Monday. Got some work done over the weekend: helped Zahra "start" her paper, and listened to Peter G. about his problems with his project; I was also going to read Cosmo lecture notes, but I ended up debugging my PhotoZGGLens (and related) code instead.
1112.3652
Understanding better (some) astronomical data using Bayesian methods
Andreon
Astronomical data: heteroscedastic (point-dependent) errors, intrinsic scatter, selection effects, data structure, non-uniform populations (Malmquist bias), non-Gaussian data, upper/lower limits. Show how to model all these features using Bayesian methods: formalize the logical link between the involved quantities, how the data arise and what is already known on the quantities studied. The posterior probability distribution summarizes what has been learned from data.
1112.3653
Spitzer IRAC identification of HErschel-ATLAS SPIRE sources
Kim et al
Use Spitzer-IRAC (3.6 and 4.5 um) data to identify NIR counterparts to submillimeter galaxies detected with Herschel-SPIRE (250um) over ~0.4 deg. sq. Identify 123 SPIRE sources out of the 159 in the IRAC coverage area. Compared to the field population, the SPIRE counterparts occupy a distince region of color-magnitude space: use this to identify further 23 counterparts to 13 SPIRE sources. IRAC identification rate of 86% is pretty high compared to WF ground-based optical and NIR imaging of Herschel fields. False id rate estimated at 4% (4 or 5 sources). ~40% of identified SPIRE galaxies are likely to be high redshift (z>1.4) sources, based on SDSS data.
1112.3655
The Gemini Cluster astrophysics spectroscopic survey (GCLASS): the role of environment and self-regulation in galaxy evolution at z~1
Muzzin, Wilson, Yee, Glibank, Hoekstra, ... van Dokkum, Franx ... et al
Evaluate the effects of environment and stellar mass on galaxy properties at 0.85<z<1.2. For galaxies with log(M*)>9.3, the well-known correlations between environment and properties (f_SF, SFR, sSFR, D(4000), colors) are already in place at z~1. SF and quiescent galaxy's properties are determined primarily by their stellar mass, not by their environment. The environment's primary role is to control the fraction of star-forming galaxies. Post-starburst galaxies with 9.3<logM*<10.7 are 3x more common in high-density regions compared to low-density regions. Clear association of post-starbursts with high-density regions as well as the lack of a correlation between sSFR and D(4000)s of SF galaxies with their environment suggests that at z~1 the environmental-quenching timescale must be rapid. Construct a simple quenching model which demonstrates that the lack of correlation between D(4000) of quiescent galaxies and their environment results naturally if self quenching dominates over environmental quenching [what's the difference?] at z>1, or if the evolution of the self-quenching rate mirrors the evolution of the environmental-quenching rate at z>1, regardless of which dominates.
1112.3656
Spectroscopy of the spatially-extended Lya emission around a QSO at z=6.4
Goto, ... Miyazaki, Yamauchi et al
Deep moderate-resolution Keck/Deimos spectra of a QSO at z=6.4. Shows spatially-extended component (more than a stellar spectrum) of Lya emission, and a continuum part. Extended component has LW of 21A, smaller than that of QSO (52A). First such observation. Emission may be from the theoretically infalling gas in the process of forming a primordial galaxy that is ionized by a central QSO. If it's gas photoionized by the host galaxy, then the SFR rate of >3Msun/yr is required. Assuming virialized gas, the dynamical mass estimate of the gas is 1.2e12 Msun. The derived MBH/Mhost is 2.1e-4, two orders smaller than those from more massive z~6 QSOs and places the galaxy in accordance with the local M-sigma relation.
1112.3658
Analytic gas orbits in an arbitrary rotating galactic potential using the linear epicyclic approximation
Pinol-Ferrer, Lindbald, Fathi
Simulate the motion of interstellar matter (and to damp the Lindbald resonances), introduce a friction which is proportional to the deviation from circular velocity, also damp corotation resonance. Program produces orbital and density maps, as well as line of sight velocity maps for a chosen orientation of the galaxy. Compare results with previous simulations and observations from literature, gives satisfactory agreement. Program should be a useful complement to elaborate numerical simulations.
1112.3659
Evolution of the merger induced hydrostatic mass bias in galaxy clusters
Nelson, Rudd, Shaw, Nagai
Examine the effects of mergers on the hydrostatic mass estimate of galaxy clusters using high-resolution Eulerian cosmo simulations. Find major merger using merger trees, follow the time evolution of the hydrostatic mass bias as the systems relax. Enables to characterize the dynamical state of clusters more robustly and quantitatively than morphological classification. Find: in major merger, a shock propagates outward from the parent cluster, resulting in a large overestimate in the hydrostatic mass bias. After the merger, as a cluster relaxes, the bias in hydrostatic mass estimate decreases but remains at a level of 5-10% with 15-20% scatter. Investigate the post-merger evolution of the non-thermal pressure support (a dominant cause of residual mass bias). At r500, the contribution from non-thermal pressure support peaks at 30% of the total pressure during the merger and quickly decays to ~10-15% as a cluster relaxes. Additionally, use a measure of the non-thermal pressure [what could that be?] to correct the hydrostatic mass estimate. After 4Gyr of the major merger, the direct effects of the merger event on the hydrostatic mass bias have become negligible. Thereafter, the mass bias is primarily due to residual bulk motions in the gas which are not accounted for in the hydrostatic equilibrium equation. Present a hydrostatic mass bias correction method that can recover the unbiased cluster mass with 8% scatter at r500 and 11% scatter in the outskirts, within r200.
* non-thermal contribution from bulk motions and turbulence messes up the hydrostatic equilibrium (HSE) assumptions in estimating mass; in X-rays, the mass using HSE systematically underestimates the total cluster mass by 10-20% even in relaxed clusters. HSE mass derived from Chandra is biased low compared to WL mass.
* mass correction requires knowledge of rho_gas, P_th(r), and dP_th/dr. So it's for mass estimates using gas density and temperatures.
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