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Register a new userT-PHOT: A new code for PSF-matched, prior-based, multiwavelength extragalactic deconfusion photometry
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We present T-PHOT, a publicly available software aimed at extracting accurate photometry from low-resolution images of deep extragalactic fields, where the blending of sources can be a serious problem for the accurate and unbiased measurement of fluxes and colours. T-PHOT has been developed within the ASTRODEEP project and it can be considered as the next generation to TFIT, providing significant improvements above it and other similar codes. T-PHOT gathers data from a high-resolution image of a region of the sky, and uses it to obtain priors for the photometric analysis of a lower resolution image of the same field. It can handle different types of datasets as input priors: i) a list of objects that will be used to obtain cutouts from the real high-resolution image; ii) a set of analytical models; iii) a list of unresolved, point-like sources, useful e.g. for far-infrared wavelength domains. We show that T-PHOT yields accurate estimations of fluxes within the intrinsic uncertainties of the method, when systematic errors are taken into account (which can be done thanks to a flagging code given in the output). T-PHOT is many times faster than similar codes like TFIT and CONVPHOT (up to hundreds, depending on the problem and the method adopted), whilst at the same time being more robust and more versatile. This makes it an optimal choice for the analysis of large datasets. In addition we show how the use of different settings and methods significantly enhances the performance. Given its versatility and robustness, T-PHOT can be considered the preferred choice for combined photometric analysis of current and forthcoming extragalactic optical to far-infrared imaging surveys. [abridged]
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We present A-PHOT, a new publicly available code for performing aperture photometry on astronomical images, that is particularly well suited for multi-band extragalactic surveys. A-PHOT estimates the fluxes emitted by astronomical objects within a chosen set of circular or elliptical apertures. Unlike other widely used codes, it runs on predefined lists of positions, allowing for repeated measurements on the same list of objects on different images. This can be very useful when forced photometric measurement on a given position is needed. A-PHOT can also estimate morphological parameters and a local background flux, and compute on-the-fly individual optimized elliptical apertures, in which the signal-to-noise ratio is maximized. We check the performance of A-PHOT on both synthetic and real test datasets: we explore a simulated case of a space-based high-resolution imaging dataset, investigating the input parameter space to optimize the accuracy of the performance, and we exploit the CANDELS GOODS-South data to compare the A-PHOT measurements with those from the survey legacy catalogs, finding good agreement overall. A-PHOT proves to a useful and versatile tool for quickly extracting robust and accurate photometric measurements and basic morphological information of galaxies and stars, with the advantage of allowing for various measurements of fluxes at any chosen position without the need of a full detection run, and for determining the basic morphological features of the sources.
NASAs Kepler, K2 and TESS missions employ Simple Aperture Photometry (SAP) to derive time-series photometry, where an aperture is estimated for each star, and pixels containing each star are summed to create a single light curve. This method is simple, but in crowded fields the derived time-series can be highly contaminated. The alternate method of fitting a Point Spread Function (PSF) to the data is able to account for crowding, but is computationally expensive. In this paper, we present a new approach to extracting photometry from these time-series missions, which fits the PSF directly, but makes simplifying assumptions in order to greatly reduce the computation expense. Our method fixes the scene of the field in each image, estimates the PSF shape of the instrument with a linear model, and allows only source flux and position to vary. We demonstrate that our method is able to separate the photometry from blended targets in the Kepler dataset that are separated by less than a pixel. Our method is fast to compute, and fully accounts for uncertainties from degeneracies due to crowded fields. We name the method described in this work Linearized Field Deblending (LFD). We demonstrate our method on the false positive Kepler target koi. We are able to separate the photometry of the two sources in the data, and demonstrate the contaminating transiting signal is consistent with a small, sub-stellar companion with a radius of $2.67R_{jup}$ ($0.27R_{sol}$). Our method is equally applicable to extracting photometry from NASAs TESS mission.
We have pioneered a new method for the measurement of extragalactic distances. This method uses the time-lag between variations in the short wavelength and long wavelength light from an active galactic nucleus (AGN), based on a quantitative physical model of dust reverberation that relates the time-lag to the absolute luminosity of the AGN. We use the large homogeneous data set from intensive monitoring observations in optical and near-infrared wavelength bands with the dedicated 2-m MAGNUM telescope to obtain the distances to 17 AGNs in the redshift range z=0.0024 to z=0.0353. These distance measurements are compared with distances measured using Cepheid variable stars, and are used to infer that H_0= 73 +- 3 (random) km/s/Mpc. The systematic error in H_0 is examined, and the uncertainty in the size distribution of dust grains is the largest source of the systematic error, which is much reduced for a sample of AGNs for which their parameter values in the model of dust reverberation are individually measured. This AGN time-lag method can be used beyond 30 Mpc, the farthest distance reached by extragalactic Cepheids, and can be extended to high-redshift quasi-stellar objects.
Aims: We developed a new method of estimating the stellar parameters Teff, log g, [M/H], and elemental abundances. This method was implemented in a new code, SP_Ace (Stellar Parameters And Chemical abundances Estimator). This is a highly automated code suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R=2,000-20,000). Methods: After the astrophysical calibration of the oscillator strengths of 4643 absorption lines covering the wavelength ranges 5212-6860AA and 8400-8924AA, we constructed a library that contains the equivalent widths (EW) of these lines for a grid of stellar parameters. The EWs of each line are fit by a polynomial function that describes the EW of the line as a function of the stellar parameters. The coefficients of these polynomial functions are stored in a library called the $GCOG$ library. SP_Ace, a code written in FORTRAN95, uses the GCOG library to compute the EWs of the lines, constructs models of spectra as a function of the stellar parameters and abundances, and searches for the model that minimizes the $chi^2$ deviation when compared to the observed spectrum. The code has been tested on synthetic and real spectra for a wide range of signal-to-noise and spectral resolutions. Results: SP_Ace derives stellar parameters such as Teff, log g, [M/H], and chemical abundances of up to ten elements for low to medium resolution spectra of FGK-type stars with precision comparable to the one usually obtained with spectra of higher resolution. Systematic errors in stellar parameters and chemical abundances are presented and identified with tests on synthetic and real spectra. Stochastic errors are automatically estimated by the code for all the parameters. A simple Web front end of SP_Ace can be found at http://dc.g-vo.org/SP_ACE, while the source code will be published soon.
Photometric redshifts, which have become the cornerstone of several of the largest astronomical surveys like PanStarrs, DES, J-PAS or the LSST, require precise measurements of galaxy photometry in different bands using a consistent physical aperture. This is not trivial, due to the variation in the shape and width of the Point Spread Function (PSF) introduced by wavelength differences, instrument positions and atmospheric conditions. Current methods to correct for this effect rely on a detailed knowledge of the PSF characteristics as a function of the survey coordinates, which can be difficult due to the relative paucity of stars tracking the PSF behaviour. Here we show that it is possible to measure accurate, consistent multicolour photometry without knowing the shape of PSF. The Chebyshev-Fourier Functions (CHEFs) can fit the observed profile of each object and produce high signal-to-noise integrated flux measurements unaffected by the PSF. These total fluxes, which encompass all the galaxy populations, are much more useful for Galaxy Evolution studies than aperture photometry. We compare the total magnitudes and colours obtained using our software to traditional photometry with SExtractor, using real data from the COSMOS survey and the Hubble Ultra Deep Field. We also apply the CHEFs technique to the recently published Extreme Deep Field and compare the results to those from ColorPro on the HUDF. We produce a photometric catalogue with 35732 sources (10823 with S/N>5), reaching a photometric redshift precision of 2% due to the extraordinary depth and wavelength coverage of the XDF images.
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