Photometric redshifts with Quasi Newton Algorithm (MLPQNA). Results in the PHAT1 contest

Context. Since the advent of modern multiband digital sky surveys, photometric redshifts (photo-z's) have become relevant if not crucial to many fields of observational cosmology, from the characterization of cosmic structures, to weak and strong lensing. Aims. We describe an application to an astrophysical context, namely the evaluation of photometric redshifts, of MLPQNA, a machine learning method based on Quasi Newton Algorithm. Methods. Theoretical methods for photo-z's evaluation are based on the interpolation of a priori knowledge (spectroscopic redshifts or SED templates) and represent an ideal comparison ground for neural networks based methods. The MultiLayer Perceptron with Quasi Newton learning rule (MLPQNA) described here is a computing effective implementation of Neural Networks for the first time exploited to solve regression problems in the astrophysical context and is offered to the community through the DAMEWARE (DAta Mining & ExplorationWeb Application REsource) infrastructure. Results. The PHAT contest (Hildebrandt et al. 2010) provides a standard dataset to test old and new methods for photometric redshift evaluation and with a set of statistical indicators which allow a straightforward comparison among different methods. The MLPQNA model has been applied on the whole PHAT1 dataset of 1984 objects after an optimization of the model performed by using as training set the 515 available spectroscopic redshifts. When applied to the PHAT1 dataset, MLPQNA obtains the best bias accuracy (0.0006) and very competitive accuracies in terms of scatter (0.056) and outlier percentage (16.3%), scoring as the second most effective empirical method among those which have so far participated to the contest. MLPQNA shows better generalization capabilities than most other empirical methods especially in presence of underpopulated regions of the Knowledge Base.Comment: Accepted for publication in Astronomy & Astrophysics; 9 pages, 2 figure

C3C^{3} : A Command-line Catalogue Cross-matching tool for modern astrophysical survey data

In the current data-driven science era, it is needed that data analysis techniques has to quickly evolve to face with data whose dimensions has increased up to the Petabyte scale. In particular, being modern astrophysics based on multi-wavelength data organized into large catalogues, it is crucial that the astronomical catalog cross-matching methods, strongly dependant from the catalogues size, must ensure efficiency, reliability and scalability. Furthermore, multi-band data are archived and reduced in different ways, so that the resulting catalogues may differ each other in formats, resolution, data structure, etc, thus requiring the highest generality of cross-matching features. We present $C^{3}$ (Command-line Catalogue Cross-match), a multi-platform application designed to efficiently cross-match massive catalogues from modern surveys. Conceived as a stand-alone command-line process or a module within generic data reduction/analysis pipeline, it provides the maximum flexibility, in terms of portability, configuration, coordinates and cross-matching types, ensuring high performance capabilities by using a multi-core parallel processing paradigm and a sky partitioning algorithm.Comment: 6 pages, 4 figures, proceedings of the IAU-325 symposium on Astroinformatics, Cambridge University pres

CLASH-VLT: Is there a dependence in metallicity evolution on galaxy structures?

We investigate the environmental dependence of the mass-metallicty (MZ) relation and it's connection to galaxy stellar structures and morphologies. In our studies, we analyze galaxies in massive clusters at z~0.4 from the CLASH (HST) and CLASH-VLT surveys and measure their gas metallicities, star-formation rates, stellar structures and morphologies. We establish the MZ relation for 90 cluster and 40 field galaxies finding a shift of ~-0.3 dex in comparison to the local trends seen in SDSS for the majority of galaxies with logM<10.5. We do not find significant differences of the distribution of 4 distinct morphological types that we introduce by our classification scheme (smooth, disc-like, peculiar, compact). Some variations between cluster and field galaxies in the MZ relation are visible at the high mass end. However, obvious trends for cluster specific interactions (enhancements or quenching of SFRs) are missing. In particular, galaxies with peculiar stellar structures that hold signs for galaxy interactions, are distributed in a similar way as disc-like galaxies - in SFRs, masses and O/H abundances. We further show that our sample falls around an extrapolation of the star-forming main sequence (the SFR-M* relation) at this redshift, indicating that emission-line selected samples do not have preferentially high star-formation rates (SFRs). However, we find that half of the high mass cluster members (M*>10^10Msun) lie below the main sequence which corresponds to the higher mass objects that reach solar abundances in the MZ diagram.Comment: Proceedings of IAU Symposium 309, Vienna, ed. B.L. Ziegler, F. Combes, H. Dannerbauer, M. Verdug

Machine learning based data mining for Milky Way filamentary structures reconstruction

We present an innovative method called FilExSeC (Filaments Extraction, Selection and Classification), a data mining tool developed to investigate the possibility to refine and optimize the shape reconstruction of filamentary structures detected with a consolidated method based on the flux derivative analysis, through the column-density maps computed from Herschel infrared Galactic Plane Survey (Hi-GAL) observations of the Galactic plane. The present methodology is based on a feature extraction module followed by a machine learning model (Random Forest) dedicated to select features and to classify the pixels of the input images. From tests on both simulations and real observations the method appears reliable and robust with respect to the variability of shape and distribution of filaments. In the cases of highly defined filament structures, the presented method is able to bridge the gaps among the detected fragments, thus improving their shape reconstruction. From a preliminary "a posteriori" analysis of derived filament physical parameters, the method appears potentially able to add a sufficient contribution to complete and refine the filament reconstruction.Comment: Proceeding of WIRN 2015 Conference, May 20-22, Vietri sul Mare, Salerno, Italy. Published in Smart Innovation, Systems and Technology, Springer, ISSN 2190-3018, 9 pages, 4 figure

Command-line Cross-matching Tool for Modern Astrophysical Pipelines

The emerging need for efficient, reliable and scalable astronomical catalog cross-matching is becoming more pressing in the current data-driven science era, where the size of data has rapidly increased up to the Petabyte scale. C3 (Command-line Catalogue Cross-matching) is a multi-platform tool designed to efficiently cross-match massive catalogues from modern astronomical surveys, ensuring high-performance capabilities through the use of a multi-core parallel processing paradigm. The tool has been conceived to be executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline, providing the maximum flexibility to the end user, in terms of parameter configuration, coordinates and cross-matching types. In this work we present the architecture and the features of the tool. Moreover, since the modular design of the tool enables an easy customization to specific use cases and requirements, we present also an example of a customized C3 version designed and used in the FP7 project ViaLactea, dedicated to cross-correlate Hi-GAL clumps with multi-band compact sources...

A Command-line Cross-matching tool for modern astrophysical pipelines

The emerging need for efficient, reliable and scalable astronomical catalog cross-matching is becoming more pressing in the current data-driven science era, where the size of data has rapidly increased up to the Petabyte scale. C3 (Command-line Catalogue Cross-matching) is a multi-platform tool designed to efficiently cross-match massive catalogues from modern astronomical surveys, ensuring high-performance capabilities through the use of a multi-core parallel processing paradigm. The tool has been conceived to be executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline, providing the maximum flexibility to the end user, in terms of parameter configuration, coordinates and cross-matching types. In this work we present the architecture and the features of the tool. Moreover, since the modular design of the tool enables an easy customization to specific use cases and requirements, we present also an example of a customized C3 version designed and used in the FP7 project ViaLactea, dedicated to cross-correlate Hi-GAL clumps with multi-band compact sources...

Shapley Supercluster Survey: mapping the dark matter distribution

We present a 23deg$^2$ weak gravitational lensing survey of the Shapley supercluster core and its surroundings using $gri$ VST images as part of the Shapley Supercluster Survey (ShaSS). This study reveals the overall matter distribution over a region containing 11 clusters at $z{\sim}0.048$ that are all interconnected, as well as several ongoing cluster-cluster interactions. Galaxy shapes have been measured by using the Kaiser-Squires-Broadhurst method for the $g$- and $r$-band images and background galaxies were selected via the $gri$ colour-colour diagram. This technique has allowed us to detect all of the clusters, either in the $g$-band or $r$-band images, although at different $\sigma$ levels, indicating that the underlying dark matter distribution is tightly correlated with the number density of the member galaxies. The deeper $r$-band images have traced the five interacting clusters in the supercluster core as a single coherent structure, confirmed the presence of a filament extending North from the core, and have revealed a background cluster at $z{\sim}0.17$. We have measured the masses of the four richest clusters (A3556, A3558, A3560 and A3562) in the two-dimensional shear pattern, assuming a spherical Navarro-Frenk-White (NFW) profile and obtaining a total mass of $\mathcal{M}_{\rm ShaSS,WL}{=}1.56^{+0.81}_{-0.55}{\times}10^{15\,}{\rm M}_{\odot}$, which is consistent with dynamical and X-ray studies. Our analysis provides further evidence of the ongoing dynamical evolution in the ShaSS region.Comment: 16 pages, 11 figures, 4 tables. Accepted for publication in MNRA

Systematic search for lensed X-ray sources in the CLASH fields

We search for unresolved X-ray emission from lensed sources in the FOV of 11 CLASH clusters with Chandra data. We consider the solid angle in the lens plane corresponding to a magnification $\mu>1.5$, that amounts to a total of ~100 arcmin$^2$. Our main goal is to assess the efficiency of massive clusters as cosmic telescopes to explore the faint end of X-ray extragalactic source population. We search for X-ray emission from strongly lensed sources identified in the optical, and perform an untargeted detection of lensed X-ray sources. We detect X-ray emission only in 9 out of 849 lensed/background optical sources. The stacked emission of the sources without detection does not reveal any signal in any band. Based on the untargeted detection, we find 66 additional X-ray sources that are consistent with being lensed sources. After accounting for completeness and sky coverage, we measure for the first time the soft- and hard-band number counts of lensed X-ray sources. The results are consistent with current modelization of the AGN population distribution. The distribution of de-lensed fluxes of the sources identified in moderately deep CLASH fields reaches a flux limit of ~$10^{-16}$ and ~$10^{-15}$ erg/s/cm$^{2}$ in the soft and hard bands, respectively. We conclude that, in order to match the depth of the CDFS exploiting massive clusters as cosmic telescopes, the required number of cluster fields is about two orders of magnitude larger than that offered by the 20 years Chandra archive. A significant step forward will be made when future X-ray facilities, with ~1' angular resolution and large effective area, will allow the serendipitous discovery of rare, strongly lensed high-$z$ X-ray sources, enabling the study of faint AGN activity in early Universe and the measurement of gravitational time delays in the X-ray variability of multiply imaged AGN.Comment: Accepted for publication in A&

The Grism Lens-Amplified Survey from Space (GLASS) X. Sub-kpc resolution gas-phase metallicity maps at cosmic noon behind the Hubble Frontier Fields cluster MACS1149.6+2223

(Abridged) We combine deep HST grism spectroscopy with a new Bayesian method to derive maps of gas-phase metallicity, nebular dust extinction, and star-formation rate for 10 star-forming galaxies at high redshift ($1.2<z<2.3$). Exploiting lensing magnification by the foreground cluster MACS1149.6+2223, we reach sub-kpc spatial resolution and push the stellar mass limit associated with such high-z spatially resolved measurements below $10^8M_\odot$ for the first time. Our maps exhibit diverse morphologies, indicative of various effects such as efficient radial mixing from tidal torques, rapid accretion of low-metallicity gas, etc., which can affect the gas and metallicity distributions in individual galaxies. Based upon an exhaustive sample of all existing sub-kpc metallicity gradients at high-z, we find that predictions given by analytical chemical evolution models assuming a relatively extended star-formation profile in the early disk formation phase can explain the majority of observed gradients, without involving galactic feedback or radial outflows. We observe a tentative correlation between stellar mass and metallicity gradient, consistent with the downsizing galaxy formation picture that more massive galaxies are more evolved into a later phase of disk growth, where they experience more coherent mass assembly at all radii and thus show shallower metallicity gradients. In addition, we compile a sample of homogeneously cross-calibrated integrated metallicity measurements spanning three orders of magnitude in stellar mass at $z\sim1.8$. We use this sample to study the mass-metallicity relation (MZR) and test the fundamental metallicity relation (FMR). The slope of the observed MZR can rule out the momentum-driven wind model at 3-$\sigma$ confidence level. We find no significant offset with respect to the FMR, taking into account the intrinsic scatter and measurement uncertainties.Comment: 26 pages, 14 figures, and 6 table