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Astroaccesible is an outreach project hosted by the Instituto de Astrof\'{\i}sica de Andaluc\'{\i}a - CSIC aimed at the teaching and popularisation of the astronomy among all publics independently of their capabilities and abilities, paying special attention to the collective of blind and visually impaired (BVI). Among the different strategies and resources using in our project, we have developed new 3D models representing in relief some of the stars, constellations and deep sky objects that can be observed during night from the Northern hemisphere in spring and summer. These models can be used by BVI to transmit to them the spatial configuration of the sky during night, but can be also used as an additional resource for all kind of publics to complement their sensorial experience. We also describe additional resources based on sounds that can also be employed to get deeper into this multisensorial experience. Finally, we summarize some of the activities and the context in which this new material has been used in the last 2 years., Comment: 6 pages, 2 figures. To appear as proceeding of the 15th Scientific Meeting of the Spanish Astronomical Society

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will soon start to scan thousands of square degrees of the northern extragalactic sky with a unique set of $56$ optical filters from a dedicated $2.55$m telescope, JST, at the Javalambre Astrophysical Observatory. Before the arrival of the final instrument (a 1.2 Gpixels, 4.2deg$^2$ field-of-view camera), the JST was equipped with an interim camera (JPAS-Pathfinder), composed of one CCD with a 0.3deg$^2$ field-of-view and resolution of 0.23 arcsec pixel$^{-1}$. To demonstrate the scientific potential of J-PAS, with the JPAS-Pathfinder camera we carried out a survey on the AEGIS field (along the Extended Groth Strip), dubbed miniJPAS. We observed a total of $\sim 1$ deg$^2$, with the $56$ J-PAS filters, which include $54$ narrow band (NB, $\rm{FWHM} \sim 145$Angstrom) and two broader filters extending to the UV and the near-infrared, complemented by the $u,g,r,i$ SDSS broad band (BB) filters. In this paper we present the miniJPAS data set, the details of the catalogues and data access, and illustrate the scientific potential of our multi-band data. The data surpass the target depths originally planned for J-PAS, reaching $\rm{mag}_{\rm {AB}}$ between $\sim 22$ and $23.5$ for the NB filters and up to $24$ for the BB filters ($5\sigma$ in a $3$~arcsec aperture). The miniJPAS primary catalogue contains more than $64,000$ sources extracted in the $r$ detection band with forced photometry in all other bands. We estimate the catalogue to be complete up to $r=23.6$ for point-like sources and up to $r=22.7$ for extended sources. Photometric redshifts reach subpercent precision for all sources up to $r=22.5$, and a precision of $\sim 0.3$% for about half of the sample. (Abridged), Comment: The miniJPAS data and associated value added catalogues are publicly accessible via this url: http://archive.cefca.es/catalogues/minijpas-pdr201912

This paper describes the Bayesian Technique for Multi-image Analysis (BaTMAn), a novel image-segmentation technique based on Bayesian statistics that characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). We illustrate its operation and performance with a set of test cases including both synthetic and real Integral-Field Spectroscopic data. The output segmentations adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. The quality of the recovered signal represents an improvement with respect to the input, especially in regions with low signal-to-noise ratio. However, the algorithm may be sensitive to small-scale random fluctuations, and its performance in presence of spatial gradients is limited. Due to these effects, errors may be underestimated by as much as a factor of two. Our analysis reveals that the algorithm prioritizes conservation of all the statistically-significant information over noise reduction, and that the precise choice of the input data has a crucial impact on the results. Hence, the philosophy of BaTMAn is not to be used as a `black box' to improve the signal-to-noise ratio, but as a new approach to characterize spatially-resolved data prior to its analysis. The source code is publicly available at http://astro.ft.uam.es/SELGIFS/BaTMAn ., Comment: 21 pages, 7 Figure, 4 Tables

We present Pipe3D, an analysis pipeline based on the FIT3D fitting tool, devel- oped to explore the properties of the stellar populations and ionized gas of Integral Field Spectroscopy data. Pipe3D was created to provide with coherent, simple to distribute, and comparable dataproducts, independently of the origin of the data, focused on the data of the most recent IFU surveys (e.g., CALIFA, MaNGA, and SAMI), and the last generation IFS instruments (e.g., MUSE). Along this article we describe the different steps involved in the analysis of the data, illustrating them by showing the dataproducts derived for NGC 2916, observed by CALIFA and P-MaNGA. As a practical use of the pipeline we present the complete set of dataproducts derived for the 200 datacubes that comprises the V500 setup of the CALIFA Data Release 2 (DR2), making them freely available through the network (ftp://ftp.caha.es/CALIFA/dataproducts/DR2/Pipe3D). Finally, we explore the hypothesis that the properties of the stellar populations and ionized gas of galaxies at the effective radius are representative of the overall average ones, finding that this is indeed the case., Comment: 53 pages, 17 figures, accepted for publishing in RevMxAA

The Square Kilometre Array (SKA) is called to revolutionise essentially all areas of Astrophysics. With a collecting area of about a square kilometre, the SKA will be a transformational instrument, and its scientific potential will go beyond the interests of astronomers. Its technological challenges and huge cost requires a multinational effort, and Europe has recognised this by putting the SKA on the roadmap of the European Strategy Forum for Research Infrastructures (ESFRI). The Spanish SKA White Book is the result of the coordinated effort of 120 astronomers from 40 different research centers. The book shows the enormous scientific interest of the Spanish astronomical community in the SKA and warrants an optimum scientific exploitation of the SKA by Spanish researchers, if Spain enters the SKA project., Comment: Editors: Miguel A. Perez-Torres (Editor-in-chief), L. Verdes-Montenegro, J. C. Guirado, A. Alberdi, J. Martin-Pintado, R. Bachiller, D. Herranz, J. M. Girart, J. Gorgas, C. Hernandez-Monteagudo, S. Migliari and J. M. Rodriguez Espinosa; 289 pages, published in June 2015 by Sociedad Espa\~nola de Astronom\'ia

[Abridged] Detecting cosmic ray hits (cosmics) in fiber-fed IFS data of single exposures is a challenging task, because of the complex signal recorded by IFS instruments. Existing detection algorithms are commonly found to be unreliable in the case of IFS data and the optimal parameter settings are usually unknown a-priori for a given dataset. The CALIFA survey generates hundreds of IFS datasets for which a reliable and robust detection algorithm for cosmics is required as an important part of the fully automatic CALIFA data reduction pipeline. We developed a novel algorithm, PyCosmic, which combines the edge-detection algorithm of L.A.Cosmic with a point-spread function convolution scheme. We generated mock data to compute the efficiency of different algorithms for a wide range of characteristic fibre-fed IFS datasets using the PMAS and VIMOS IFS instruments as representative cases. PyCosmic is the only algorithm that achieves an acceptable detection performance for CALIFA data. We find that PyCosmic is the most robust tool with a detection rate of >~90% and a false detection rate <5% for any of the tested IFS data. It has one less free parameter than the L.A.Cosmic algorithm. Only for strongly undersampled IFS data does L.A.Cosmic exceed the performance of PyCosmic by a few per cent. DCR never reaches the efficiency of the other two algorithms and should only be used if computational speed is a concern. Thus, PyCosmic appears to be the most versatile cosmics detection algorithm for IFS data. It is implemented in the new CALIFA data reduction pipeline as well as in recent versions of the multi-instrument IFS pipeline P3D., Comment: 10 pages, 8 figures, accepted for publication in A&A, updated after language editing of the publisher