An official website of the United States government
Abstract There is untapped cosmological information in galaxy redshift surveys in the nonlinear regime. In this work, we use theAemulussuite of cosmologicalN-body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales (0.1–50h−1Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation functionwp(rp), the redshift-space monopole of the correlation functionξ0(s), and the quadrupoleξ2(s)—we emulate statistics that include information about the local environment, namely the underdensity probability functionPU(s) and the density-marked correlation functionM(s). This extends the model ofAemulusIII for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: includingPU(s) andM(s) improves the precision of our constraints on Ωmby 27%,σ8by 19%, and the growth of structure parameter,fσ8, by 12% compared to standard statistics. We additionally find that scales below ∼6h−1Mpc contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy–halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.
more »
« less
Non-parametric Lagrangian biasing from the insights of neural nets
Abstract We present a Lagrangian model of galaxy clustering bias in which we train a neural net using the local properties of the smoothed initial density field to predict the late-time mass-weighted halo field.By fitting the mass-weighted halo field in theAbacusSummitsimulations atz= 0.5, we find that including three coarsely spaced smoothing scales gives the best recovery of the halo power spectrum. Adding more smoothing scales may lead to 2–5% underestimation of the large-scale power and can cause the neural net to overfit.We find that the fitted halo-to-mass ratio can be well described by two directions in the original high-dimension feature space.Projecting the original features into these two principal components and re-training the neural net either reproduces the original training result, or outperforms it with a better match of the halo power spectrum. The elements of the principal components are unlikely to be assigned physical meanings, partly owing to the features being highly correlated between different smoothing scales.Our work illustrates a potential need to include multiple smoothing scales when studying galaxy bias, and this can be done easily with machine-learning methods that can take in high dimensional input feature space.
more »
« less
- Award ID(s):
- 2019786
- PAR ID:
- 10505454
- Publisher / Repository:
- IOP
- Date Published:
- Journal Name:
- Journal of Cosmology and Astroparticle Physics
- Volume:
- 2023
- Issue:
- 05
- ISSN:
- 1475-7516
- Page Range / eLocation ID:
- 040
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract We present radial profiles of luminosity-weighted age (ageL) and ΔΣSFRfor various populations of high- and low-mass central and satellite galaxies in the TNG100 cosmological simulation. Using these profiles, we investigate the impact of intrinsic and environmental factors on the radial distribution of star formation. For both central galaxies and satellites, we investigate the effects of black hole mass, cumulative active galactic nucleus (AGN) feedback energy, morphology, halo mass, and local galaxy overdensity on the profiles. In addition, we investigate the dependence of radial profiles of the satellite galaxies as a function of the redshifts at which they joined their hosts, as well as the net change in star-forming gas mass since the satellites joined their host. We find that high-mass (M*> 1010.5M⊙) central and satellite galaxies show evidence of inside-out quenching driven by AGN feedback. Effects from environmental processes only become apparent in averaged profiles at extreme halo masses and local overdensities. We find that the dominant quenching process for low-mass galaxies (M*< 1010M⊙) is environmental, generally occurring at low halo mass and high local galaxy overdensity for low-mass central galaxies and at high host halo masses for low-mass satellite galaxies. Overall, we find that environmental processes generally drive quenching from the outside-in.more » « less
-
Abstract This paper represents an effort to provide robust constraints on the galaxy–halo connection and simultaneously test the Planck ΛCDM cosmology using a fully numerical model of small-scale galaxy clustering. We explore two extensions to the standard Halo Occupation Distribution model: assembly bias, whereby halo occupation depends on both halo mass and the larger environment, and velocity bias, whereby galaxy velocities do not perfectly trace the velocity of the dark matter within the halo. Moreover, we incorporate halo mass corrections to account for the impact of baryonic physics on the halo population. We identify an optimal set of clustering measurements to constrain this “decorated” HOD model for both low- and high-luminosity galaxies in SDSS DR7. We find that, for low-luminosity galaxies, a model with both assembly bias and velocity bias provides the best fit to the clustering measurements, with no tension remaining in the fit. In this model, we find evidence for both central and satellite galaxy assembly bias at the 99% and 95% confidence levels, respectively. In addition, we find evidence for satellite galaxy velocity bias at the 99.9% confidence level. For high-luminosity galaxies, we find no evidence for either assembly bias or velocity bias, but our model exhibits significant tension with SDSS measurements. We find that all of these conclusions still stand when we include the effects of baryonic physics on the halo mass function, suggesting that the tension we find for high-luminosity galaxies may be due to a problem with our assumed cosmological model.more » « less
-
ABSTRACT Cosmological constraints from current and upcoming galaxy cluster surveys are limited by the accuracy of cluster mass calibration. In particular, optically identified galaxy clusters are prone to selection effects that can bias the weak lensing mass calibration. We investigate the selection bias of the stacked cluster lensing signal associated with optically selected clusters, using clusters identified by the redMaPPer algorithm in the Buzzard simulations as a case study. We find that at a given cluster halo mass, the residuals of redMaPPer richness and weak lensing signal are positively correlated. As a result, for a given richness selection, the stacked lensing signal is biased high compared with what we would expect from the underlying halo mass probability distribution. The cluster lensing selection bias can thus lead to overestimated mean cluster mass and biased cosmology results. We show that the lensing selection bias exhibits a strong scale dependence and is approximately 20–60 per cent for ΔΣ at large scales. This selection bias largely originates from spurious member galaxies within ±20–60 $$h^{-1}\, \rm Mpc$$ along the line of sight, highlighting the importance of quantifying projection effects associated with the broad redshift distribution of member galaxies in photometric cluster surveys. While our results qualitatively agree with those in the literature, accurate quantitative modelling of the selection bias is needed to achieve the goals of cluster lensing cosmology and will require synthetic catalogues covering a wide range of galaxy–halo connection models.more » « less
-
Abstract Ultra-diffuse galaxies (UDGs) are both extreme products of galaxy evolution and extreme environments in which to test our understanding of star formation. In this work, we contrast the spatially resolved star formation activity of a sample of 22 Hi-selected UDGs and 35 low-mass galaxies from the NASA Sloan Atlas (NSA) catalog within 120 Mpc. We employ a new joint spectral energy distribution fitting method to compute star formation rate and stellar mass surface density maps that leverage the high spatial resolution optical imaging data of the Hyper Suprime-Cam Subaru Strategic Program and the UV coverage of the Galaxy Evolution Explorer, along with Hiradial profiles estimated from a subset of galaxies that have spatially resolved Himaps. We find that UDGs have low star formation efficiencies as a function of their atomic gas down to scales of 500 pc. We additionally find that the stellar mass-weighted sizes of our UDG sample are unremarkable when considered as a function of their Himass—their stellar sizes are comparable to NSA dwarfs at fixed Himass. This is a natural result in the picture where UDGs are forming stars normally, but at low efficiencies. We compare our results to predictions from contemporary models of galaxy formation, and find in particular that our observations are difficult to reproduce in models where UDGs undergo stellar expansion due to vigorous star formation feedback should bursty star formation be required down toz= 0.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1088/1475-7516/2023/05/040
