The Three Hundred : contrasting clusters galaxy density in hydrodynamical and dark matter simulations

Cluster number counts will be a key cosmological probe in the next decade thanks to the Euclid satellite mission. For this purpose, cluster detection algorithm performance, which are sensitive to the spatial distribution of the cluster galaxy members and their luminosity function, need to be accurately characterized. Using The Three Hundred hydrodynamical and dark matter only simulations we study a complete sample of massive clusters beyond 7 (5) $\times$ 10$^{14}$ M$_{\odot}$ at redshift 0 (1) on a $(1.48 \ \mathrm{Gpc})^3$ volume. We find that the mass resolution of the current hydrodynamical simulations (1.5 $\times$ 10$^9$ M$_{\odot}$) is not enough to characterize the luminosity function of the sample in the perspective of Euclid data. Nevertheless, these simulations are still useful to characterize the spatial distribution of the cluster substructures assuming a common relative mass threshold for the different flavours and resolutions. By comparing with the dark matter only version of these simulations, we demonstrate that baryonic physics preserves significantly low mass subhalos (galaxies) as have also been observed in previous studies with less statistics. Furthermore, by comparing the hydro simulations with higher resolution dark matter only simulations of the same objects and taking the same limit in subhalo mass we find significantly more cuspy galaxy density profiles towards the center of the clusters, where the low mass substructures would tend to concentrate. We conclude that using dark matter only simulation may lead to some biases on the spatial distribution and density of galaxy cluster members. Based on the preliminary analysis of few high resolution hydro simulations we conclude that a mass resolution of 1.8 $\times$ 10$^8$ h$^{-1}$ M$_{\odot}$ will be needed for The Three Hundred simulations to approach the expected magnitude limits for the Euclid survey

Prospects for high-z cluster detections with Planck, based on a follow-up of 28 candidates using MegaCam@CFHT

The Planck catalogue of SZ sources limits itself to a significance threshold of 4.5 to ensure a low contamination rate by false cluster candidates. This means that only the most massive clusters at redshift z>0.5, and in particular z>0.7, are expected to enter into the catalogue, with a large number of systems in that redshift regime being expected around and just below that threshold. In this paper, we follow-up a sample of SZ sources from the Planck SZ catalogues from 2013 and 2015. In the latter maps, we consider detections around and at lower significance than the threshold adopted by the Planck Collaboration. To keep the contamination rate low, our 28 candidates are chosen to have significant WISE detections, in combination with non-detections in SDSS/DSS, which effectively selects galaxy cluster candidates at redshifts $z\gtrsim0.5$. By taking r- and z-band imaging with MegaCam@CFHT, we bridge the 4000A rest-frame break over a significant redshift range, thus allowing accurate redshift estimates of red-sequence cluster galaxies up to z~0.8. After discussing the possibility that an overdensity of galaxies coincides -by chance- with a Planck SZ detection, we confirm that 16 of the candidates have likely optical counterparts to their SZ signals, 13 (6) of which have an estimated redshift z>0.5 (z>0.7). The richnesses of these systems are generally lower than expected given the halo masses estimated from the Planck maps. However, when we follow a simplistic model to correct for Eddington bias in the SZ halo mass proxy, the richnesses are consistent with a reference mass-richness relation established for clusters detected at higher significance. This illustrates the benefit of an optical follow-up, not only to obtain redshift estimates, but also to provide an independent mass proxy that is not based on the same data the clusters are detected with, and thus not subject to Eddington bias.Comment: 13 pages, 7 figures. Accepted for publication in A&

The 1989 and 2015 outbursts of V404 Cygni: a global study of wind-related optical features

The black hole transient V404 Cygni exhibited a bright outburst in June 2015 that was intensively followed over a wide range of wavelengths. Our team obtained high time resolution optical spectroscopy (~90 s), which included a detailed coverage of the most active phase of the event. We present a database consisting of 651 optical spectra obtained during this event, that we combine with 58 spectra gathered during the fainter December 2015 sequel outburst, as well as with 57 spectra from the 1989 event. We previously reported the discovery of wind-related features (P-Cygni and broad-wing line profiles) during both 2015 outbursts. Here, we build diagnostic diagrams that enable us to study the evolution of typical emission line parameters, such as line fluxes and equivalent widths, and develop a technique to systematically detect outflow signatures. We find that these are present throughout the outburst, even at very low optical fluxes, and that both types of outflow features are observed simultaneously in some spectra, confirming the idea of a common origin. We also show that the nebular phases depict loop patterns in many diagnostic diagrams, while P-Cygni profiles are highly variable on time-scales of minutes. The comparison between the three outbursts reveals that the spectra obtained during June and December 2015 share many similarities, while those from 1989 exhibit narrower emission lines and lower wind terminal velocities. The diagnostic diagrams presented in this work have been produced using standard measurement techniques and thus may be applied to other active low-mass X-ray binaries.Comment: Accepted for publication in MNRAS. 23 pages paper, plus a 9 pages appendix with extra tables and figures. 18 figures are included in the paper and 8 in the appendi

The hydrostatic-to-lensing mass bias from resolved X-ray and optical-IR data

An accurate reconstruction of galaxy cluster masses is key to use this population of objects as a cosmological probe. In this work we present a study on the hydrostatic-to-lensing mass scaling relation for a sample of 53 clusters whose masses were reconstructed homogeneously in a redshift range between $z= 0.05$ and $1.07$. The $M_{500}$ mass for each cluster was indeed inferred from the mass profiles extracted from the X-ray and lensing data, without using a priori observable-mass scaling relations. We assessed the systematic dispersion of the masses estimated with our reference analyses with respect to other published mass estimates. Accounting for this systematic scatter does not change our main results, but enables the propagation of the uncertainties related to the mass reconstruction method or used dataset. Our analysis gives a hydrostatic-to-lensing mass bias of $(1-b) =0.739^{+0.075}_{-0.070}$ and no evidence of evolution with redshift. These results are robust against possible subsample differences

Galaxy cluster mass bias from projected mass maps: The Three Hundred-NIKA2 LPSZ twin samples

The determination of the mass of galaxy clusters from observations is subject to systematic uncertainties. Beyond the errors due to instrumental and observational systematic effects, in this work we investigate the bias introduced by modelling assumptions. In particular, we consider the reconstruction of the mass of galaxy clusters from convergence maps employing spherical mass density models. We make use of The Three Hundred simulations, selecting clusters in the same redshift and mass range as the NIKA2 Sunyaev-Zel'dovich Large Program sample: $3 \leq M_{500}/ 10^{14} \mathrm{M}_{\odot} \leq 10$ and $0.5 \leq z \leq 0.9$. We study different modelling and intrinsic uncertainties that should be accounted for when using the single cluster mass estimates for scaling relations. We confirm that the orientation of clusters and the radial ranges considered for the fit have an important impact on the mass bias. The effect of the projection adds uncertainties to the order of $10\%$ to $14\%$ to the mass estimates. We also find that the scatter from cluster to cluster in the mass bias when using spherical mass models is less than $20\%$ of the true mass of the clusters

CHEX-MATE: A non-parametric deep learning technique to deproject and deconvolve galaxy cluster X-ray temperature profiles

Temperature profiles of the hot galaxy cluster intracluster medium (ICM) have a complex non-linear structure that traditional parametric modelling may fail to fully approximate. For this study, we made use of neural networks, for the first time, to construct a data-driven non-parametric model of ICM temperature profiles. A new deconvolution algorithm was then introduced to uncover the true (3D) temperature profiles from the observed projected (2D) temperature profiles. An auto-encoder-inspired neural network was first trained by learning a non-linear interpolatory scheme to build the underlying model of 3D temperature profiles in the radial range of [0.02-2] R$_{500}$, using a sparse set of hydrodynamical simulations from the THREE HUNDRED PROJECT. A deconvolution algorithm using a learning-based regularisation scheme was then developed. The model was tested using high and low resolution input temperature profiles, such as those expected from simulations and observations, respectively. We find that the proposed deconvolution and deprojection algorithm is robust with respect to the quality of the data, the morphology of the cluster, and the deprojection scheme used. The algorithm can recover unbiased 3D radial temperature profiles with a precision of around 5\% over most of the fitting range. We apply the method to the first sample of temperature profiles obtained with XMM{\it -Newton} for the CHEX-MATE project and compared it to parametric deprojection and deconvolution techniques. Our work sets the stage for future studies that focus on the deconvolution of the thermal profiles (temperature, density, pressure) of the ICM and the dark matter profiles in galaxy clusters, using deep learning techniques in conjunction with X-ray, Sunyaev Zel'Dovich (SZ) and optical datasets.Comment: 32 pages, 30 figures, 6 tables, Accepted in A&

CHEX-MATE: A non-parametric deep learning technique to deproject and deconvolve galaxy cluster X-ray temperature profiles

Temperature profiles of the hot galaxy cluster intracluster medium (ICM) have a complex non-linear structure that traditional parametric modelling may fail to fully approximate. For this study, we made use of neural networks, for the first time, to construct a data-driven non-parametric model of ICM temperature profiles. A new deconvolution algorithm was then introduced to uncover the true (3D) temperature profiles from the observed projected (2D) temperature profiles. An auto-encoder-inspired neural network was first trained by learning a non-linear interpolatory scheme to build the underlying model of 3D temperature profiles in the radial range of [0.02- 2] R500, using a sparse set of hydrodynamical simulations from the THREE HUNDRED PROJECT. A deconvolution algorithm using a learning-based regularisation scheme was then developed. The model was tested using high and low resolution input temperature profiles, such as those expected from simulations and observations, respectively. We find that the proposed deconvolution and deprojection algorithm is robust with respect to the quality of the data, the morphology of the cluster, and the deprojection scheme used. The algorithm can recover unbiased 3D radial temperature profiles with a precision of around 5% over most of the fitting range. We apply the method to the first sample of temperature profiles obtained with XMM-Newton for the CHEX-MATE project and compared it to parametric deprojection and deconvolution techniques. Our work sets the stage for future studies that focus on the deconvolution of the thermal profiles (temperature, density, pressure) of the ICM and the dark matter profiles in galaxy clusters, using deep learning techniques in conjunction with X-ray, Sunyaev Zel'Dovich (SZ) and optical datasets

CHEX-MATE: Constraining the origin of the scatter in galaxy cluster radial X-ray surface brightness profiles

We investigate the statistical properties and the origin of the scatter within the spatially resolved surface brightness profiles of the CHEXâ MATE sample, formed by 118 galaxy clusters selected via the SZ effect. These objects have been drawn from the Planck SZ catalogue and cover a wide range of masses, M500â =â [2â â â 15]à - 1014â Mâ , and redshift, zâ =â [0.05,â 0.6]. We derived the surface brightness and emission measure profiles and determined the statistical properties of the full sample and sub-samples according to their morphology, mass, and redshift. We found that there is a critical scale, Râ â ¼â 0.4R500, within which morphologically relaxed and disturbed object profiles diverge. The median of each sub-sample differs by a factor of â ¼10 at 0.05R500. There are no significant differences between mass- and redshift-selected sub-samples once proper scaling is applied. We compare CHEXâ MATE with a sample of 115 clusters drawn from the THE THREE HUNDRED suite of cosmological simulations. We found that simulated emission measure profiles are systematically steeper than those of observations. For the first time, the simulations were used to break down the components causing the scatter between the profiles. We investigated the behaviour of the scatter due to object-by-object variation. We found that the high scatter, approximately 110%, at R

Planck 2015 results. XXVII. The Second Planck Catalogue of Sunyaev-Zeldovich Sources

We present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest all-sky catalogue of galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data-sets, and is the first SZ-selected cluster survey containing > $10^3$ confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that the Y5R500 estimates are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires. the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical and X-ray data-sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under- luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples

3D scaling laws and projection effects in The300-NIKA2 Sunyaev-Zeldovich Large Program Twin Samples

The abundance of galaxy clusters with mass and redshift is a wellknown cosmological probe. The cluster mass is a key parameter for studies that aim to constrain cosmological parameters using galaxy clusters, making it critical to understand and properly account for the errors in its estimates. Subsequently, it becomes important to correctly calibrate scaling relations between observables like the integrated Compton parameter and the mass of the cluster. The NIKA2 Sunyaev-Zeldovich Large program (LPSZ) enables one to map the intracluster medium profiles in the mm–wavelength band with great details (resolution of 11 & 17″ at 1.2 & 2 mm, respectively) and hence, to estimate the cluster hydrostatic mass more precisely than previous SZ observations. However, there are certain systematic effects which can only be accounted for with the use of simulations. For this purpose, we employ The Three Hundred simulations which have been modelled with a range of physics modules to simulate galaxy clusters. The so-called twin samples are constructed by picking synthetic clusters of galaxies with properties close to the observational targets of the LPSZ. In particular, we use the Compton parameter maps and projected total mass maps of these twin samples along 29 different lines of sight. We investigate the scatter that projection induces on the total masses. Eventually, we consider the statistical values along different lines of sight to construct a kind of 3D scaling law between the integrated Compton parameter, total mass, and overdensity of the galaxy clusters to determine the overdensity that is least impacted by the projection effect