Galaxy Cluster Mass Reconstruction Project: II. Quantifying scatter and bias using contrasting mock catalogues
L. Old, R. Wojtak, G. A. Mamon, R. A. Skibba, F. R. Pearce, D. Croton, S. Bamford, P. Behroozi, R. de Carvalho, J. C. Muñoz-Cuartas, D. Gifford, M. E. Gray, A. … 展开作者
L. Old, R. Wojtak, G. A. Mamon, R. A. Skibba, F. R. Pearce, D. Croton, S. Bamford, P. Behroozi, R. de Carvalho, J. C. Muñoz-Cuartas, D. Gifford, M. E. Gray, A. von der Linden, M. R. Merrifield, S. I. Muldrew, V. Müller, R. J. Pearson, T. J. Ponman, E. Rozo, E. Rykoff, A. Saro, T. Sepp, C. Sifón, E. Tempel
备注：
25 pages, 19 figures, 7 tables. Accepted for publication in MNRAS
This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the RMS errors in log M200c delivered by the different methods (0.18 to 1.08 dex, i.e., a factor of ~1.5 to 12), with abundance matching and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under- or over-estimated by a factor greater than 10. Given the steeply falling high-mass end of the cluster mass function, we recommend that richness or abundance matching-based methods are used in conjunction with these methods as a sanity check for studies selecting high mass clusters. We see a stronger correlation of the recovered to input number of galaxies for both catalogues in comparison with the group/cluster mass, however, this does not guarantee that the correct member galaxies are being selected. We do not observe significantly higher scatter for either mock galaxy catalogues. Our results have implications for cosmological analyses that utilise the masses, richnesses, or abundances of clusters, which have different uncertainties when different methods are used.
Mock Observatory: two thousand lightcone mock catalogues of luminous red galaxies from the Hyper Suprime-Cam Survey for the cosmological large-scale analysis
Modeling the HI-Halo Connection: Evolution, Scatter, and a Halo-based Prescription for 21-cm Mock Catalogs
INAF – Astronomical Observatory of Trieste（意大利国家天体物理研究所的里雅斯特天文台）；IFPU – Institute for Fundamental Physics of the Universe（宇宙基础物理研究所）；Observatoire de la Côte d’Azur, Laboratoire Lagrange（蔚蓝海岸天文台拉格朗日实验室）；Department of Physics & Astronomy, University of the Western Cape（西开普大学物理与天文学系）；Tianjin Astrophysics Center, Tianjin Normal University（天津师范大学天津天体物理中心）；Institute of Physics, Laboratory of Astrophysics, EPFL（洛桑联邦理工学院物理研究所天体物理实验室）
We present the Cardinal mock galaxy catalogs, a new version of the Buzzard simulation that has been updated to support ongoing and future cosmological surveys, including DES, DESI, and LSST. These catalogs are based on a one-quarter sky simulation populated with galaxies out to a redshift of $z=2.35$ to a depth of $m_{\rm{r}}=27$. Compared to the Buzzard mocks, the Cardinal mocks include an updated subhalo abundance matching (SHAM) model that considers orphan galaxies and includes mass-dependent scatter between galaxy luminosity and halo properties. This model can simultaneously fit galaxy clu…
The effect of baryons on the positions and velocities of satellite galaxies in the MTNG simulation
Universidad de Sevilla（塞维利亚大学）；Donostia International Physics Center（多诺斯蒂亚国际物理中心）；IKERBASQUE, Basque Foundation for Science（伊卡巴斯基，巴斯克科学基金会）；Institute for Computational Cosmology, Department of Physics, Durham University（杜伦大学物理学院计算宇宙学研究所）；Kavli Institute for Cosmology Cambridge（剑桥卡弗里宇宙学研究所）；Institute of Astronomy（天文学研究所）；Harvard-Smithsonian Center for Astrophysics（哈佛-史密森尼天体物理中心）；Columbia Astrophysics Laboratory, Columbia University（哥伦比亚大学天体物理学实验室）；Max Planck Institute for Astrophysics（马克斯·普朗克天体物理学研究所）
The scientific exploitation of the Dark Energy Spectroscopic Instrument Bright Galaxy Survey (DESI BGS) data requires the construction of mocks with galaxy population properties closely mimicking those of the actual DESI BGS targets. We create a high fidelity mock galaxy catalogue, including information about galaxies and their host dark matter subhaloes. The mock catalogue uses subhalo abundance matching (SHAM) with scatter to populate the P-Millennium N-body simulation with galaxies at the median BGS redshift of ~ 0.2, using formation redshift information to assign (g-r) rest-frame colours. …
Accurate mock catalogues are essential for assessing systematics in the cosmological analysis of large galaxy surveys. Anisotropic two-point clustering measurements from the same simulation show some scatter for different lines of sight (LOS), but are on average equal, due to cosmic variance. This results in scatter in the measured cosmological parameters. We use the OuterRim N-body simulation halo catalogue to investigate this, considering the 3 simulation axes as LOS. The quadrupole of the 2-point statistics is particularly sensitive to changes in the LOS, with sub-percent level differences …
We test different implementations of the halo occupation distribution (HOD) model to reconstruct the spatial distribution of galaxies as predicted by a publicly available semi-analytical model (SAM). We compare the measured two-point correlation functions of the HOD mock catalogues and the SAM samples to quantify the fidelity of the reconstruction. We use fixed number density galaxy samples selected according to stellar mass or star formation rate (SFR). We develop three different schemes to populate haloes with galaxies with increasing complexity, considering the scatter of the satellite HOD …
The most massive and luminous galaxies in the Universe serve as powerful probes to study the formation of structure, the assembly of mass, and cosmology. However, their detailed formation and evolution is still barely understood. Here we extract a sample of massive mock galaxies from the semi-analytical model of galaxy formation (SAM) GALACTICUS from the MultiDark-Galaxies, by replicating the CMASS photometric selection from the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). The comparison of the GALACTICUS CMASS-mock with BOSS-CMASS data allows us to explore different aspects of the…
Radio relics in galaxy clusters are believed to trace merger shock fronts. If cosmological structure formation determines the luminosity, size and shape distributions of radio relics then merger shocks need to be lighted up in a homogeneous way. We investigate if a mock relic sample, obtained from zoomed galaxy cluster simulations, is able to match the properties of relics measured in the NRAO VLA Sky Survey (NVSS). We compile a list of all radio relics known to date and homogeneously measure their parameters in all NVSS images and apply the same procedure to relics in our simulations. Number …
Testing the inference of kinematics from mock JWST NIRSpec/MSA observations of TNG50 galaxies at $z\sim2-6$
Max-Planck-Institut für Astronomie（马克斯·普朗克天文学研究所）；Fakultät für Physik und Astronomie, Universität Heidelberg（海德堡大学物理与天文学院）；Space Telescope Science Institute（太空望远镜科学研究所）
The thermal Sunyaev-Zel'dovich (tSZ) effect signal is widely recognized as a robust mass proxy of galaxy clusters with small intrinsic scatter. However, recent observational calibration of the tSZ scaling relation using weak lensing (WL) mass exhibits considerably larger scatter than the intrinsic scatter predicted from numerical simulations. This raises a question as to whether we can realize the full statistical power of ongoing and upcoming tSZ-WL observations of galaxy clusters. In this work, we investigate the origin of observed scatter in the tSZ-WL scaling relation, using mock maps of g…
The impact of source and survey modelling on the connection between [O III] emitters and Ly $α$ forest transmission at z ~ 6
The University of Nottingham（诺丁汉大学）；University of Edinburgh（爱丁堡大学）；Kavli Institute for Cosmology（卡弗里宇宙学研究所）；Tata Institute of Fundamental Research（塔塔基础研究所）；Leibniz-Institut für Astrophysik Potsdam（波茨坦阿斯特拉物理研究所）
We describe an extension of the halo-based galaxy group-finding algorithm. We add freedom to the algorithm in order to more accurately determine which galaxies are central and which are satellites, and to provide unbiased estimates of halo masses. We focus on determination of the galaxy-halo relations for star-forming and quiescent galaxies. The added freedom in the group-finding algorithm is self-calibrated using observations of color-dependent galaxy clustering, as well as measurements of the total satellite luminosity in deep imaging data around stacked samples of spectroscopic central gala…
We present a machine-learning approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep machine learning tool commonly used in image recognition tasks. The CNN is trained and tested on our sample of 7,896 Chandra X-ray mock observations, which are based on 329 massive clusters from the IllustrisTNG simulation. Our CNN learns from a low resolution spatial distribution of photon counts and does not use spectral information. Despite our simplifying assumption to neglect spectral information, the resulting mass values estimated …
An excess up-scattering mass bias on a weak lensing cluster mass estimate is a statistical bias that an observed weak lensing mass ($M_{\rm obs}$) of a cluster of galaxies is, in a statistical sense, larger than its true mass ($M_{\rm true}$) because of a higher chance of up-scattering than that of down-scattering due to random noises in a weak lensing cluster shear profile. This non-symmetric scattering probability is caused by a monotonically decreasing cluster mass function with increasing mass. We examine this bias (defined by $b=M_{\rm obs}/M_{\rm true}$) in weak lensing shear-selected cl…
Photo-z error is one of the major sources of systematics degrading the accuracy of weak lensing cosmological inferences. Zhang et al. (2010) proposed a self-calibration method combining galaxy-galaxy correlations and galaxy-shear correlations between different photo-z bins. Fisher matrix analysis shows that it can determine the rate of photo-z outliers at a level of 0.01-1% merely using photometric data and do not rely on any prior knowledge. In this paper, we develop a new algorithm to implement this method by solving a constrained nonlinear optimization problem arising in the self-calibratio…
We develop a method to simulate galaxy-galaxy weak lensing by utilizing all-sky, light-cone simulations and their inherent halo catalogs. Using the mock catalog to study the error covariance matrix of galaxy-galaxy weak lensing, we compare the full covariance with the "jackknife" (JK) covariance, the method often used in the literature that estimates the covariance from the resamples of the data itself. We show that there exists the variation of JK covariance over realizations of mock lensing measurements, while the average JK covariance over mocks can give a reasonably accurate estimation of …
We develop a machine learning algorithm to infer the 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich effect maps. We generate around 73,000 mock images along various lines of sight using 2,522 simulated clusters from the \thethreehundred{} project at redshift $z< 0.12$ and train a model that combines an autoencoder and a random forest. Without making any prior assumptions about the hydrostatic equilibrium of the clusters, the model is capable of reconstructing the total mass profile as well as the gas mass profile, which is responsible for…
We demonstrate the ability of convolutional neural networks (CNNs) to mitigate systematics in the virial scaling relation and produce dynamical mass estimates of galaxy clusters with remarkably low bias and scatter. We present two models, CNN$_\mathrm{1D}$ and CNN$_\mathrm{2D}$, which leverage this deep learning tool to infer cluster masses from distributions of member galaxy dynamics. Our first model, CNN$_\text{1D}$, infers cluster mass directly from the distribution of member galaxy line-of-sight velocities. Our second model, CNN$_\text{2D}$, extends the input space of CNN$_\text{1D}$ to le…
We present a machine learning approach for estimating galaxy cluster masses, trained using both Chandra and eROSITA mock X-ray observations of 2,041 clusters from the Magneticum simulations. We train a random forest regressor, an ensemble learning method based on decision tree regression, to predict cluster masses using an input feature set. The feature set uses core-excised X-ray luminosity and a variety of morphological parameters, including surface brightness concentration, smoothness, asymmetry, power ratios, and ellipticity. The regressor is cross-validated and calibrated on a training sa…
J-PAS & FLAMINGO: Cosmic voids and void galaxies in the gravitational landscape of photometric surveys
University of Tartu（塔尔图大学）；University of Groningen（格罗宁根大学）；University of Turku（图尔库大学）；Leiden University（莱顿大学）；Universidade de São Paulo（圣保罗大学）；Instituto de Astronomia, Geofísica e Ciências Atmosféricas da USP（圣保罗大学天文、地球物理与大气科学研究所）；Centro de Estudios de Física del Cosmos de Aragón (CEFCA)（阿拉贡宇宙物理研究中心）
Machine learning (ML) techniques, in particular supervised regression algorithms, are a promising new way to use multiple observables to predict a cluster's mass or other key features. To investigate this approach we use the \textsc{MACSIS} sample of simulated hydrodynamical galaxy clusters to train a variety of ML models, mimicking different datasets. We find that compared to predicting the cluster mass from the $σ-M$ relation, the scatter in the predicted-to-true mass ratio is reduced by a factor of 4, from $0.130\pm0.004$ dex (${\simeq} 35$ per cent) to $0.031 \pm 0.001$ dex (${\simeq} 7$ p…
Challenges of standard halo models in constraining galaxy properties from CIB anisotropies
Institutes of Computer Science and Astrophysics, Foundation for Research and Technology Hellas (FORTH)（计算机科学与天体物理研究所，希腊研究与技术基金会）；Aix Marseille Univ, CNRS, CNES, LAM（艾克斯马赛大学）；Université de Strasbourg, CNRS, Observatoire astronomique de Strasbourg, UMR 7550（斯特拉斯堡大学）；Kavli Institute for Particle Astrophysics and Cosmology, Stanford University（斯坦福大学卡弗里粒子天体物理学与宇宙学研究所）；SLAC National Accelerator Laboratory（SLAC国家加速器实验室）
Denoising clustering covariance matrices with Rotational Invariant Estimators
INAF - Osservatorio Astronomico di Brera（意大利国家天体物理研究所布拉拉天文台）；Dipartimento di Fisica, Università degli Studi di Genova（热那亚大学物理系）；INFN - Sezione di Genova（意大利国家核物理研究所热那亚分部）；Dipartimento di Fisica e Astronomia Augusto Righi, Università di Bologna（博洛尼大学奥古斯托·里基物理与天文学系）
Galaxy clusters can act as gravitational lenses to magnify the universe behind them, allowing us to see deep into the early universe. The Hubble Space Telescope Frontier Fields program (Lotz et al. 2017) uses six galaxy clusters imaged by Hubble to discover and study galaxies at z ~ 5-10. Seven independent teams developed lens models and derived magnifications for each galaxy cluster, based on positional and redshift constraints from the best available data at the time. In this work we evaluate ten models for MACSJ0416.1-2403, which were made public in 2015, by contrasting them with new spectr…
We present a Bayesian hierarchical inference formalism to study the relation between the properties of dark matter halos and those of their central galaxies using weak gravitational lensing. Unlike traditional methods, this technique does not resort to stacking the weak lensing signal in bins, and thus allows for a more efficient use of the information content in the data. Our method is particularly useful for constraining scaling relations between two or more galaxy properties and dark matter halo mass, and can also be used to constrain the intrinsic scatter in these scaling relations. We sho…
We perform the first application of the wavelet scattering transform (WST) to actual galaxy observations, through a WST analysis of the BOSS DR12 CMASS dataset. We included the effects of redshift-space anisotropy, non-trivial survey geometry, systematic weights, and the Alcock-Paczynski distortion effect, following the commonly adopted steps for the power spectrum analysis. In order to capture the cosmological dependence of the WST, we use galaxy mocks obtained from the state-of-the-art ABACUSSUMMIT simulations, tuned to match the anisotropic correlation function of the BOSS CMASS sample in t…
