RXCJ1111.6+4050 galaxy cluster: the observational evidence of a transitional fossil group

We present a detailed kinematical and dynamical study of the galaxy cluster RXCJ1111.6+4050 (RXCJ1111), at z = 0.0756 using 104 new spectroscopic redshifts of galaxies observed at the TNG 3.5m telescope and SDSS DR16 public archive. Our analysis is performed in a multiwavelength context in order to study and compare mainly optical and X-ray properties using XMM-Newton data. We find that RXCJ1111 is a galaxy cluster showing a velocity distribution with clear deviations from Gaussianity, that we are able to explain by the presence of a substructure within the cluster. The two cluster components show velocity dispersions of $644 \pm 56$ km/s and $410 \pm 123$ km/s, which yield dynamical masses of M$_{200}$=$1.9 \pm 0.4 \times10^{14}$ M$_{\odot}$ and $0.6 \pm 0.4 \times 10^{14}$ M$_{\odot}$ for the main system and substructure, respectively. RXCJ1111 presents an elongation in the North-South direction and a gradient of 250-350 km/s/Mpc in the velocity field, suggest that the merger axis between the main system and substructure is slightly tilted with respect to the line-of-sight. The substructure is characterized by a magnitude gap $\Delta m_{12} \ge 1.8$, so it fits the "fossil-like" definition of a galaxy group. Mass estimates derived from X-ray and optical are in good agreement when two galaxy components are considered separately. We propose a 3D merging model and find that the fossil group is in an early phase of collision with the RXCJ1111 main cluster and almost aligned with the line-of-sight. This merging model would explain the slight increase found in the T$_X$ with respect to what we would expect for relaxed clusters. Due to the presence of several brightest galaxies, after this collision, the substructure would presumably lose its fossil condition. Therefore, RXCJ1111 represents the observational evidence that the fossil stage of a system can be temporary and transitional.Comment: 16 pages, 11 figures, 3 tables and 1 appendi

Biases in galaxy cluster velocity dispersion and mass estimates in the small number of galaxies regime

We present a study of the statistical properties of three velocity dispersion and mass estimators, namely biweight, gapper and standard deviation, in the small number of galaxies regime ($N_{\rm gal} \le 75$). Using a set of 73 numerically simulated galaxy clusters, we characterise the statistical bias and the variance for the three estimators, both in the determination of the velocity dispersion and the dynamical mass of the clusters via the $\sigma-M$ relation. The results are used to define a new set of unbiased estimators, that are able to correct for those statistical biases with a minimal increase of the associated variance. The numerical simulations are also used to characterise the impact of velocity segregation in the selection of cluster members, and the impact of using cluster members within different physical radii from the cluster centre. The standard deviation is found to be the lowest variance estimator. The selection of galaxies within the sub-sample of the most massive galaxies in the cluster introduces a $2\,$\% bias in the velocity dispersion estimate when calculated using a quarter of the most massive cluster members. We also find a dependence of the velocity dispersion estimate on the aperture radius as a fraction of $R_{200}$, consistent with previous results. The proposed set of unbiased estimators effectively provides a correction of the velocity dispersion and mass estimates from all those effects in the small number of cluster members regime. This is tested by applying the new estimators to a subset of simulated observations. Although for a single galaxy cluster the statistical and physical effects discussed here are comparable or slightly smaller than the bias introduced by interlopers, they will be of relevance when dealing with ensemble properties and scaling relations for large cluster samples (Abridged).Comment: accepted for publication in A&

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 three hundred project. A machine learning method to infer clusters of galaxy mass radial profiles from mock Sunyaev–Zel’dovich maps

We develop a machine learning algorithm to infer the three-dimensional cumulative radial profiles of total and gas masses in galaxy clusters from thermal Sunyaev–Zel’dovich effect maps. We generate around 73 000 mock images along various lines of sight using 2522 simulated clusters from THE THREE HUNDRED project at redshift z < 0.12 and train a model that combines an auto-encoder 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 the Sunyaev–Zel’dovich effect. We show that the recovered profiles are unbiased with a scatter of about 10 per cent, slightly increasing towards the core and the outskirts of the cluster. We selected clusters in the mass range of 1013.5 ≤ M200/(h−1 M) ≤ 1015.5, spanning different dynamical states, from relaxed to disturbed haloes. We verify that both the accuracy and precision of this method show a slight dependence on the dynamical state, but not on the cluster mass. To further verify the consistency of our model, we fit the inferred total mass profiles with a Navarro–Frenk–White model and contrast the concentration values with those of the true profiles. We note that the inferred profiles are unbiased for higher concentration values, reproducing a trustworthy mass–concentration relation. The comparison with a widely used mass estimation technique, such as hydrostatic equilibrium, demonstrates that our method recovers the total mass that is not biased by non-thermal motions of the gas

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

The Three Hundred Project: the gizmo-simba run

We introduce gizmo-simba, a new suite of galaxy cluster simulations within The Three Hundred project. The Three Hundred consists of zoom re-simulations of 324 clusters with M 200≳ 1014.8, M ⊙ drawn from the MultiDark-Planck N-body simulation, run using several hydrodynamic and semi-analytical codes. The gizmo-simba suite adds a state-of-the-art galaxy formation model based on the highly successful Simba simulation, mildly re-calibrated to match z = 0 cluster stellar properties. Comparing to The Three Hundred zooms run with gadget-x, we find intrinsic differences in the evolution of the stellar and gas mass fractions, BCG ages, and galaxy colour-magnitude diagrams, with gizmo-simba generally providing a good match to available data at z ≈ 0. gizmo-simba's unique black hole growth and feedback model yields agreement with the observed BH scaling relations at the intermediate-mass range and predicts a slightly different slope at high masses where few observations currently lie. Gizmo-Simba provides a new and novel platform to elucidate the co-evolution of galaxies, gas, and black holes within the densest cosmic environments

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&

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