Day 691

Thursday.

1407.0390
The Gigaparsec WiggleZ Simulations: characterising scale dependent bias and associated systematics in growth of structure measurements
Poole, Blacke, Marin, Power, Mutch, Croton, Colless, Couch, Drinkwater, Glazebrook

Present the GiggleZ simulation suite and use this resource to characterize the effects of galaxy bias and its scale dependence on the 2-pt correlation function of DM haloes for a range of redshifts (z~1.2) and DM halo masses (100<Vmax<700 km/s) in a standard cosmology.  Under the ansatz that bias converges to a scale independent form at large scales, develop an 8-parameter model which fully expresses the mass and redshift dependence of bias and its scale dependence in real or redshift space.  Lastly, use this fitting formula to illustrate how scale-dependent bias can systematically skew measurement of the growth-rate of cosmic structure as obtained from z-space distortion measurements.  When data is fit only to scales less than k_max=0.1 h/Mpc, find that scale dependent bias effects are significant only for large biases (b>~3) at large redshifts (z>~1).  However, when smaller scales are incorporated (k_max>~0.2 h/Mpc), the combination of reduced statistical uncertainties and increased scale dependent bias effects can result in highly significant systematics for most large haloes across all redshifts.  Identify several new interesting aspects of scale dependent bias, including a significant halo bias boost for small halos at low-redshifts due to substructure effects (approximately 20% for MW-like systems) and a halo mass that is nearly independent of redshift (corresponding to a z-space bias of approximately 1.5 at all redshifts) for which halo bias has no scale dependence on scales greater than 3 Mpc/h.  This suggests an optimal strategy of targeting bias ~1.5 systems for clustering studies which are dominated more by systematic effects than statistical precision, such as cosmological measurements of neutrino masses.  Code for generating the fitting formula has been made public.

1407.0550
Characterizing the chemical pathways for water formation -- a deep search for hydrogen peroxide
Parise, Bergman, Menten

Detection of HOOH in 2011, but found only in Oph A.  Possible that it is abundant, as HOOH is an intermediate product in the formation of H2O on the surface of dust grains.  Derive 3 sigma upper limits for the abundance of HOOH relative to H2 lower than Oph A for most sources.  In an attempt to figure out why Oph A is specie, show chemical models of production of HOOH that is extremely sensitive to the temperature, and favored only in the range 20-30K, implying Oph A material temperature of that range.