METAPHOR: Probability density estimation for machine learning based photometric redshifts

We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z's and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF's derived from a traditional SED template fitting method (Le Phare).Comment: proceedings of the International Astronomical Union, IAU-325 symposium, Cambridge University pres

Oxygen- and carbon-rich variable red giant populations in the Magellanic Clouds from EROS, OGLE, MACHO, and 2MASS photometry

The carbon-to-oxygen (C/O) ratio of asymptotic giant branch (AGB) stars constitutes an important index of evolutionary and environment/metallicity factor. We develop a method for mass C/O classification of AGBs in photometric surveys without using periods. For this purpose we rely on the slopes in the tracks of individual stars in the colour-magnitude diagram. We demonstrate that our method enables the separation of C-rich and O-rich AGB stars with little confusion. For the Magellanic Clouds we demonstrate that this method works for several photometric surveys and filter combinations. As we rely on no period identification, our results are relatively insensitive to the phase coverage, aliasing, and time-sampling problems that plague period analyses. For a subsample of our stars, we verify our C/O classification against published C/O catalogues. With our method we are able to produce C/O maps of the entire Magellanic Clouds. Our purely photometric method for classification of C- and O-rich AGBs constitutes a method of choice for large, near-infrared photometric surveys. Because our method depends on the slope of colour-magnitude variation but not on magnitude zero point, it remains applicable to objects with unknown distances.Comment: 14 pages, 16 figures, 1 table, accepted for publication in Astronomy & Astrophysic

Extracting Hα\alpha flux from photometric data in the J-PLUS survey

We present the main steps that will be taken to extract H$\alpha$ emission flux from Javalambre Photometric Local Universe Survey (J-PLUS) photometric data. For galaxies with $z\lesssim0.015$, the H$\alpha$+[NII] emission is covered by the J-PLUS narrow-band filter $F660$. We explore three different methods to extract the H$\alpha$ + [NII] flux from J-PLUS photometric data: a combination of a broad-band and a narrow-band filter ($r'$ and $F660$), two broad-band and a narrow-band one ($r'$, $i'$ and $F660$), and a SED-fitting based method using 8 photometric points. To test these methodologies, we simulated J-PLUS data from a sample of 7511 SDSS spectra with measured H$\alpha$ flux. Based on the same sample, we derive two empirical relations to correct the derived H$\alpha$+[NII] flux from dust extinction and [NII] contamination. We find that the only unbiased method is the SED fitting based one. The combination of two filters underestimates the measurements of the H$\alpha$ + [NII] flux by a 28%, while the three filters method by a 9%. We study the error budget of the SED-fitting based method and find that, in addition to the photometric error, our measurements have a systematic uncertainty of a 4.3%. Several sources contribute to this uncertainty: differences between our measurement procedure and the one used to derive the spectroscopic values, the use of simple stellar populations as templates, and the intrinsic errors of the spectra, which were not taken into account. Apart from that, the empirical corrections for dust extinction and [NII] contamination add an extra uncertainty of 14%. Given the J-PLUS photometric system, the best methodology to extract H$\alpha$ + [NII] flux is the SED-fitting based one. Using this method, we are able to recover reliable H$\alpha$ fluxes for thousands of nearby galaxies in a robust and homogeneous way.Comment: 11 pages, 14 figures. Minor changes to match the published versio

Photometric Redshifts of Submillimeter Galaxies

We use the photometric redshift method of Chakrabarti & McKee (2008) to infer photometric redshifts of submillimeter galaxies with far-IR (FIR) $\it{Herschel}$ data obtained as part of the PACS Evolutionary Probe (PEP) program. For the sample with spectroscopic redshifts, we demonstrate the validity of this method over a large range of redshifts ( 4 \ga z \ga 0.3) and luminosities, finding an average accuracy in $(1+z_{\rm phot})/(1+z_{\rm spec})$ of 10%. Thus, this method is more accurate than other FIR photometric redshift methods. This method is different from typical FIR photometric methods in deriving redshifts from the light-to-gas mass ($L/M$) ratio of infrared-bright galaxies inferred from the FIR spectral energy distribution (SED), rather than dust temperatures. Once the redshift is derived, we can determine physical properties of infrared bright galaxies, including the temperature variation within the dust envelope, luminosity, mass, and surface density. We use data from the GOODS-S field to calculate the star formation rate density (SFRD) of sub-mm bright sources detected by AzTEC and PACS. The AzTEC-PACS sources, which have a threshold 850 \micron flux \ga 5 \rm mJy, contribute 15% of the SFRD from all ULIRGs (L_{\rm IR} \ga 10^{12} L_{\odot}), and 3% of the total SFRD at $z \sim 2$.Comment: 7 pages, 2 figures, submitted to Ap

Towards a photometric metallicity scale for open clusters

Open clusters are a useful tool when investigating several topics connected with stellar evolution; for example the age or distance can be more accurately determined than for field stars. However, one important parameter, the metallicity, is only known for a marginal percentage of open clusters. We aim at a consistent set of parameters for the open clusters investigated in our photometric Delta-a survey of chemically peculiar stars. Special attention is paid to expanding our knowledge of cluster metallicities and verifying their scale. Making use of a previously developed method based on normalised evolutionary grids and photometric data, the distance, age, reddening, and metallicity of open clusters were derived. To transform photometric measurements into effective temperatures to use as input for our method, a set of temperature calibrations for the most commonly used colour indices and photometric systems was compiled. We analysed 58 open clusters in total. Our derived metallicity values were in excellent agreement with about 30 spectroscopically studied targets. The mean value of the absolute deviations was found to be 0.03 dex, with no noticeable offset or gradient. The method was also applied using recent evolutionary models based on the currently accepted lower solar abundance value Z=0.014. No significant differences were found compared to grids using the former adopted solar value Z=0.02. Furthermore, some divergent photometric datasets were identified and discussed. The method provides an accurate way of obtaining properly scaled metallicity values for open clusters. In light of present and future homogeneous photometric sky surveys, the sample of stellar clusters can be extended to the outskirts of the Milky Way, where spectroscopic studies are almost impossible. This will help for determining galactic metallicity gradients in more detail.Comment: Accepted for publication in A&A (19 pages including online material

Recovering the real-space correlation function from photometric redshift surveys

Measurements of clustering in large-scale imaging surveys that make use of photometric redshifts depend on the uncertainties in the redshift determination. We have used light-cone simulations to show how the deprojection method successfully recovers the real space correlation function when applied to mock photometric redshift surveys. We study how the errors in the redshift determination affect the quality of the recovered two-point correlation function. Considering the expected errors associated to the planned photometric redshift surveys, we conclude that this method provides information on the clustering of matter useful for the estimation of cosmological parameters that depend on the large scale distribution of galaxies.Comment: 11 pages, 8 figures. Accepted for publication in MNRA

Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies

Despite the high accuracy of photometric redshifts (zphot) derived using Machine Learning (ML) methods, the quantification of errors through reliable and accurate Probability Density Functions (PDFs) is still an open problem. First, because it is difficult to accurately assess the contribution from different sources of errors, namely internal to the method itself and from the photometric features defining the available parameter space. Second, because the problem of defining a robust statistical method, always able to quantify and qualify the PDF estimation validity, is still an open issue. We present a comparison among PDFs obtained using three different methods on the same data set: two ML techniques, METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts) and ANNz2, plus the spectral energy distribution template fitting method, BPZ. The photometric data were extracted from the KiDS (Kilo Degree Survey) ESO Data Release 3, while the spectroscopy was obtained from the GAMA (Galaxy and Mass Assembly) Data Release 2. The statistical evaluation of both individual and stacked PDFs was done through quantitative and qualitative estimators, including a dummy PDF, useful to verify whether different statistical estimators can correctly assess PDF quality. We conclude that, in order to quantify the reliability and accuracy of any zphot PDF method, a combined set of statistical estimators is required.Comment: Accepted for publication by MNRAS, 20 pages, 14 figure