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Register a new userPhotometric redshifts from evolutionary synthesis with PEGASE: the code ZPEG and the z=0 age constraint
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Photometric redshifts are estimated on the basis of template scenarios with the help of the code ZPEG, an extension of the galaxy evolution model PEGASE.2 and available on the PEGASE web site. The spectral energy distribution (SED) templates are computed for nine spectral types including starburst, irregular, spiral and elliptical. Dust, extinction and metal effects are coherently taken into account, depending on evolution scenarios. The sensitivity of results to adding near-infrared colors and IGM absorption is analyzed. A comparison with results of other models without evolution measures the evolution factor which systematically increases the estimated photometric redshift values by $Delta z$ > 0.2 for z > 1.5. Moreover we systematically check that the evolution scenarios match observational standard templates of nearby galaxies, implying an age constraint of the stellar population at z=0 for each type. The respect of this constraint makes it possible to significantly improve the accuracy of photometric redshifts by decreasing the well-known degeneracy problem. The method is applied to the HDF-N sample. From fits on SED templates by a $chi^2$-minimization procedure, not only is the photometric redshift derived but also the corresponding spectral type and the formation redshift $z_for$ when stars first formed. Early epochs of galaxy formation z > 5 are found from this new method and results are compared to faint galaxy count interpretations. The new tool is available at: http://www.iap.fr/pegase
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We present PEGASE-HR, a new stellar population synthesis program generating high resolution spectra (R=10 000) over the optical range lambda=400--680 nm. It links the spectro-photometric model of galaxy evolution PEGASE.2 (Fioc & Rocca-Volmerange 1997) to an updated version of the ELODIE library of stellar spectra observed with the 193 cm telescope at the Observatoire de Haute-Provence (Prugniel & Soubiran 2001a). The ELODIE star set gives a fairly complete coverage of the Hertzprung-Russell (HR) diagram and makes it possible to synthesize populations in the range [Fe/H]=-2 to +0.4. This code is an exceptional tool for exploring signatures of metallicity, age, and kinematics. We focus on a detailed study of the sensitivity to age and metallicity of the high-resolution stellar absorption lines and of the classical metallic indices proposed until now to solve the age-metallicity degeneracy. Validity tests on several stellar lines are performed by comparing our predictions for Lick indices to the models of other groups. The comparison with the lower resolution library BaSeL (Lejeune et al. 1997) confirms the quality of the ELODIE library when used for simple stellar populations (SSPs) from 10 Myr to 20 Gyr. Predictions for the evolved populations of globular clusters and elliptical galaxies are given and compared to observational data. Two new high-resolution indices are proposed around the Hgamma line. They should prove useful in the analysis of spectra from the new generation of telescopes and spectrographs.
We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of photometric redshifts when galaxy size, ellipticity, S{e}rsic index and surface brightness are included in training on galaxy samples from the SDSS and the CFHT Stripe-82 Survey (CS82). We show that by adding galaxy morphological parameters to full $ugriz$ photometry, only mild improvements are obtained, while the gains are substantial in cases where fewer passbands are available. For instance, the combination of $grz$ photometry and morphological parameters almost fully recovers the metrics of $5$-band photometric redshifts. We demonstrate that with morphology it is possible to determine useful redshift distribution $N(z)$ of galaxy samples without any colour information. We also find that the inclusion of quasar redshifts and associated object sizes in training improves the quality of photometric redshift catalogues, compensating for the lack of a good star-galaxy separator. We further show that morphological information can mitigate biases and scatter due to bad photometry. As an application, we derive both point estimates and posterior distributions of redshifts for the official CS82 catalogue, training on morphology and SDSS Stripe-82 $ugriz$ bands when available. Our redshifts yield a 68th percentile error of $0.058(1+z)$, and a catastrophic outlier fraction of $5.2$ per cent. We further include a deep extension trained on morphology and single $i$-band CS82 photometry.
We present a galaxy group-finding algorithm, the Photo-z Probability Peaks (P3) algorithm, optimized for locating small galaxy groups using photometric redshift data by searching for peaks in the signal-to-noise of the local overdensity of galaxies in a three-dimensional grid. This method is an improvement over similar two-dimensional matched-filter methods in reducing background contamination through the use of redshift information, allowing it to accurately detect groups at lower richness. We present the results of tests of our algorithm on galaxy catalogues from the Millennium Simulation. Using a minimum S/N of 3 for detected groups, a group aperture size of 0.25 Mpc/h, and assuming photometric redshift accuracy of sigma_z = 0.05 it attains a purity of 84% and detects ~295 groups/deg.^2 with an average group richness of 8.6 members. Assuming photometric redshift accuracy of sigma_z = 0.02, it attains a purity of 97% and detects ~143 groups/deg.^2 with an average group richness of 12.5 members. We also test our algorithm on data available for the COSMOS field and the presently-available fields from the CFHTLS-Wide survey, presenting preliminary results of this analysis.
Pegase.3 is a Fortran 95 code modeling the spectral evolution of galaxies from the far-ultraviolet to submillimeter wavelengths. It also follows the chemical evolution of their stars, gas and dust. For a given scenario (a set of parameters defining the history of mass assembly, the star formation law, the initial mass function...), Pegase.3 consistently computes the following: * the star formation, infall, outflow and supernova rates from 0 to 20 Gyr; * the stellar metallicity, the abundances of main elements in the gas and the composition of dust; * the unattenuated stellar spectral energy distribution (SED); * the nebular SED, using nebular continua and emission lines precomputed with code Cloudy (Ferland et al. 2017); * the attenuation in star-forming clouds and the diffuse interstellar medium, by absorption and scattering on dust grains, of the stellar and nebular SEDs. For this, the code uses grids of the transmittance for spiral and spheroidal galaxies. We precomputed these grids through Monte Carlo simulations of radiative transfer based on the method of virtual interactions; * the re-emission by grains of the light they absorbed, taking into account stochastic heating. The main innovation compared to Pegase.2 is the modeling of dust emission and its evolution. The computation of nebular emission has also been entirely upgraded to take into account metallicity effects and infrared lines. Other major differences are that complex scenarios of evolution (derived for instance from cosmological simulations), with several episodes of star formation, infall or outflow, may now be implemented, and that the detailed evolution of the most important elements -- not only the overall metallicity -- is followed.
We apply clustering-based redshift inference to all extended sources from the Sloan Digital Sky Survey photometric catalogue, down to magnitude r = 22. We map the relationships between colours and redshift, without assumption of the sources spectral energy distributions (SED). We identify and locate star-forming, quiescent galaxies, and AGN, as well as colour changes due to spectral features, such as the 4000 AA{} break, redshifting through specific filters. Our mapping is globally in good agreement with colour-redshift tracks computed with SED templates, but reveals informative differences, such as the need for a lower fraction of M-type stars in certain templates. We compare our clustering-redshift estimates to photometric redshifts and find these two independent estimators to be in good agreement at each limiting magnitude considered. Finally, we present the global clustering-redshift distribution of all Sloan extended sources, showing objects up to z ~ 0.8. While the overall shape agrees with that inferred from photometric redshifts, the clustering redshift technique results in a smoother distribution, with no indication of structure in redshift space suggested by the photometric redshift estimates (likely artifacts imprinted by their spectroscopic training set). We also infer a higher fraction of high redshift objects. The mapping between the four observed colours and redshift can be used to estimate the redshift probability distribution function of individual galaxies. This work is an initial step towards producing a general mapping between redshift and all available observables in the photometric space, including brightness, size, concentration, and ellipticity.
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