them, we confirmed 60 galaxy clusters and measure their redshifts. For the remaining sample, 83 candidates are so heavily contaminated by stars due to their location near the Galactic plane that we do not identify galaxy members and assign reliable redshifts. For the rest 94 candidates we find no optical counterparts. By examining with 150 Planck confirmed clusters with spectroscopy redshifts, our redshift estimations have an accuracy of σ_{z/(1+z)}~0.022. Scaling for the already published Planck sample, we expect the majority of the unconfirmed candidates to be noise fluctuations, except a few at high redshift that the Pan-STARRS1 (PS1) data are not sufficiently deep for confirmation. Thus we use the depth of the optical imaging for each candidate together with a model of the expected galaxy population for a massive cluster to estimate a redshift lower limit, beyond which we would not have expected to detect the optical counterpart. Second, we use 95GHz, 150GHz, and 220GHz observations from South Pole Telescope (SPT) to study the SZE signatures of a sample of 46 X-ray selected groups and clusters drawn from ~6 deg^2 of the XMM-Newton Blanco Cosmology Survey (XMM-BCS). The wide redshift range and low masses make this analysis complementary to previous studies. We develop an analysis tool that using X-ray luminosity as a mass proxy to extract selection-bias corrected constraints on the SZE significance- and Y_{SZ}-mass relations. The SZE significance- mass relation is in good agreement with an extrapolation of the relation obtained from high mass clusters. However, the fit to the Y_{SZ}-mass relation at low masses, while in agreement with the extrapolation from high mass SPT sample, is in tension at 2.8σ with the constraints from the Planck sample. We examine the tension with the Planck relation, discussing sample differences and biases that could contribute. We also analyse the radio galaxy point source population in this ensemble of X-ray selected systems. We find 18 of our systems have 1 GHz Sydney University Molonglo Sky Survey (SUMSS) sources within 2 arcmin of the X-ray centre, and three of these are also detected at significance >4 by SPT. Among these three, two are associated with the brightest cluster galaxies, and the third is a likely unassociated quasar candidate. We examined the impact of these point sources on our SZE scaling relation result and find no evidence of biases. We also examined the impact of dusty galaxies. By stacking the 220 GHz data, we found 2.8σ significant evidence of flux excess, which would correspond to an average underestimate of the SZE signal that is (17±9) % in this sample of low mass systems. Finally we predict a factor of four to five improvements on these SZE mass-observable relation constraints based on future data from SPTpol and XMM-XXL. In the end we present a study using clusters as tools to probe deviations from adiabatic evolution of the Cosmic Microwave Background (CMB) temperature. The expected adiabatic evolution is a key prediction of standard cosmology. We measure the deviation of the form T(z)=T_0(1+z)^{1-α} using measurements of the spectrum of the SZE with SPT. We present a method using the ratio of the SZE signal measured at 95 and 150 GHz in the SPT data to constrain the temperature of the CMB. We validate that this approach provides unbiased results using mock observations of cluster from a new set of hydrodynamical simulations. Applying this method to a sample of 158 SPT-selected clusters, we measure α=0.017^{+0.030}_{−0.028} consistent with the standard model prediction of α=0. Combining with other published results, we find α=0.005±0.012, an improvement of ~ 10% over published constraints. This measurement also provides a strong constraint on the effective equation of state, w_{eff}=−0.994±0.010, which is presented in models of decaying dark energy

On Low-Resolution ADCs in Practical 5G Millimeter-Wave Massive MIMO Systems

Nowadays, millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems is a favorable candidate for the fifth generation (5G) cellular systems. However, a key challenge is the high power consumption imposed by its numerous radio frequency (RF) chains, which may be mitigated by opting for low-resolution analog-to-digital converters (ADCs), whilst tolerating a moderate performance loss. In this article, we discuss several important issues based on the most recent research on mmWave massive MIMO systems relying on low-resolution ADCs. We discuss the key transceiver design challenges including channel estimation, signal detector, channel information feedback and transmit precoding. Furthermore, we introduce a mixed-ADC architecture as an alternative technique of improving the overall system performance. Finally, the associated challenges and potential implementations of the practical 5G mmWave massive MIMO system {with ADC quantizers} are discussed.Comment: to appear in IEEE Communications Magazin

SZE Observables, Pressure Profiles and Center Offsets in Magneticum Simulation Galaxy Clusters

We present a detailed study of the galaxy cluster thermal \ac{sze} signal $Y$ and pressure profiles using {\it Magneticum} Pathfinder hydrodynamical simulations. With a sample of 50,000 galaxy clusters ($M_{\rm 500c}>1.4\times10^{14} \rm M_{\odot}$) out to $z=2$, we find significant variations in the shape of the pressure profile with mass and redshift and present a new generalized NFW model that follows these trends. We show that the thermal pressure at $R_{\rm 500c}$ accounts for only 80~percent of the pressure required to maintain hydrostatic equilibrium, and therefore even idealized hydrostatic mass estimates would be biased at the 20~percent level. We compare the cluster \ac{sze} signal extracted from a sphere with different virial-like radii, a virial cylinder within a narrow redshift slice and the full light cone, confirming small scatter ($\sigma_{\ln Y}\simeq 0.087$) in the sphere and showing that structure immediately surrounding clusters increases the scatter and strengthens non self-similar redshift evolution in the cylinder. Uncorrelated large scale structure along the line of sight leads to an increase in the \ac{sze} signal and scatter that is more pronounced for low mass clusters, resulting in non self-similar trends in both mass and redshift and a mass dependent scatter that is $\sim0.16$ at low masses. The scatter distribution is consistent with log-normal in all cases. We present a model of the offsets between the center of the gravitational potential and the \ac{sze} center that follows the variations with cluster mass and redshift.Comment: 20 pages, 15 figures, submitted to MNRA

Modelling escalation in crime seriousness:a latent variable approach

This paper investigates the use of latent variable models in assessing escalation in crime seriousness. It has two aims. The first is to contrast a mixed-effects approach to modelling crime escalation with a latent variable approach. The paper therefore examines whether there are specific subgroups of offenders with distinct seriousness trajectory shapes. The second is methodological - to compare mixed-effects modelling used in previous work on escalation with group-based trajectory modelling and growth mixture modelling (mixture of mixed-effects models). The availability of software is an issue, and comparisons of fit across software packages is not straightforward. We suggest that mixture models are necessary in modelling crime seriousness, that growth mixture models rather than group based trajectory models provide the best fit to the data, and that R gives the best software environment for comparing models. Substantively, we identify three latent groups, with the largest group showing crime seriousness increases with criminal justice experience (measured through number of conviction occasions) and decreases with increasing age. The other two groups show more dramatic non-linear effects with age, and non-significant effects of criminal justice experience. Policy considerations of these results are briefly discussed

Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem

Email platforms need to generate personalized rankings of emails that satisfy user preferences, which may vary over time. We approach this as a recommendation problem based on three criteria: closeness (how relevant the sender and topic are to the user), timeliness (how recent the email is), and conciseness (how brief the email is). We propose MOSR (Multi-Objective Stationary Recommender), a novel online algorithm that uses an adaptive control model to dynamically balance these criteria and adapt to preference changes. We evaluate MOSR on the Enron Email Dataset, a large collection of real emails, and compare it with other baselines. The results show that MOSR achieves better performance, especially under non-stationary preferences, where users value different criteria more or less over time. We also test MOSR's robustness on a smaller down-sampled dataset that exhibits high variance in email characteristics, and show that it maintains stable rankings across different samples. Our work offers novel insights into how to design email re-ranking systems that account for multiple objectives impacting user satisfaction.Comment: Published in KDD'2