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 flux
es 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]
We present ROBO, a model and its companion code for the study of the interstellar medium (ISM). The aim is to provide an accurate description of the physical evolution of the ISM and to set the ground for an ancillary tool to be inserted in NBody-Tre
e-SPH (NB-TSPH) simulations of large scale structures in cosmological context or of the formation and evolution of individual galaxies. The ISM model consists of gas and dust. The gas chemical composition is regulated by a network of reactions that includes a large number of species (hydrogen and deuterium based molecules, helium, and metals). New reaction rates for the charge transfer in $mathrm H^+$ and $mathrm H_2$ collisions are presented. The dust contains the standard mixture of carbonaceous grains (graphite grains and PAHs) and silicates of which the model follows the formation and destruction by several processes. The model takes into account an accurate treatment of the cooling process, based on several physical mechanisms, and cooling functions recently reported in the literature. The model is applied to a wide range of the input parameters and the results for important quantities describing the physical state of the gas and dust are presented. The results are organized in a database suited to the artificial neural networks (ANNs). Once trained, the ANNs yield the same results obtained by ROBO, with great accuracy. We plan to develop ANNs suitably tailored for applications to NB-TSPH simulations of cosmological structures and/or galaxies.
