1812.05105
Searching for oscillations in the primordial power spectrum with CMB and LSS Data
Zeng, et al
Different inflationary models predict oscillatory features in the primordial power spectrum. These can leave imprint on both the CMB and LSS of our Universe, that can be searched for the current data. Inspired by the axion-monodromy model of inflation, search for primordial oscillations that are logarithmic in wavenumber, using both CMB data from the Planck satellite and LSS data from the WiggleZ galaxy survey. Find that, within the search range for the new oscillation parameters (amplitude, frequency and phase), both CMB-only and CMB+LSS data yield the same best-fit oscillation frequency of log_10 omega = 1.5, improving the fit over LCDM by Delta chi^2 = -9 and Delta chi^2 = -13 (roughly corresponding to 2 sigma and 2.8 sigma significance), respectively. Bayesian evidence for the log-oscillation model versus LCDM indicates a very slight preference for the latter. Future CMB and LSS data will further probe this scenario.
1812.05113
Explicit Bayesian treatment of unknown foreground contaminations in galaxy surveysPorqueres, et al
The treatment of unknown foreground contaminations will be one of the major challenges for galaxy clustering analyses of coming decadal surveys. These data contaminations introduce erroneous large-scale effects in recovered power spectra and inferred DM density fields. In this work, present an effective solution to this problem in terms of a robust likelihood designed to account for effects due to unknown foreground and target contaminations. Conceptually, this robust likelihood marginalizes over the unknown large-scale contamination amplitudes. Showcase the effectiveness of this novel likelihood via an application to a mock SDSS-III data set subject to dust extinction contamination. In order to illustrate the performance of the proposed likelihood, infer the underlying DM density field and reconstruct the matter power spectrum while being maximally agnostic about the foregrounds. These results are contrasted to an analysis with a standard Poisson likelihood, as typically used in modern large-scale structure analyses. While the standard Poissonian analyses yields excessive power for large-scale modes and introduces an overall bias in the power spectrum, their likelihood provides unbiased estimates of the matter power spectrum over the entire range of Fourier modes considered in this work. Further demonstrate that the approach accurately accounts for and corrects effects of unknown foreground contaminations when inferring three-dimensional density fields. Robust likelihood approaches, as presented in this work, will be crucial to control unknown systematics and maximize the outcome of the decadal surveys.
1812.05116
Dark energy survey year 1 results: validation of weak lensing cluster member contamination estimates from P(z) decomposition
Varga, et al
WL source galaxy catalogs used in estimating the masses of galaxy clusters can be heavily contaminated by cluster members, prohibiting accurate mass calibration. In this study, test the performance of an estimator for the extent of cluster member contamination based on decomposing the photometric redshift P(z) of source galaxies into contaminating and background components. Perform a full survey mock analysis on a simulated sky survey approximately mirroring the true number profile of contaminating cluster member galaxies in the simulation and the estimated one. Further apply the method to estimate the cluster member contamination for the DES Y1 redMaPPer cluster mass calibration analysis, and compare the results to an alternative approach based on the angular correlation of WL source galaxies. Find indications that correlation based estimates are biased by the selection of the WL sources in the cluster vicinity, which does not strongly impact the P(z) decomposition method. Collectively, these benchmarks demonstrate the strength of the P(z) decomposition method in alleviating membership contamination and enabling highly accurate cluster WL studies without broad exclusion of source galaxies, thereby improving the total constraining power of cluster mass calibration via weak lensing.
1812.05594
On the road to per-cent accuracy: nonlinear reaction of the matter power spectrum to dark energy and modified gravity
Cataneo, et al
Present a general method to compute the nonlinear matter power spectrum for DE and modified gravity scenarios with % level accuracy. By adopting the halo model and nonlinear perturbation theory, predict the reaction of a LCDM matter power spectrum to the physics of an extended cosmo parameter space. By comparing the predictions to N-body sims, demonstrate that with no-free parameters, can recover the nonlinear matter power spectrum for a wide range of different w0-wa DE models to better than 1% accuracy out to k~1 h Mpc^{-1}. Obtain a similar performance for both DGP and f(R) gravity, with the nonlinear matter power spectrum predicted to better than 3% accuracy over the same range of scales. When including direct measurements of the halo mass function from the simulations, this accuracy improves to 1%. With a single suite of standard LCDM N-body sims, the methodology provides a direct route to constrain a wide range of non-standard extensions to the concordance cosmology in the high S/N NL regime.
1812.05608
An older, more quiescent universe from Panchromatic SED fitting of the 3D-HST survey
Leja, et al
Galaxy observations are influenced by many physical parameters: stellar masses, star formation fates (SFRs), SFHs, metallicities, dust ,BH activity, and more. As a result, inferring accurate physical parameters requires high-dimensional models which capture or marginalize over this complexity. Here, re-assess inferences of galaxy stellar masses and SFRs using the 14-paramter physical model Prospector-Alpha build in the Prospector Bayesian inference framework. Fit the photometry of 58,461 galaxies from the 3D-HST catalogs at 0.5<z<2.5. The resulting stellar masses are ~0.1-0.3 dex larger than the fiducial masses while remaining consistent with dynamical constraints. This change is primarily due to the systematically older SFHs inferred with Prospector. The SFRs are ~0.1-1+ dex lower than UV+IR SFRs, with the largest offsets caused by emission from "old" (t>100 Myr) stars. These new inferences lower the observed cosmic star formation rate density by ~0.2 dex and increase the observed stellar mass growth by ~0.1 dex, finally bringing these two quantities into agreement and implying an older, more quiescent Universe than found by previous studies at these redshifts. Corroborate these results by showing that the Prospector-Alpha SFHs are both more physically realistic and are much better predictors of the evolution of the stellar mass function. Finally, highlight examples of observational data which can break degeneracies in the current model; these observations can be incorporated into prior's in future models to produce new & more accurate physical parameters.
1812.05613
A conclusive test for star formation prescriptions in cosmological hydrodynamical simulations
Buck, Dutton, Maccio
State-of-the-art cosmo hydro sims of galaxy formation have reached the point at which their outcomes result in galaxies with ever more realism. Still, the employed sub-grid models include several free parameters such as the density threshold, n, to localize the SF gals. In this work, investigate the possibilities to utilize the observed clustered nature of SF in order to refine SF prescriptions and constrain the density threshold parameter. To this end, measure the clustering strength, correlation length and power-law index of the 2pt correlation function of young (tau<50 Myr) stellar particles and compare the results to observations from the HST Legacy Extragalactic UV survey (LEGUS). Simulations reveal a clear trend of larger clustering signal and power-law index and lower correlation length as the SF threshold increases with only mild dependence on galaxy properties such as stellar mass or specific SFR. In conclusion, find that the observed clustering of SF is inconsistent with a low threshold for SF (n<1 cm^{-3}) and strongly favors a high density threshold for SF (n>10 cm^{-3}) which in cosmological hydrodynamical sims (evolved to z=0) is currently only employed by the NIHAO and FIRE simulations.
1812.05733
Constraining scatter in the stellar mss-halo mass relation for haloes less massive than the Milky Way
Allen, Behroozi, Ma
Most galaxies are hosted by massive, invisible DM haloes, yet little is known about the scatter in the stellar mass--hallo mass relation for galaxies with host halo masses M_h <= 1e11 Msun. Using mock catalogues based on DM simulations, find that two observable signatures are sensitive to scatter in the stellar mass--halo mass relation even at these mass scales; i.e., conditional stellar mass functions and velocity distribution functions for neighboring galaxies. Compute these observables for 179,373 galaxies in SDSS with stellar masses M*>1e9 Msun and 0.01<z<0.307. Then compare to mock observations generated from the Bolshoi-Planck DM sims for stellar mass-halo mass scatters ranging from 0 to 0.6 dex. The observed results are consistent with simulated results for low values of scatter (~0.2 dex), but SDSS statistics are insufficient to provide firm constraints. This method could provide much tighter constraints on stellar mass--halo mass scatter in the future if applied to larger data sets, especially the anticipated DE spectroscopic instrument bright galaxy survey, and constraining the scatter could have important implications for galaxy formation and evolution.
1812.05777
Numerical convergence of simulations of galaxy formation: the abundance and internal structure of cold dark matter haloes
Ludlow, Schaye, Bower
Study the impact of numerical parameters on the properties of CDM haloes formed in collisionless cosmological simulations. Quantify convergence in the median spherically-averaged circular velocity profiles for haloes of widely varying particle number, as well as in the statistics of their structural scaling relations and mass functions. In agreement with prior work focused on single haloes, the results suggest that cosmological simulations yield robust halo properties for a wide range of softening parameters, epsilon, provided: 1) epsilon is not larger than a "convergence radius", r_conv, which is dictated by 2-body relaxation and determined by particle number, and 2) sufficient number of time steps are taken to accurately resolve particle orbits with short dynamical times. Provided these conditions are met, median circular velocity profiles converge to within approx 10% for radii beyond which the local 2-body relaxation timescale exceeds the Hubble time by a factor kappa == t_relax/t_H>0.177, with better convergence attained for higher kappa. Provide analytic estimates of r_conv that build on previous attempts in two ways: first, by highlighting its explicit (but weak) softening-dependence and, second, by providing a simple criterion in which r_conv is determined entirely by the mean inter particle spacing, ell; for example, <10% convergence in circular velocity for r>0.05 ell. Show how these analytic criteria can be used to assess convergence in structural scaling relations for dark matter haloes as a function of their mass or maximum circular speed, V_max. The convergence radius is smaller than the virial radius, r_200, of all haloes resolved with >=32 particles, a result that is verified explicitly using the suite of sims.
1812.05781
Denoising weak lensing mass maps with deep learning
Shirasaki, et al
WL is a powerful probe of the large-scale cosmic matter distribution. Wide-field galaxy surveys allow us to generate the so-called WL maps, but actual observations suffer from noise due to imperfect measurement of galaxy shape distortions and to the limited number density of the source galaxies. In this paper, explore a deep-learning approach to reduce the noise. Develop an image-to-image translation method with conditional adversarial networks (CANs), which learn efficient mapping from ain input noise WL map to the underlying noise field. Train the CANs using 30000 image pairs obtained from 1000 ray-tracing sims of WL. Show that the trained CANs reproduce the true 1pt probability distribution function of the noiseless lensing map with a bias less than 1 sigma on average, where sigma is the statistical error. Since a number of model parameters are used in the CANs, the method has additional error budgets when reconstructing the summary statistics of WL maps. The typical amplitude of such reconstruction error is found to be of 1-2 sigma level. Interestingly, pixel-by-pixel denoising for under-dense regions is less biased than denoising over-dense regions. The deep-learning approach is complementary to existing analysis methods which focus on clustering properties and peak statistics of WL maps.
1812.05995
Core cosmology library: precision cosmological predictions for LSST
Chisari, et al
The Core Cosmology Library (CCL) provides routines to compute basic cosmological observables to a high degree of accuracy, which have been verified with an extensive suite of validation tests. Predictions are provided for many cosmological quantities, including distances, angular power spectra, correlation functions, halo bias and the halo mass function through state-of-the-art modeling prescriptions available in the literature. Fiducial specifications for the expected galaxy distributions for LSST are also included, together with the capability of computing redshift distributions for a user-defined photometric redshift model. A rigorous validation procedure, based on comparisons between CCL and independent software packages, allows establishment of a well-defined numerical accuracy for each predicted quantity. As a result, predictions for correlation functions of galaxy clustering, gg lensing and cosmic shear are demonstrated to be within a fraction of the expected statistical uncertainty of the observables for the models and in the range of scales of interest to LSST. CCL is an open source software package written in C, with a python interface and publicly available at GitHub.com/LSSTDESC/CCL.
1812.06076
KiDS+VIKING-450: Cosmic shear tomography with optical+infrared data
Hildebrandt, et al
Present a tomographic cosmic shear analysis of KiDS combined with the VISTA Kilo-Degree Infrared Galaxy Survey (VIKING). This is the first time that a full optical to near-infrared data set has been used for a wide-field cosmo WL experiment. This unprecedented data, spanning 450-deg^2, allows significant improvement of the estimation of photo-z, such that robustly higher-z sources can be included for the lensing measurement, and most importantly, solidify the knowledge of the z distributions of the sources. Based on a flat LCDM model, find S8==sigma8 sqrt(Omega_m/0.3)=0.737-0.036+0.040 in a blind analysis from cosmic shear alone. The tension between KiDS cosmic shear and the Planck Legacy CMB measurements remains in this systematically more robust analysis, with S8 differing by 2.3 sigma. This result is insensitive to changes in the priors on nuisance parameters for IA, baryon feedback, and neutrino mass. KiDS shear measurements are calibrated with a new, more realistic set of image simulations and no significant B-modes are detected in the survey, indicating that systematic errors are under control When calibrating the redshift distributions by assuming the 30-band COSMOS-2015 photo-z are correct (following DES and HSC), find the tension with Planck is alleviated. The COSMOS-2015-calibrated KiDS z distributions are however discrepant with the results from the extensive spectroscopic calibration sample and the distributions recovered using angular clustering measurements, which is deemed more reliable. The robust determination of source z distributions remains one of the most challenging aspects for future cosmic shear surveys.
1812.06077
KiDS_VIKING-450: A new combined optical & near-IR dataset for cosmology and astrophysics
Wright, et al
Present the curation and verification of a new combined optical and NIR dataset for cosmo and astrophysics, derived from the combination of ugri-band imaging from KiDS and ZYJHKs-band imaging from VIKING. This dataset is unrivaled in cosmological imaging surveys due to tis combination of area 458 deg^2 before masking), depth (r<=25), and wavelength coverage (ugriZYJHKs). The combination of survey depth, area and (most importantly) wavelength coverage allows significant reductions in systematic uncertainties (i.e. reductions of between 10 and 60% in bias, outlier rate, and scatter) in photometric-to-spectroscopic z comparisons, compared to the optical-only case at photo-z above 0.7. The complementarily between the optical and NIR surveys means that over 80% of the sources, across all photo-z, have significant detection (i.e. not upper limits) in the 8 reddest bands. Derive photometry, photo-z, and stellar masses for all sources in the survey, and verify these data products against existing spectroscopic galaxy sample. Demonstrate the fidelity of the higher-level data products by constructing the survey stellar mass functions in 8 volume-complete z bins. Find that these photometrically derived mass functions provide excellent agreement with previous mass evolution studies derived using spectroscopic surveys. The primary data products presented in this paper are publicly available at kids.strw.leidenuniv.nl.
No comments:
Post a Comment