Day 319

Sunday.

1210.6347
Modeling mid-infrared diagnostics of obscured quasars and starbursts
Snyder, Hayward, ..., Hernquist, Hopkins, et al

Connection between MIR flux and AGN using radiative transfer calculations of SBs in hydrosims.  Study quantities as a function of time, viewing angle, dust model, AGN spectrum, and AGN strength in merger simulations.  In obscured SB: begins SF dominated with significant PAH emission, and ends with a 1e9 yr period of red NIR colors.  Dust obscuration of AGN coalescence (i.e., when it's most luminous), dust obscures the NIR AGN signature, reduces the relative emission from PAHs, and ehnahces the 9.7 um absorption by silicates grains.   Imply none of these indicators can unambiguously estimate the AGN luminosity fraction in all cases.  A combination of extinction feature at 9.7 um, the PAH strength, and a NR slope an simultaneously constrain the AGN fraction and dust grain distribution for a wide range of obscuration.   James Webb ST can do this, and may estimate the AGN power as tightly as the hard X-ray flux alone---can provide X-checkk and constraint for large samples of distant ULIRGs.

1210.6354
Lensing noise in mm-wave Galaxy cluster surveys
Hezaveh et al

How gravitational lensing affects SZ cluster number counts, due to its effects of DSFGs (dusty SF galaxies, due to its detection frequency range) and CMB.  For a single-frequency 150 GHz survey, lensing of DSFGs leads to both a 10% increase in detected cluster number counts (due to a 50% increase in the variance of the DSFG background, and hence an increased Eddington bias), as well as to a rare (2% of the clusters) "filling-in" of SZ cluster signals by bright strongly lensed background sources.  Lensing of the CMB leads to a 55% reduction in CMB power at the location of massive galaxy clusters in a spatially-matched single-frequency filter, leading to a net decrease in detected cluster number counts.  Find that the increase in DSFG power and decrease in CMB power due to lensing at cluster locations largely cancel, such that the net effect on cluster number counts for current SZ surveys is sub-dominant to Poisson errors.

* eddington bias: statistical fluctuation in the measurement from one bin into the other, typically seen when detection distribution functions overlap.
* malmquist bias: detection bias, as seen in "luminosity-limited" samples (counter with "volume-limited" samples)