Paul Thorman

DISCOVERY OF A DISSOCIATIVE GALAXY CLUSTER MERGER WITH LARGE PHYSICAL SEPARATION

We present DLSCL J0916.2+2951 (z = 0.53), a newly discovered major cluster merger in which the collisional cluster gas has become dissociated from the collisionless galaxies and dark matter (DM). We identified the cluster using optical and weak-lensing observations as part of the Deep Lens Survey. Our follow-up observations with Keck, Subaru, Hubble Space Telescope, and Chandra show that the cluster is a dissociative merger and constrain the DM self-interaction cross-section σDM m –1 DM 7 cm2 g–1. The system is observed at least 0.7 ± 0.2 Gyr since first pass-through, thus providing a picture of cluster mergers 2-5 times further progressed than similar systems observed to date. This improved temporal leverage has implications for our understanding of merging clusters and their impact on galaxy evolution.

HUBBLE SPACE TELESCOPE OBSERVATIONS OF FIELD ULTRACOOL DWARFS AT HIGH GALACTIC LATITUDE

We present a sample of 17 newly discovered ultracool dwarf candidates later than ~M8, drawn from 231.90 arcmin^2 of Hubble Space Telescope Wide Field Camera 3 infrared imaging. By comparing the observed number counts for 17.5 ≤ J_(125) ≤ 25.5 AB mag to an exponential disk model, we estimate a vertical scale height of z_(scl) = 290 ± 25 (random) ± 31 (systematic) pc for a binarity fraction of f_b = 0. While our estimate is roughly consistent with published results, we suggest that the differences can be attributed to sample properties, with the present sample containing far more substellar objects than previous work. We predict the object counts should peak at J_(125) ~ 24 AB mag due to the exponentially declining number density at the edge of the disk. We conclude by arguing that trend in scale height with spectral type may breakdown for brown dwarfs since they do not settle onto the main sequence.

Improved photometric redshifts via enhanced estimates of system response, galaxy templates and magnitude priors

Wide, deep photometric surveys require robust photometric redshift estimates (photo-zs) for studies of large-scale structure. These estimates depend critically on accurate photometry. We describe the improvements to the photometric calibration and the photo-z estimates in the Deep Lens Survey (DLS) from correcting three of the inputs to the photo-z calculation: the system response as a function of wavelength, the spectral energy distribution templates, and template prior probabilities as a function of magnitude. We model the system response with a physical model of the MOSAIC cameras CCD, which corrects a 0.1 magnitude discrepancy in the colours of type M2 and later stars relative to the SDSS z-band photometry. We provide our estimated z-band response function for the use of other surveys that used MOSAIC before its recent detector upgrade. The improved throughput curve, template set, and Bayesian prior lead to a 20 per cent reduction in photo-z scatter and a reduction of the bias by a factor of more than two. This paper serves as both a photo-z data release description for DLS and a guide for testing the quality of photometry and resulting photo-zs generally.

CHARACTERIZING AND PROPAGATING MODELING UNCERTAINTIES IN PHOTOMETRICALLY-DERIVED REDSHIFT DISTRIBUTIONS

The uncertainty in the redshift distributions of galaxies has a significant potential impact on the cosmological parameter values inferred from multi-band imaging surveys. The accuracy of the photometric redshifts measured in these surveys depends not only on the quality of the flux data, but also on a number of modeling assumptions that enter into both the training set and spectral energy distribution (SED) fitting methods of photometric redshift estimation. In this work we focus on the latter, considering two types of modeling uncertainties: uncertainties in the SED template set and uncertainties in the magnitude and type priors used in a Bayesian photometric redshift estimation method. We find that SED template selection effects dominate over magnitude prior errors. We introduce a method for parameterizing the resulting ignorance of the redshift distributions, and for propagating these uncertainties to uncertainties in cosmological parameters.