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Register a new userMulti-wavelength consensus of large-scale linear bias
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We model the large-scale linear galaxy bias $b_g(x,z)$ as a function of redshift $z$ and observed absolute magnitude threshold $x$ for broadband continuum emission from the far infrared to ultra-violet, as well as for prominent emission lines, such as the H$alpha$, H$beta$, Lya and [OII] lines. The modelling relies on the semi-analytic galaxy formation model GALFORM, run on the state-of-the-art $N$-body simulation SURFS with the Planck 2015 cosmology. We find that both the differential bias at observed absolute magnitude $x$ and the cumulative bias for magnitudes brighter than $x$ can be fitted with a five-parameter model: $b_g(x,z)=a + b(1+z)^e(1 + exp{[(x-c)d]})$. We also find that the bias for the continuum bands follows a very similar form regardless of wavelength due to the mixing of star-forming and quiescent galaxies in a magnitude limited survey. Differences in bias only become apparent when an additional colour separation is included, which suggest extensions to this work could look at different colours at fixed magnitude limits. We test our fitting formula against observations, finding reasonable agreement with some measurements within $1sigma$ statistical uncertainties, and highlighting areas of improvement. We provide the fitting parameters for various continuum bands, emission lines and intrinsic galaxy properties, enabling a quick estimation of the linear bias in any typical survey of large-scale structure.
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The 21 cm intensity mapping experiments promise to obtain the large-scale distribution of HI gas at the post-reionization epoch. In order to reveal the underlying matter density fluctuations from the HI mapping, it is important to understand how HI gas traces the matter density distribution. Both nonlinear halo clustering and nonlinear effects modulating HI gas in halos may determine the scale below which the HI bias deviates from linearity. We employ three approaches to generate the mock HI density from a large-scale N-body simulation at low redshifts, and demonstrate that the assumption of HI linearity is valid at the scale corresponding to the first peak of baryon acoustic oscillations, but breaks down at $k gtrsim 0.1,h, {rm Mpc}^{-1}$. The nonlinear effects of halo clustering and HI content modulation counteract each other at small scales, and their competition results in a model-dependent sweet-spot redshift near $z$=1 where the HI bias is scale-independent down to small scales. We also find that the linear HI bias scales approximately linearly with redshift for $zle 3$.
We use field-level forward models of galaxy clustering and the EFT likelihood formalism to study, for the first time for self-consistently simulated galaxies, the relations between the linear $b_1$ and second-order bias parameters $b_2$ and $b_{K^2}$. The forward models utilize all of the information available in the galaxy distribution up to a given order in perturbation theory, which allows us to infer these bias parameters with high signal-to-noise, even from relatively small volumes ($L_{rm box} = 205{rm Mpc}/h$). We consider galaxies from the IllustrisTNG simulations, and our main result is that the $b_2(b_1)$ and $b_{K^2}(b_1)$ relations obtained from gravity-only simulations for total mass selected objects are broadly preserved for simulated galaxies selected by stellar mass, star formation rate, color and black hole accretion rate. We also find good agreement between the bias relations of the simulated galaxies and a number of recent estimates for observed galaxy samples. The consistency under different galaxy selection criteria suggests that theoretical priors on these bias relations may be used to improve cosmological constraints based on observed galaxy samples. We do identify some small differences between the bias relations in the hydrodynamical and gravity-only simulations, which we show can be linked to the environmental dependence of the relation between galaxy properties and mass. We also show that the EFT likelihood recovers the value of $sigma_8$ to percent-level from various galaxy samples (including splits by color and star formation rate) and after marginalizing over 8 bias parameters. This demonstration using simulated galaxies adds to previous works based on halos as tracers, and strengthens further the potential of forward models to infer cosmology from galaxy data.
In this work, we compare large scale structure observables for stellar mass selected samples at $z=0$, as predicted by two galaxy models, the hydrodynamical simulation IllustrisTNG and the Santa-Cruz semi-analytic model (SC-SAM). Although both models have been independently calibrated to match observations, rather than each other, we find good agreement between the two models for two-point clustering and galaxy assembly bias signatures. The models also show a qualitatively similar response of occupancy and clustering to secondary halo paramaters other than mass, such as formation history and concentration, although with some quantitative differences. Thus, our results demonstrate that the galaxy-halo relationships in SC-SAM and TNG are quite similar to first order. However, we also find areas in which the models differ. For example, we note a strong correlation between halo gas content and environment in TNG, which is lacking in the SC-SAM, as well as differences in the occupancy predictions for low-mass haloes. Moreover, we show that higher-order statistics, such as cumulants of the density field, help to accurately describe the galaxy distribution and discriminate between models that show degenerate behavior for two-point statistics. Our results suggest that SAMs are a promising cost-effective and intuitive method for generating mock catalogues for next generation cosmological surveys.
This is the second paper in a series where we propose a method of indirectly measuring large scale structure using information from small scale perturbations. The idea is to build a quadratic estimator from small scale modes that provides a map of structure on large scales. We demonstrated in the first paper that the quadratic estimator works well on a dark-matter-only N-body simulation at a snapshot of $z=0$. Here we generalize the theory to the case of a light cone halo catalog with a non-cubic region taken into consideration. We successfully apply the generalized version of the quadratic estimator to the light cone halo catalog based on an N-body simulation of volume $sim15.03,(h^{-1},rm Gpc)^3$. The most distant point in the light cone is at a redshift of $1.42$, indicating the applicability of our method to next generation of galaxy surveys.
The PdBI (Plateau de Bure Interferometer) Arcsecond Whirlpool Survey (PAWS) has mapped the molecular gas in the central ~9kpc of M51 in its 12CO(1-0) line emission at cloud-scale resolution of ~40pc using both IRAM telescopes. We utilize this dataset to quantitatively characterize the relation of molecular gas (or CO emission) to other tracers of the interstellar medium (ISM), star formation and stellar populations of varying ages. Using 2-dimensional maps, a polar cross-correlation technique and pixel-by-pixel diagrams, we find: (a) that (as expected) the distribution of the molecular gas can be linked to different components of the gravitational potential, (b) evidence for a physical link between CO line emission and radio continuum that seems not to be caused by massive stars, but rather depend on the gas density, (c) a close spatial relation between the PAH and molecular gas emission, but no predictive power of PAH emission for the molecular gas mass,(d) that the I-H color map is an excellent predictor of the distribution (and to a lesser degree the brightness) of CO emission, and (e) that the impact of massive (UV-intense) young star-forming regions on the bulk of the molecular gas in central ~9kpc can not be significant due to a complex spatial relation between molecular gas and star-forming regions that ranges from co-spatial to spatially offset to absent. The last point, in particular, highlights the importance of galactic environment -- and thus the underlying gravitational potential -- for the distribution of molecular gas and star formation.
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