Publicaciones: Técnicas

Publicaciones: Técnicas

GRANDMA (Global Rapid Advanced Network Devoted to the Multi-messenger Addicts) is a network of 25 telescopes of different sizes, including both photometric and spectroscopic facilities. The network aims to coordinate follow-up observations of gravitational-wave (GW) candidate alerts, especially those with large localization uncertainties, to reduce the delay between the initial detection and the optical confirmation. In this paper, we detail GRANDMA's observational performance during Advanced LIGO/Advanced Virgo Observing Run 3 (O3), focusing on the second part of O3; this includes summary statistics pertaining to coverage and possible astrophysical origin of the candidates. To do so, we quantify our observation efficiency in terms of delay between GW candidate trigger time, observations, and the total coverage. Using an optimized and robust coordination system, GRANDMA followed-up about 90 per cent of the GW candidate alerts, that is 49 out of 56 candidates. This led to coverage of over 9000 deg2 during O3. The delay between the GW candidate trigger and the first observation was below 1.5 h for 50 per cent of the alerts. We did not detect any electromagnetic counterparts to the GW candidates during O3, likely due to the very large localization areas (on average thousands of degrees squares) and relatively large distance of the candidates (above 200 Mpc for 60 per cent of binary neutron star, BNS candidates). We derive constraints on potential kilonova properties for two potential BNS coalescences (GW190425 and S200213t), assuming that the events' locations were imaged.

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The location of large telescopes, generally far from the data processing centers, represents a logistical problem for the supervision of the capture of images. In this work, we carried out a preliminary study of the vibration signature of the T80 telescope at the Javalambre Astrophysical Observatory (JAO). The study analyzed the process of calculating the displacement that occurs because of the vibration in each of the frequencies in the range of interest. We analyzed the problems associated with very low frequencies by means of simulation, finding the most critical vibrations below 20 Hz, since they are the ones that generate greater displacements. The work also relates previous studies based on simulation with the real measurements of the vibration of the telescope taken remotely when it is subjected to different positioning movements (right ascension and/or declination) or when it performs movement actions such as those related to filter trays or mirror cover. The obtained results allow us to design a remote alarm system to detect invalid images (taken with excess vibration).

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Context. Future astrophysical surveys such as J-PAS will produce very large datasets, the so-called "big data", which will require the deployment of accurate and efficient machine-learning (ML) methods. In this work, we analyze the miniJPAS survey, which observed about ∼1 deg2 of the AEGIS field with 56 narrow-band filters and 4 ugri broad-band filters. The miniJPAS primary catalog contains approximately 64 000 objects in the r detection band (magAB ≲ 24), with forced-photometry in all other filters. Aims: We discuss the classification of miniJPAS sources into extended (galaxies) and point-like (e.g., stars) objects, which is a step required for the subsequent scientific analyses. We aim at developing an ML classifier that is complementary to traditional tools that are based on explicit modeling. In particular, our goal is to release a value-added catalog with our best classification. Methods: In order to train and test our classifiers, we cross-matched the miniJPAS dataset with SDSS and HSC-SSP data, whose classification is trustworthy within the intervals 15 ≤ r ≤ 20 and 18.5 ≤ r ≤ 23.5, respectively. We trained and tested six different ML algorithms on the two cross-matched catalogs: K-nearest neighbors, decision trees, random forest (RF), artificial neural networks, extremely randomized trees (ERT), and an ensemble classifier. This last is a hybrid algorithm that combines artificial neural networks and RF with the J-PAS stellar and galactic loci classifier. As input for the ML algorithms we used the magnitudes from the 60 filters together with their errors, with and without the morphological parameters. We also used the mean point spread function in the r detection band for each pointing. Results: We find that the RF and ERT algorithms perform best in all scenarios. When the full magnitude range of 15 ≤ r ≤ 23.5 is analyzed, we find an area under the curve AUC = 0.957 with RF when photometric information alone is used, and AUC = 0.986 with ERT when photometric and morphological information is used together. When morphological parameters are used, the full width at half maximum is the most important feature. When photometric information is used alone, we observe that broad bands are not necessarily more important than narrow bands, and errors (the width of the distribution) are as important as the measurements (central value of the distribution). In other words, it is apparently important to fully characterize the measurement. Conclusions: ML algorithms can compete with traditional star and galaxy classifiers; they outperform the latter at fainter magnitudes (r ≳ 21). We use our best classifiers, with and without morphology, in order to produce a value-added catalog. Full Table 2 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/645/A87 The catalog is available at http://j-pas.org/datareleases via the ADQL table minijpas.StarGalClass. The ML models are available at http://github.com/J-PAS-collaboration/StarGalClass-MachineLearning.

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The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) will scan thousands of square degrees of the northern sky with a unique set of 56 filters using the dedicated 2.55 m Javalambre Survey Telescope (JST) at the Javalambre Astrophysical Observatory. Prior to the installation of the main camera (4.2 deg2 field-of-view with 1.2 Gpixels), the JST was equipped with the JPAS-Pathfinder, a one CCD camera with a 0.3 deg2 field-of-view and plate scale of 0.23 arcsec pixel−1. To demonstrate the scientific potential of J-PAS, the JPAS-Pathfinder camera was used to perform miniJPAS, a ∼1 deg2 survey of the AEGIS field (along the Extended Groth Strip). The field was observed with the 56 J-PAS filters, which include 54 narrow band (FWHM ∼ 145 Å) and two broader filters extending to the UV and the near-infrared, complemented by the u, g, r, i SDSS broad band filters. In this miniJPAS survey overview paper, we present the miniJPAS data set (images and catalogs), as we highlight key aspects and applications of these unique spectro-photometric data and describe how to access the public data products. The data parameters reach depths of magAB ≃ 22−23.5 in the 54 narrow band filters and up to 24 in the broader filters (5σ in a 3″ aperture). The miniJPAS primary catalog contains more than 64 000 sources detected in the r band and with matched photometry in all other bands. This catalog is 99% complete at r = 23.6 (r = 22.7) mag for point-like (extended) sources. We show that our photometric redshifts have an accuracy better than 1% for all sources up to r = 22.5, and a precision of ≤0.3% for a subset consisting of about half of the sample. On this basis, we outline several scientific applications of our data, including the study of spatially-resolved stellar populations of nearby galaxies, the analysis of the large scale structure up to z ∼ 0.9, and the detection of large numbers of clusters and groups. Sub-percent redshift precision can also be reached for quasars, allowing for the study of the large-scale structure to be pushed to z > 2. The miniJPAS survey demonstrates the capability of the J-PAS filter system to accurately characterize a broad variety of sources and paves the way for the upcoming arrival of J-PAS, which will multiply this data by three orders of magnitude.

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The first JPLUS Data Release (July 2018) provided data in 12 filters, covering a total area of 1022 deg^2, collected from November 2015 to January 2018 by the JAST/T80 telescope. The JPLUS Consortium aims to include the astrophysical parameters of the sources in the JPLUS DR1 added value catalogue. As a first step temperatures are derived for a small set of stars (Gold sample) with the best photometric precision in all filters. This work derives temperatures from JPLUS colours of this Gold sample. The addition of Gaia mission second release (GDR2, April 2018) information, with magnitudes, parallaxes and colours for more than one billion sources is very useful to determine the astrophysical parameters of the stellar content in JPLUS data. In particular, the use of Gaia parallaxes are used to improve the characterisation of the observed sources.

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The Javalambre Survey Telescope (JST/T250) is a wide-field 2.6 m telescope ideal for carrying out large sky photometric surveys from the Javalambre Astrophysical Observatory in Teruel, Spain. The most immediate goal of JST is to perform J-PAS, a survey of several thousands square degrees of the Northern sky in 59 optical bands, 54 of them narrow (˜ 145 Å FWHM) and contiguous. J-PAS will provide a low resolution photo-spectrum for every pixel of the sky, hence promising crucial breakthroughs in Cosmology and Astrophysics. J-PAS will be conducted with JPCam, a camera with a mosaic of 14 CCDs of 9.2k × 9.2k pix, more than 1200 Mpix and an effective FoV of 4.3 deg2 . Before JPCam is on telescope, the project will work in 2018 with an interim camera, JPAS-Pathfinder, with a reduced FoV of ˜ 0.6 × 0.6 deg2 to perform commissioning and the first JST science. This paper presents the current status and performance of the JST telescope, describing the commissioning and first science of the JPAS-Pathfinder at JST.

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The Observatorio Astrofísico de Javalambre (OAJ) is a new Spanish astronomical facility particularly designed for carrying out large sky surveys. The OAJ is mainly motivated by the development of J-PAS, the Javalambre- PAU Astrophysical Survey, an unprecedented astronomical survey that aims to observe 8500 deg² of the sky with a set of 54 optical contiguous narrow-band filters (FWHM ~14 nm) and 5 mid and broad-band ones. J-PAS will provide a low resolution spectrum (R ~ 50) for every pixel of the Northern sky down to AB~22:5 - 23:5 per square arcsecond (at 5 σ level), depending on the narrow-band filter, and ~ 2 magnitudes deeper for the redder broad-band filters. The main telescope at the OAJ is the Javalambre Survey Telescope (JST/T250), an innovative Ritchey-Chrétien, alt-azimuthal, large-etendue telescope with a primary mirror diameter of 2.55m and 3 deg (diameter) FoV. The JST/T250 is the telescope devoted to conduct J-PAS with JPCam, a panoramic camera of 4.7 deg² FoV and a mosaic of 14 large format CCDs that, overall, amounts to 1.2 Gpix. The second largest telescope at the OAJ is the Javalambre Auxiliary Survey Telescope (JAST/T80), a Ritchey-Chrétien, German-equatorial telescope of 82 cm primary mirror and 2 deg FoV, whose main goal is to perform J-PLUS, the Javalambre Photometric Local Universe Survey. J-PLUS will cover the same sky area of J-PAS using the panoramic camera T80Cam with 12 filters in the optical range, which are specifically defined to perform the photometric calibration of J-PAS. The OAJ project officially started in mid 2010. Four years later, the OAJ is mostly completed and the first OAJ operations have already started. The civil work and engineering installations are finished, including the telescope buildings and the domes. JAST/T80 is at the OAJ undertaking commissioning tasks, and JST/T250 is in AIV phase at the OAJ. Related astronomical subsystems like the seeing and atmospheric extinction monitors and the all-sky camera are fully operative. This paper aims to present a brief description and status of the OAJ main installations, telescopes and cameras. The current development and operation plan of the OAJ in terms of staffing organization, resources, observation scheduling, and data archiving, is also described.

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The Javalambre Photometric Local Universe Survey (J-PLUS) is an ongoing 12 band photometric optical survey, observing thousands of square degrees of the Northern Hemisphere from the dedicated JAST80 telescope at the Observatorio Astrofísico de Javalambre (OAJ). Observational strategy is a critical point in this large survey. To plan the best observations, it is necessary to select pointings depending on object visibility, the pointing priority and status and location and phase of the Moon. In this context, the J-PLUS Tracking Tool, a web application, has been implemented, which includes tools to plan the best observations, as well as tools to create the command files for the telescope; to track the observations; and to know the status of the survey. In this environment, robustness is an important point. To obtain it, a feedback software system has been implemented. This software automatically decides and marks which observations are valid or which must be repeated. It bases its decision on the data obtained from the data management pipeline database using a complex system of pointing and filter statuses. This contribution presents J-PLUS Tracking Tool and all feedback software system.

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The Centro de Estudios de Física del Cosmos de Aragón (CEFCA) is carrying out from the Observatorio Astrofísico de Javalambre (OAJ, Teruel, Spain) two large area multiband photometric sky surveys, J-PLUS and J-PAS, covering the entire optical spectrum using narrow and broad band filters. J-PAS and J-PLUS include coadded and individual frame images and dual and single catalogue data. To publish all of this data, the CEFCA catalogues portal has been implemented offering web user interface services, as well, as Virtual Observatory (VO) services. This contribution presents the effort and work done in the CEFCA Catalogues Portal to enhance data publication of these large surveys following FAIR principles to increase data value and maximize research efficiency. It presents how FAIR principles have been achieved and improved with the implementation and publishing of the CEFCA Catalogues Publishing Registry, the use of VO services, their validation and improving processes and the effort made to offer data to improve provenance information.

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The Observatorio Astrofísico de Javalambre (OAJ, Teruel, Spain) has two main telescopes: JST/T250, a 2.5m 3 deg FoV and JAST/T80 with 2 deg FoV. From OAJ two large area multiband photometric sky surveys of 8500 square degrees are being carried out. J-PAS using 54 narrow and 5 broad band filters and J-PLUS using 12 filters. The OAJ also offers 20% of observing time to the community. This contribution presents different web applications designed and implemented at the Centro de Estudios de Física del Cosmos de Aragón (CEFCA) used for a variety of purposes: scheduling and tracking of the different observations, management and data quality review of the products of the reduction pipeline, external access to the data products of the Open Observing Time, and external access and visualization of the images and catalogues of the J-PLUS and J-PAS surveys using services such as images search, cone search, object list search, object visualization, sky navigation and asynchronous queries (ADQL). All web applications have been developed with Python language and PostgreSQL database.

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The Observatorio Astrofísico de Javalambre consists of two main telescopes: JST/T250, a 2.5 m telescope with a FoV of 3 deg, and JAST/T80, a 83 cm with a 2 deg FoV. JST/T250 will be devoted to complete the Javalambre-PAU Astronomical Survey (J-PAS). It is a photometric survey with a system of 54 narrow-band plus 3 broad-band filters covering an area of 8500°^2. The JAST/T80 will perform the J-PLUS survey, covering the same area in a system of 12 filters. This contribution presents the software and hardware architecture designed to store and process the data. The processing pipeline runs daily and it is devoted to correct instrumental signature on the science images, to perform astrometric and photometric calibration, and the computation of individual image catalogs. In a second stage, the pipeline performs the combination of the tile mosaics and the computation of final catalogs. The catalogs are ingested in as Scientific database to be provided to the community. The processing software is connected with a management database to store persistent information about the pipeline operations done on each frame. The processing pipeline is executed in a computing cluster under a batch queuing system. Regarding the storage system, it will combine disk and tape technologies. The disk storage system will have capacity to store the data that is accessed by the pipeline. The tape library will store and archive the raw data and earlier data releases with lower access frequency.

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The Observatorio Astrofísico de Javalambre have two main telescopes: JST/T250, a 2.5m 3deg FoV and JAST/T80 with 2deg FoV. From OAJ two surveys of 8500 square degrees will be carried out. J-PAS using 54 narrow and several broad band filters and J-PLUS using 12 filters. Both surveys will produce ~2.5 PB of data. This contribution presents the software and hardware architecture to store, process and publish the data. Results about pipeline and hardware performance with data collected during the first months of JAST/T80 operation will be presented.

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Located at the Observatorio Astrofísico de Javalambre, the ’’Javalambre Auxiliary Survey Telescope’’ is an 80cm telescope with a unvignetted 2 square degrees field of view. The telescope is equipped with T80Cam, a camera with a large format CCD and two filter wheels which can host, at any given time, 12 filters. The telescope has been designed to provide optical quality all across the field of view, which is achieved with a field corrector. In this talk, I will review the commissioning of the telescope. The optical performance in the centre of the field of view has been tested with lucky imaging technique, providing a telescope PSF of 0.4’’, which is close to the one expected from theory. Moreover, the tracking of the telescope does not affect the image quality, as it has been shown that stars appear round even in exposures of 10minutes obtained without guiding. Most importantly, we present the preliminary results of science verification observations which combine the two main characteristics of this telescope: the large field of view and the special filter set.

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Context. We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential for identifying low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. Aims: SPEEM is a tool used to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars based on the unique J-PLUS photometric system. The adoption of adequate selection criteria allows for the identification of metal-poor star candidates that are suitable for spectroscopic follow-up investigations. Methods: SPEEM consists of a series of machine-learning models that use a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures, Teff, between 4800 K and 9000 K, values of log g between 1.0 and 4.5, as well as −3.1 < [Fe/H] < +0.5. The performance of the pipeline was tested with a sample of stars observed by the LAMOST survey within the same parameter range. Results: The average differences between the parameters of a sample of stars observed with SEGUE and J-PLUS, obtained with the SEGUE Stellar Parameter Pipeline and SPEEM, respectively, are ΔTeff ~ 41 K, Δlog g ~ 0.11 dex, and Δ[Fe/H] ~ 0.09 dex. We define a sample of 177 stars that have been identified as new candidates with [Fe/H] < −2.5, with 11 of them having been observed with the ISIS spectrograph at the William Herschel Telescope. The spectroscopic analysis confirms that 64% of stars have [Fe/H] < −2.5, including one new star with [Fe/H] < −3.0. Conclusions: Using SPEEM in combination with the J-PLUS filter system has demonstrated their potential in estimating the stellar atmospheric parameters (Teff, log g, and [Fe/H]). The spectroscopic validation of the candidates shows that SPEEM yields a success rate of 64% on the identification of very metal-poor star candidates with [Fe/H] < −2.5.

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This paper presents time-series observations and analysis of broadband night sky airglow intensity 4 September 2018 through 30 April 2020. Data were obtained at 5 sites spanning more than 8500 km during the historically deep minimum of Solar Cycle 24 into the beginning of Solar Cycle 25. New time-series observations indicate previously unrecognized significant sources of broadband night sky brightness variations, not involving corresponding changes in the Sun's 10.7 cm solar flux, occur during deep solar minimum. New data show; (1) Even during a deep solar minimum the natural night sky is rarely, if ever, constant in brightness. Changes with time-scales of minutes, hours, days, and months are observed. (2) Semi-annual night sky brightness variations are coincident with changes in the orientation of Earth's magnetic field relative to the interplanetary magnetic field. (3) Solar wind plasma streams from solar coronal holes arriving at Earth's bow shock nose are coincident with major night sky brightness increase events. (4) Sites more than 8500 km along the Earth's surface experience nights in common with either very bright or very faint night sky airglow emissions. The reason for this observational fact remains an open question. (5) It is plausible, terrestrial night airglow and geomagnetic indices have similar responses to the solar energy input into Earth's magnetosphere. Our empirical results contribute to a quantitative basis for understanding and predicting broadband night sky brightness variations. They are applicable in astronomical, planetary science, space weather, light pollution, biological, and recreational studies.

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The Centro de Estudios de Física del Cosmos de Aragón (CEFCA) is carrying out two large area multiband photometric sky surveys, J-PLUS and J-PAS, from the Observatorio Astrofísico de Javalambre (OAJ, Teruel, Spain) covering the entire optical spectrum using narrow and broad band filters. As an effort to make the data public, we offer Virtual Observatory (VO) compliant services to make the access to the data more versatile through the multiple VO compliant existent tools. For example, catalogues are offered through TAP protocol and images can be searched and downloaded using the SIAP protocol. This contribution summarizes why we decided to make our own implementation, the process we followed to choose which services to implement according to the kind of data generated by the survey, why Python and PostgreSQL were chosen and, finally, the lessons learned.

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GALANTE is an optical (3000-9000 Å) photometric survey with seven intermediate/narrow filters that has been covering the Galactic Plane since 2016 using the Javalambre JAST/T80. The GALANTE photometric system (defined in Lorenzo et al. 2019) is designed to identify the majority of the early-type massive stars within several kpc of the Sun and derive estimations for stellar parameters (Maíz Apellániz & Sota 2008; Maíz Apellániz et al. 2014). The calibration scheme make use of external 2MASS and Gaia (photometric and astrometric) data. As of mid 2020, 21% of the project observations have been completed, resulting in over 300 1.4°x1.4° astronomical fields. The pipeline is functional and here we focus on our test field, Berkeley 59, showing preliminary results. The collaboration will ultimately provide a 7-filter photometric catalog of stars with a precision of several mili-magnitudes.

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Wide field photometric surveys aim at observing large areas of sky in various filters. Yet, almost all surveys use constant exposure times, regardless of the quality of the images or the level of background, mostly due to the moon, which may result in a lack of homogeneity in the data sets. In the J-PLUS survey,1 modulating the exposure time with the sky background has resulted not only in an improved homogeneity of the data but also in a significant improvement of the efficiency of the survey execution. In this paper, we show the effect on J-PAS and J-PLUS of using fixed exposure times, regardless of the Moon background, and we describe the system to estimate this background reliably and provide a significant improvement, not only in the quality of the observations, but also in the survey speed.

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Context. Multifilter photometry from large sky surveys is commonly used to assign asteroid taxonomic types and study various problems in planetary science. To maximize the science output of those surveys, it is important to use methods that best link the spectro-photometric measurements to asteroid taxonomy. Aims: We aim to determine which machine learning methods are the most suitable for the taxonomic classification for various sky surveys. Methods: We utilized five machine learning supervised classifiers: logistic regression, naive Bayes, support vector machines (SVMs), gradient boosting, and MultiLayer Perceptrons (MLPs). Those methods were found to reproduce the Bus-DeMeo taxonomy at various rates depending on the set of filters used by each survey. We report several evaluation metrics for a comprehensive comparison (prediction accuracy, balanced accuracy, F1 score, and the Matthews correlation coefficient) for 11 surveys and space missions. Results: Among the methods analyzed, multilayer perception and gradient boosting achieved the highest accuracy and naive Bayes achieved the lowest accuracy in taxonomic prediction across all surveys. We found that selecting the right machine learning algorithm can improve the success rate by a factor of >2. The best balanced accuracy (~85% for a taxonomic type prediction) was found for the Visible and Infrared Survey telescope for Astronomy (VISTA) and the ESA Euclid mission surveys where broadband filters best map the 1 µm and 2 µm olivine and pyroxene absorption bands. Conclusions: To achieve the highest accuracy in the taxonomic type prediction based on multifilter photometric measurements, we recommend the use of gradient boosting and MLP optimized for each survey. This can improve the overall success rate even when compared with naive Bayes. A merger of different datasets can further boost the prediction accuracy. For the combination of the Legacy Survey of Space and Time and VISTA survey, we achieved 90% for the taxonomic type prediction.

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Context. The importance of photometric galaxy redshift estimation is rapidly increasing with the development of specialised powerful observational facilities. Aims: We develop a new photometric redshift estimation workflow TOPz to provide reliable and efficient redshift estimations for the upcoming large-scale survey J-PAS which will observe 8500 deg2 of the northern sky through 54 narrow-band filters. Methods: TOPz relies on template-based photo-z estimation with some added J-PAS specific features and possibilities. We present TOPz performance on data from the miniJPAS survey, a precursor to the J-PAS survey with an identical filter system. First, we generated spectral templates based on the miniJPAS sources using the synthetic galaxy spectrum generation software CIGALE. Then we applied corrections to the input photometry by minimising systematic offsets from the template flux in each filter. To assess the accuracy of the redshift estimation, we used spectroscopic redshifts from the DEEP2, DEEP3, and SDSS surveys, available for 1989 miniJPAS galaxies with r < 22 magAB. We also tested how the choice and number of input templates, photo-z priors, and photometric corrections affect the TOPz redshift accuracy. Results: The general performance of the combination of miniJPAS data and the TOPz workflow fulfills the expectations for J-PAS redshift accuracy. Similarly to previous estimates, we find that 38.6% of galaxies with r < 22 mag reach the J-PAS redshift accuracy goal of dz/(1 + z) < 0.003. Limiting the number of spectra in the template set improves the redshift accuracy up to 5%, especially for fainter, noise-dominated sources. Further improvements will be possible once the actual J-PAS data become available.

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This paper describes the characterization of the GALANTE photometric system, a seven intermediate- and narrow-band filter system with a wavelength coverage from 3000 Å to 9000 Å. We describe the photometric system presenting the full sensitivity curve as a product of the filter sensitivity, CCD, telescope mirror, and atmospheric transmission curves, as well as some first- and second-order moments of this sensitivity function. The GALANTE photometric system is composed of four filters from the J-PLUS photometric system, a twelve broad-to-narrow filter system, and three exclusive filters, specifically designed to measure the physical parameters of stars such as effective temperature Teff, log (g), metallicity, colour excess E(4405 - 5495), and extinction type R5495. Two libraries, the Next Generation Spectral Library (NGSL) and the one presented in Maíz Apellániz & Weiler (2018), have been used to determine the transformation equations between the Sloan Digital Sky Survey (SDSS) ugriz photometry and the GALANTE photometric system. We will use this transformation to calibrate the zero-points of GALANTE images. To this end, a preliminary photometric calibration of GALANTE has been made based on two different griz libraries (SDSS DR12 and ATLAS All-Sky Stellar Reference Catalog, hereinafter RefCat2). A comparison between both zero-points is performed leading us to the choice of RefCat2 as the base catalogue for this calibration, and applied to a field in the Cyg OB2 association.

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We present the first data release of the Javalambre Local Universe Photometric Survey (J-PLUS), an ongoing photometric survey with 12 optical bands observing thousands of square degrees of the sky from the JAST/T80 telescope at the Observatorio Astrofísico de Javalambre (OAJ). T80Cam is a 2 deg² field-of-view (FoV) camera mounted on JAST/T80, and is equipped with a unique system of filters spanning the entire optical range (3500 - 10000 Å), optimally designed to extract the rest-frame spectral features that are key to both characterize stellar types and to deliver a low-resolution photo-spectrum for each observed object. With a typical depth (5σ in 3 arcsec aperture) of AB~20.7 mag per band, we release the first 1022 deg² of J-PLUS data, containing about 4.3 million stars and 3.0 million galaxies at r < 21 mag.

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Aims: We present the photometric calibration of the twelve optical passbands for the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), comprising 1088 pointings of two square degrees, and study the systematic impact of metallicity on the stellar locus technique. Methods: The [Fe/H] metallicity from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) for 146 184 high-quality calibration stars, defined with signal-to-noise ratio larger than ten in J-PLUS passbands and larger than three in Gaia parallax, was used to compute the metallicity-dependent stellar locus (ZSL). The initial homogenization of J-PLUS photometry, performed with a unique stellar locus, was refined by including the metallicity effect in colors via the ZSL. Results: The variation of the average metallicity along the Milky Way produces a systematic offset in J-PLUS calibration. This effect is well above 1% for the bluer passbands and amounts 0.07, 0.07, 0.05, 0.03, and 0.02 mag in u, J0378, J0395, J0410, and J0430, respectively. We modeled this effect with the Milky Way location of the J-PLUS pointing, also providing an updated calibration for those observations without LAMOST information. The estimated accuracy in the calibration after including the metallicity effect is at 1% for the bluer J-PLUS passbands and below for the rest. Conclusions: Photometric calibration with the stellar locus technique is prone to significant systematic bias in the Milky Way for passbands bluer than λ = 4500 Å. The calibration method for J-PLUS DR2 reaches 1-2% precision and 1% accuracy for 12 optical filters within an area of 2176 square degrees.

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Observatories and satellites around the globe produce tremendous amounts of imaging data to study many different astrophysical phenomena. The serendipitous observations of Solar System objects are a fortunate by-product which have often been neglected due to the lack of a simple yet efficient identification algorithm. Meanwhile, the determination of the orbit, chemical composition, and physical properties such as rotation period and 3D-shape of Solar System objects requires a large number of astrometry and multi-band photometry observations. Such observations are hidden in current and future astrophysical archives, and a method to harvest these goldmines is needed. This article presents an easy-to-implement, light-weight software package which detects bodies of the Solar System in astronomical images and measures their astrometry and photometry. The ssos pipeline is versatile, allowing for application to all kinds of observatory imaging products. The sole principle requirement is that the images observe overlapping areas of the sky within a reasonable time range. Both known and unknown Solar System objects are recovered, from fast-moving near-Earth asteroids to slow objects in the distant Kuiper belt. The high-level pipeline design and two test applications are described here, highlighting the versatility of the algorithm with both narrow-field pointed and wide-field survey observations. In the first study, 2,828 detections of 204 SSOs are recovered from publicly available images of the GTC OSIRIS Broad Band DR1 (Cortés-Contreras, in preparation). The false-positive ratio of SSO detections ranges from 0% - 23% depending on the pipeline setup. The second test study utilizes the images of the first data release of J-PLUS, a 12-band optical survey. 4,606 SSO candidates are recovered, with a false-positive ratio of (2.0 ± 0.2)%. A stricter pipeline parameter setup recovers 3,696 candidates with a sample contamination below 0.68%.

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Context. Scientific interest in studying high-energy transient phenomena in the Universe has risen sharply over the last decade. At present, multiple ground-based survey projects have emerged to continuously monitor the optical (and multi-messenger) transient sky at higher image cadences and covering ever larger portions of the sky every night. These novel approaches are leading to a substantial increase in global alert rates, which need to be handled with care, especially with regard to keeping the level of false alarms as low as possible. Therefore, the standard transient detection pipelines previously designed for narrow field-of-view instruments must now integrate more sophisticated tools to deal with the growing number and diversity of alerts and false alarms. Aims: Deep machine learning algorithms have now proven their efficiency in recognising patterns in images. These methods are now used in astrophysics to perform different classification tasks such as identifying bogus from real transient point-like sources. We explore this method to provide a robust and flexible algorithm that could be included in any kind of transient detection pipeline. Methods: We built a convolutional neural network (CNN) algorithm in order to perform a `real or bogus' classification task on transient candidate cutouts (subtraction residuals) provided by different kinds of optical telescopes. The training involved human-supervised labelling of the cutouts, which are split into two balanced data sets with `true' and `false' point-like source candidates. We tested our CNN model on the candidates produced by two different transient detection pipelines. In addition, we made use of several diagnostic tools to evaluate the classification performance of our CNN models. Results: We show that our CNN algorithm can be successfully trained on a large and diverse array of images on very different pixel scales. In this training process, we did not detect any strong over- or underfitting with the requirement of providing cutouts with a limited size no larger than 50 × 50 pixels. Tested on optical images from four different telescopes and utilising two different transient detection pipelines, our CNN model provides a robust `real or bogus' classification performance accuracy from 93% up to 98% for well-classified candidates. The codes and diagnostic tools presented in this paper are available at https://github.com/dcorre/otrain

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Commissioning results, on-sky performance and first operations of the Javalambre Panoramic Camera (JPCam) are presented in this paper. JPCam is a 1.2 Gpixel camera deployed on the 2.6m, large field-of-vie Javalambre Survey Telescope (JST250) at the Observatorio Astrofísico Javalambre. JPCam has been conceived to perform J-PAS, a photometric survey of several thousand square degrees of the northern sky in 56 optical bands, 54 of them narrow-band filters (145 ˚A FWHM), contiguous and equi-spaced between 370 and 920nm, producing a low resolution photo-spectrum of every pixel of the observed sky, hence promising crucial breakthroughs in Cosmology and galaxy formation and evolution. JPCam has been designed to maximize field-of-view and wavelength coverage while guaranteeing a high image quality over the entire focal plane. To this aim, JPCam is equipped with a mosaic of 14 9.2k x 9.2k, 10µm pixel, low noise detectors from Teledyne-E2V, providing a FoV of 4.1 square degrees with a plate scale of 0.2267''/pix. In full frame mode, camera electronics allows read times of 10.9s at 633kHz read frequency (16.4s at 400kHz) with a readout noise of 5.5e− (4.3e−). Its filter unit admits 5 filter trays, each mounting 14 filters corresponding to the 14 CCDs of the mosaic and allowing all the J-PAS filters to be permanently installed. To fully optimize image quality, position of JST250 secondary mirror and JPCam focal plane are maintained optically aligned by means of two hexapod systems. To perform this task, JPCam includes 12 auxiliary detectors, 4 for autoguiding and 8 for image quality control through wavefront sensing.

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To carry out J-PAS survey, the JST/T250 telescope at the Observatorio Astrofósico de Javalambre (OAJ) is equipped with JPCam, a panoramic camera designed to exploit survey capabilities of the telescope. JPCam is a direct imaging instrument designed to work in a fast convergent beam at the telescope’s Cassegrain focus. It is based on state-of-the-art, high efficiency, low noise 9.2k-by-9.2k, 10μm pixel CCDs specially developed by e2v for JPCam. The instrument is equipped with a 1.2Gpixel mosaic of 14 CCDs providing a useful FoV of 4.7 deg2 (67% focal plane coverage) with a plate scale of 0.2267 arcsec/pix. Moreover, JPCam includes 12 auxiliary detectors for auto-guiding and wave front sensing purposes. JPCam is completed with an innovative set of 59 optical filters specifically designed to perform accurate BAO measurements, main science driver of J-PAS.

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The Observatorio Astrofísico de Javalambre (OAJ) is a new astronomical facility located at the Sierra de Javalambre (Teruel, Spain) whose primary role will be to conduct all-sky astronomical surveys. The main OAJ facilities are two wide-field telescopes: the JST/T250, a 2.55 m telescope with a 3° diameter FoV, and the JAST/T80, a 0.83 m telescope with a 2° diameter FoV. These telescopes are equipped with panoramic cameras that have been designed to exploit the survey capabilities of the OAJ telescopes. T80Cam will be mounted at the JAST/T80 and its large format CCD covers a large fraction of the JAST/T80 FoV with a pixel scale of 0.55"pix⁻¹. The JST/T250 will be equipped with JPCam, a 14-CCD mosaic camera using the new e2v 9k-by-9k, 10 μm pixel detectors, providing a pixel scale of 0.2"pix⁻¹. It is designed to perform the J-PAS, a BAO survey of the northern sky. The J-PAS survey will use 59 filters, 56 narrow-band filters (14.5 nm width) equi-spaced between 350 and 1000 nm plus 3 broad-band filters to achieve unprecedented photometric redshift accuracies for faint galaxies over 8500°² of sky. In this paper, the OAJ first light instrumentation is presented.

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The GALANTE optical photometric survey is observing the northern Galactic plane and some adjacent regions using seven narrow- and intermediate-filters, covering a total of 1618 deg2. The survey has been designed with multiple exposure times and at least two different air masses per field to maximize its photometric dynamic range, comparable to that of Gaia, and ensure the accuracy of its photometric calibration. The goal is to reach at least 1 per cent accuracy and precision in the seven bands for all stars brighter than AB magnitude 17 while detecting fainter stars with lower values of the signal-to-noise ratio. The main purposes of GALANTE are the identification and study of extinguished O+B+WR stars, the derivation of their extinction characteristics, and the cataloguing of F and G stars in the solar neighbourhood. Its data will be also used for a variety of other stellar studies and to generate a high-resolution continuum-free map of the Hα emission in the Galactic plane. We describe the techniques and the pipeline that are being used to process the data, including the basis of an innovative calibration system based on Gaia DR2 and 2MASS photometry.

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In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper we develop a pipeline to compute synthetic photometry of quasars, galaxies and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey. To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 ≤ r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modeling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.

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The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS; see Benítez et al. 2014) and the Javalambre-Photometric Local Universe Survey (J-PLUS) will be conducted at the brand-new Observatorio Astrofísico de Javalambre (OAJ) in Teruel, Spain. J-PLUS is planned to start by the first half of 2015 while J-PAS first light is expected to happen along 2015. Besides the two main telescopes (with 2.5 m and 80 cm apertures), several smaller-sized facilities are present at the OAJ devoted to site characterization and supporting measurements to be used to calibrate the J-PAS and J-PLUS photometry and to feed up the OAJ's Sequencer with the integrated seeing and the sky transparency. These instruments are: i) an extinction monitor, an 11 " telescope estimating the atmospheric extinction to finally obtain the OAJ extinction curve, which is the initial step to J-PAS overall photometric calibration procedure; ii) an 8 " telescope implementing the Differential Image Motion Monitor (DIMM) technique to obtain the integrated seeing; and iii) an All-Sky Transmission MONitor (ASTMON), a roughly all-sky instrument providing the sky transparency as well as sky brightness and the atmospheric extinction too.

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The Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is an unprecedented photometric sky survey of 8,500 deg^2 visible from the Observatorio Astrofísico de Javalambre (OAJ) in 59 colors, using a set of broad, intermediate and narrow band filters. J-PAS is going to provide the first complete 3D map of a large volume of the Universe and will contribute on many astrophysical science cases, from Solar System minor bodies to Cosmology. The survey will be conducted by the Javalambre Survey Telescope, JST/T250, with Javalambre Panoramic Camera (JPCam), which is currently in its engineering phase. Until then, the interim JPAS-Pathfinder camera, mounting a single CCD covering the center of the FoV, is installed at the telescope. Its filter wheel is ready to host the J-PAS filters already available for use on sky. This is permitting the commissioning of the equipment and is providing the first scientific data: the mini J-PAS. The up-to-date JPAS-Pathfinder commissioning and the results of the science operation is summarized here.

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Context. In modern astronomy, machine learning has proved to be efficient and effective to mine the big data from the newest telescopes. Spectral surveys enable us to characterize millions of objects, while long exposure time observations and wide surveys constrain their strides from millions to billions. Aims. In this study, we construct a supervised machine learning algorithm, to classify the objects in the Javalambre Photometric Local Universe Survey first data release (J-PLUS DR1). Methods. The sample set is featured with 12-waveband photometry, and magnitudes are labeled with spectrum-based catalogs, including Sloan Digital Sky Survey spectroscopic data, Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and VERONCAT - Veron Catalog of Quasars & AGN. The performance of the classifier is presented with applications of blind test validations based on RAdial Velocity Extension, Kepler Input Catalog, 2 MASS Redshift Survey, and the UV-bright Quasar Survey. A new algorithm is applied to constrain the extrapolation that could decrease accuracies for many machine learning classifiers. Results. The accuracies of the classifier are 96.5% in blind test and 97.0% in training cross validation. The F1-scores for each class are presented to show the precision of the classifier. We also discuss different methods to constrain the potential extrapolation.

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Context. Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. Aims: The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. Methods: The training data for the parameters regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. Results: We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods. Table with the sample of stars and derived parameters is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/664/A38

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Understanding the origins of small-scale flats of CCDs and their wavelength-dependent variations plays an important role in high-precision photometric, astrometric, and shape measurements of astronomical objects. Based on the unique flat data of 47 narrow-band filters provided by JPAS-{\it Pathfinder}, we analyze the variations of small-scale flats as a function of wavelength. We find moderate variations (from about 1.0%1.0% at 390 nm to 0.3%0.3% at 890 nm) of small-scale flats among different filters, increasing towards shorter wavelengths. Small-scale flats of two filters close in central wavelengths are strongly correlated. We then use a simple physical model to reproduce the observed variations to a precision of about ±0.14%±0.14% , by considering the variations of charge collection efficiencies, effective areas and thicknesses between CCD pixels. We find that the wavelength-dependent variations of small-scale flats of the JPAS-{\it Pathfinder} camera originate from inhomogeneities of the quantum efficiency (particularly charge collection efficiency) as well as the effective area and thickness of CCD pixels. The former dominates the variations in short wavelengths while the latter two dominate at longer wavelengths. The effects on proper flat-fielding as well as on photometric/flux calibrations for photometric/slit-less spectroscopic surveys are discussed, particularly in blue filters/wavelengths. We also find that different model parameters are sensitive to flats of different wavelengths, depending on the relations between the electron absorption depth, the photon absorption length and the CCD thickness. In order to model the wavelength-dependent variations of small-scale flats, a small number (around ten) of small-scale flats with well-selected wavelengths are sufficient to reconstruct small-scale flats in other wavelengths.

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Understanding the origins of small-scale flats of CCDs and their wavelength-dependent variations plays an important role in high-precision photometric, astrometric, and shape measurements of astronomical objects. Based on the unique flat data of 47 narrowband filters provided by JPAS-Pathfinder, we analyze the variations of small-scale flats as a function of wavelength. We find moderate variations (from about 1.0% at 390 nm to 0.3% at 890 nm) of small-scale flats among different filters, increasing toward shorter wavelengths. Small-scale flats of two filters close in central wavelengths are strongly correlated. We then use a simple physical model to reproduce the observed variations to a precision of about ±0.14% by considering the variations of charge collection efficiencies, effective areas, and thicknesses between CCD pixels. We find that the wavelength-dependent variations of the small-scale flats of the JPAS-Pathfinder camera originate from inhomogeneities of the quantum efficiency (particularly charge collection efficiency), as well as the effective area and thickness of CCD pixels. The former dominates the variations in short wavelengths, while the latter two dominate at longer wavelengths. The effects on proper flat-fielding, as well as on photometric/flux calibrations for photometric/slitless spectroscopic surveys, are discussed, particularly in blue filters/wavelengths. We also find that different model parameters are sensitive to flats of different wavelengths, depending on the relations between the electron absorption depth, photon absorption length, and CCD thickness. In order to model the wavelength-dependent variations of small-scale flats, a small number (around 10) of small-scale flats with well-selected wavelengths are sufficient to reconstruct small-scale flats in other wavelengths.

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The Observatorio Astrofísico de Javalambre (OAJ) is a new astronomical facility located at the Sierra de Javalambre (Teruel, Spain) whose primary role will be to conduct all-sky astronomical surveys with two unprecedented telescopes of unusually large fields of view: the JST/T250, a 2.55m telescope of 3deg field of view, and the JAST/T80, an 83cm telescope of 2deg field of view. CEFCA engineering team has been designing the OAJ control system as a global concept to manage, monitor, control and maintain all the observatory systems including not only astronomical subsystems but also infrastructure and other facilities. In order to provide quality, reliability and efficiency, the OAJ control system (OCS) design is based on CIA (Control Integrated Architecture) and OEE (Overall Equipment Effectiveness) as a key to improve day and night operation processes. The OCS goes from low level hardware layer including IOs connected directly to sensors and actuators deployed around the whole observatory systems, including telescopes and astronomical instrumentation, up to the high level software layer as a tool to perform efficiently observatory operations. We will give an overview of the OAJ control system design and implementation from an engineering point of view, giving details of the design criteria, technology, architecture, standards, functional blocks, model structure, development, deployment, goals, report about the actual status and next steps.

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The Observatorio Astrofísico de Javalambre (OAJ) is a new astronomical facility located at the Sierra de Javalambre (Teruel, Spain) whose primary role will be to conduct all-sky astronomical surveys with two unprecedented telescopes of unusually large fields of view: the JST/T250, a 2.55 m telescope of 3 deg field of view, and the JAST/T80, an 83 cm telescope of 2 deg field of view. CEFCA engineering team has been designing the OAJ control system as a global concept to manage, monitor, control and maintain all the observatory systems including not only astronomical subsystems but also infrastructure and other facilities. Three main factors have been considered in the design of a global control system for the robotic OAJ: quality, reliability and efficiency. We propose CIA (Control Integrated Architecture) design and OEE (Overall Equipment Effectiveness) as a key performance indicator in order to improve operation processes, minimizing resources and obtain high cost reduction maintaining quality requirements. Here we present the OAJ robotic control strategy to achieve maximum quality efficiency for the observatory surveys, processes and operations, giving practical examples of our approach.

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The Observatorio Astrofísico de Javalambre in Spain is a new astronomical facility particularly conceived for carrying out large sky surveys with two unprecedented telescopes of unusually large fields of view: the JST/T250, a 2.55m telescope of 3deg field of view, and the JAST/T80, an 83cm telescope of 2deg field of view. The most immediate objective of the two telescopes for the next years is carrying out two unique photometric surveys of several thousands square degrees, J-PAS[9][14][16] and J-PLUS [14][16], each of them with a wide range of scientific applications, like e.g. large structure cosmology and Dark Energy, galaxy evolution, supernovae, Milky Way structure, exoplanets, among many others. To do that, JST and JAST will be equipped with panoramic cameras under development within the J-PAS collaboration, JPCam and T80Cam respectively, which make use of large format (~ 10k x 10k) CCDs covering the entire focal plane. This paper describes in detail the engineering development of the overall facilities and infrastructures for the robotic observatory and a global overview of current status and future actions to perform from engineering point of view.

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There are many ways to solve the challenging problem of making a high performance robotic observatory from scratch. The Observatorio Astrofísico de Javalambre (OAJ) is a new astronomical facility located in the Sierra de Javalambre (Teruel, Spain) whose primary role will be to conduct all-sky astronomical surveys. The OAJ control system has been designed from a global point of view including astronomical subsystems as well as infrastructures and other facilities. Three main factors have been considered in the design of a global control system for the robotic OAJ: quality, reliability and efficiency. We propose CIA (Control Integrated Architecture) design and OEE (Overall Equipment Effectiveness) as a key performance indicator in order to improve operation processes, minimizing resources and obtaining high cost reduction whilst maintaining quality requirements. The OAJ subsystems considered for the control integrated architecture are the following: two wide-field telescopes and their instrumentation, active optics subsystems, facilities for sky quality monitoring (seeing, extinction, sky background, sky brightness, cloud distribution, meteorological station), domes and several infrastructure facilities such as water supply, glycol water, water treatment plant, air conditioning, compressed air, LN2 plant, illumination, surveillance, access control, fire suppression, electrical generators, electrical distribution, electrical consumption, communication network, Uninterruptible Power Supply and two main control rooms, one at the OAJ and the other remotely located in Teruel, 40km from the observatory, connected through a microwave radio-link. This paper presents the OAJ strategy in control design to achieve maximum quality efficiency for the observatory processes and operations, giving practical examples of our approach.

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The Observatorio Astrofísico de Javalambre is a fully automated astronomical observatory particularly conceived for carrying out large sky surveys with two unprecedented telescopes of unusually large fields of view: the JST/T250, a 2.55m telescope of 3deg field of view, and the JAST/T80, an 83cm telescope of 2deg field of view. The most immediate objective of the two telescopes for the next years is carrying out two unique photometric surveys of several thousands square degrees, Javalambre Phtometry of the Accelerating universe Survey (J-PAS) and Javalambre Photometry of the Local Universe Survey (J-PLUS), each of them with a wide range of scientific applications, like e.g. large structure cosmology and dark energy, galaxy evolution, supernovae, Milky Way structure, among others. To do that, JST and JAST will be equipped with panoramic cameras under development within the J-PAS collaboration, JPCam and T80Cam respectively, which make use of large format ( 10k x 10k) CCDs covering the entire focal plane. This paper describes in detail, from operations point of view, the engineering development of the overall facilities and infrastructures for the robotic observatory and a global overview of current status pinpointing lessons learned in order to boost observatory operations performance achieving scientific targets, maintaining quality requirements but also minimizing resources, material and human resources. We also briefly introduce the Early Data Release (EDR) of J-PLUS, which is already freely accessible worldwide, and the first scientific papers. Finally, we show the next steps necessary for JST to perform the J-PAS project.

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The Observatorio Astrofísico de Javalambre (OAJ†1 ) in Spain is a young astronomical facility, conceived and developed from the beginning as a fully automated observatory with the main goal of optimizing the processes in the scientific and general operation of the Observatory. The OAJ has been particularly conceived for carrying out large sky surveys with two unprecedented telescopes of unusually large fields of view (FoV): the JST/T250, a 2.55m telescope of 3deg field of view, and the JAST/T80, an 83cm telescope of 2deg field of view. The most immediate objective of the two telescopes for the next years is carrying out two unique photometric surveys of several thousands square degrees, J-PAS†2 and J-PLUS†3 , each of them with a wide range of scientific applications, like e.g. large structure cosmology and Dark Energy, galaxy evolution, supernovae, Milky Way structure, exoplanets, among many others. To do that, JST and JAST are equipped with panoramic cameras under development within the J-PAS collaboration, JPCam and T80Cam respectively, which make use of large format (~ 10k x 10k) CCDs covering the entire focal plane. This paper describes in detail, from operations point of view, a comparison between the detailed cost of the global automation of the Observatory and the standard automation cost for astronomical facilities, in reference to the total investment and highlighting all benefits obtained from this approach and difficulties encountered. The paper also describes the engineering development of the overall facilities and infrastructures for the fully automated observatory and a global overview of current status, pinpointing lessons learned in order to boost observatory operations performance, achieving scientific targets, maintaining quality requirements, but also minimizing operation cost and human resources.

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