Weak lensing detection of intra-cluster filaments with ground based data

According to the current standard model of Cosmology, matter in the Universe arranges itself along a network of filamentary structure. These filaments connect the main nodes of this so-called 'Cosmic Web', which are clusters of galaxies. Although its large-scale distribution is clearly characterized by numerical simulations, constraining the dark matter content of the cosmic web in reality turns out to be difficult. The natural method of choice is gravitational lensing. However, the direct detection and mapping of the elusive filament signal is challenging and in this work we present two methods,specifically tailored to achieve this task. A linear matched filter aims at the detection of the smooth mass component of filaments and is optimized to perform a shear decomposition that follows the anisotropic component of the lensing signal. Filaments clearly inherit this property due to their morphology. At the same time, the contamination arising from the central massive cluster is controlled in a natural way. The filament 1 {\sigma} detection is of about {\kappa} ~ 0.01-0.005 according to the filter's template width and length, enabling the detection of structures out of reach with other approaches. The second, complementary method seeks to detect the clumpy component of filaments. The detection is determined by the number density of sub-clump identifications in an area enclosing the potential filament, as it was found within the observed field with the filter approach. We test both methods against Mock observations based on realistic N-Body simulations of filamentary structure and prove the feasibility of detecting filaments with ground-based data.Comment: 9 pages, 7 figures. Submitted to A&A. Comments very welcom

Multi-color detection of gravitational arcs

Strong gravitational lensing provides fundamental insights into the understanding of the dark matter distribution in massive galaxies, galaxy clusters and the background cosmology. Despite their importance, the number of gravitational arcs discovered so far is small. The urge for more complete, large samples and unbiased methods of selecting candidates is rising. A number of methods for the automatic detection of arcs have been proposed in the literature, but large amounts of spurious detections retrieved by these methods forces observers to visually inspect thousands of candidates per square degree in order to clean the samples. This approach is largely subjective and requires a huge amount of eye-ball checking, especially considering the actual and upcoming wide field surveys, which will cover thousands of square degrees. In this paper we study the statistical properties of colours of gravitational arcs detected in the 37 deg^2 of the CARS survey. We have found that most of them lie in a relatively small region of the (g'-r',r'-i') colour-colour diagram. To explain this property, we provide a model which includes the lensing optical depth expected in a LCDM cosmology that, in combination with the sources' redshift distribution of a given survey, in our case CARS, peaks for sources at redshift z~1. By further modelling the colours derived from the SED of the galaxies dominating the population at that redshift, the model well reproduces the observed colours. By taking advantage of the colour selection suggested by both data and model, we show that this multi-band filtering returns a sample 83% complete and a contamination reduced by a factor of ~6.5 with respect to the single-band arcfinder sample. New arc candidates are also proposed.Comment: 13 pages, 7 figures, 4 tables; title modified, text extended, figures improved, error estimate improve

Camouflaged galactic CMB foregrounds: total and polarized contributions of the kinetic Sunyaev Zeldovich effect

We consider the role of the galactic kinetic Sunyaev Zeldovich (SZ) effect as a CMB foreground. While the galactic thermal Sunyaev Zeldovich effect has previously been studied and discarded as a potential CMB foreground, we find that the kinetic SZ effect is dominant in the galactic case. We analyse the detectability of the kinetic SZ effect by means of an optimally matched filter technique applied to a simulation of an ideal observation. We obtain no detection, getting a S/N ratio of 0.1, thereby demonstrating that the kinetic SZ effect can also safely be ignored as a CMB foreground. However we provide maps of the expected signal for inclusion in future high precision data processing. Furthermore, we rule out the significant contamination of the polarised CMB signal by second scattering of galactic kinetic Sunyaev-Zeldovich photons, since we show that the scattering of the CMB quadrupole photons by galactic electrons is a stronger effect than the Sunyaev Zeldovich second scattering, and has already been shown to produce no significant polarised contamination. We confirm the latter assessment also by means of an optimally matched filter.Comment: 9 pages, 6 figures, 2 tables. submitte

AMICO: optimised detection of galaxy clusters in photometric surveys

We present AMICO (Adaptive Matched Identifier of Clustered Objects), a new algorithm for the detection of galaxy clusters in photometric surveys. AMICO is based on the Optimal Filtering technique, which allows to maximise the signal-to-noise ratio of the clusters. In this work we focus on the new iterative approach to the extraction of cluster candidates from the map produced by the filter. In particular, we provide a definition of membership probability for the galaxies close to any cluster candidate, which allows us to remove its imprint from the map, allowing the detection of smaller structures. As demonstrated in our tests, this method allows the deblending of close-by and aligned structures in more than $50\%$ of the cases for objects at radial distance equal to $0.5 \times R_{200}$ or redshift distance equal to $2 \times \sigma_z$, being $\sigma_z$ the typical uncertainty of photometric redshifts. Running AMICO on mocks derived from N-body simulations and semi-analytical modelling of the galaxy evolution, we obtain a consistent mass-amplitude relation through the redshift range $0.3 < z < 1$, with a logarithmic slope $\sim 0.55$ and a logarithmic scatter $\sim 0.14$. The fraction of false detections is steeply decreasing with S/N, and negligible at S/N > 5.Comment: 18 pages, accepted for publication in MNRA

AMICO galaxy clusters in KiDS-DR3: sample properties and selection function

We present the first catalogue of galaxy cluster candidates derived from the third data release of the Kilo Degree Survey (KiDS-DR3). The sample of clusters has been produced using the Adaptive Matched Identifier of Clustered Objects (AMICO) algorithm. In this analysis AMICO takes advantage of the luminosity and spatial distribution of galaxies only, not considering colours. In this way, we prevent any selection effect related to the presence or absence of the red-sequence in the clusters. The catalogue contains 7988 candidate galaxy clusters in the redshift range 0.13.5 with a purity approaching 95% over the entire redshift range. In addition to the catalogue of galaxy clusters we also provide a catalogue of galaxies with their probabilistic association to galaxy clusters. We quantify the sample purity, completeness and the uncertainties of the detection properties, such as richness, redshift, and position, by means of mock galaxy catalogues derived directly from the data. This preserves their statistical properties including photo-z uncertainties, unknown absorption across the survey, missing data, spatial correlation of galaxies and galaxy clusters. Being based on the real data, such mock catalogues do not have to rely on the assumptions on which numerical simulations and semi-analytic models are based on. This paper is the first of a series of papers in which we discuss the details and physical properties of the sample presented in this work.Comment: 16 pages, 14 figures, 3 tables, submitted to MNRA