Suchergebnisse

A database containing star measurements from the period 2006–2009 taken by the Pi of the Sky detector located in Las Campanas Observatory in Chile contains more than 2 billion measurements of almost 17 million objects. All measurements are available on the Pi of the Sky web site through a dedicated interface, which also allows users to download selected data. Accurate analysis of Pi of the Sky data is a real challenge, because of a number of factors that can influence the measurements. Possible sources of errors in our measurements include: reading the chip with the shutter open, strong and varying sky background, passing planets or planetoids, and clouds and hot pixels. In order tofacilitate the analysis of variable stars we have developed a system of dedicated filters to remove bad measurements or frames. The spectral sensitivity of the detector is taken into account by appropriate corrections based on the spectral type of reference stars. This process is illustrated by an analysis of the BG Ind system, where we have been able to reduce the systematic uncertainty to about 0.05 magnitudo.

Context. Studies of galaxy pairs can provide valuable information to jointly understand the formation and evolution of galaxies and galaxy groups. Consequently, taking the new high-precision photo-z surveys into account, it is important to have reliable and tested methods that allow us to properly identify these systems and estimate their total masses and other properties. Aims. In view of the forthcoming Physics of the Accelerating Universe Survey (PAUS), we propose and evaluate the performance of an identification algorithm of projected close isolated galaxy pairs. We expect that the photometrically selected systems can adequately reproduce the observational properties and the inferred lensing mass-luminosity relation of a pair of truly bound galaxies that are hosted by the same dark matter halo. Methods. We developed an identification algorithm that considers the projected distance between the galaxies, the projected velocity difference, and an isolation criterion in order to restrict the sample to isolated systems. We applied our identification algorithm using a mock galaxy catalog that mimics the features of PAUS. To evaluate the feasibility of our pair finder, we compared the identified photometric samples with a test sample that considers that both members are included in the same halo. Taking advantage of the lensing properties provided by the mock catalog, we also applied a weak-lensing analysis to determine the mass of the selected systems. Results. Photometrically selected samples tend to show high purity values, but tend to misidentify truly bounded pairs as the photometric redshift errors increase. Nevertheless, overall properties such as the luminosity and mass distributions are successfully reproduced. We also accurately reproduce the lensing mass-luminosity relation as expected for galaxy pairs located in the same halo. ; This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie grant agreement No 734374. This work has been supported by MINECO grants AYA2015-71825 & ESP2015-66861. IEEC is partially funded by the CERCA program of the Generalitat de Catalunya. This work was also partially supported by Agencia Nacional de Promoción Científica y Tecnoóogica (PICT 2015-3098), the Con-sejo Nacional de Investigaciones Científicas y Técnicas (CONICET, Argentina) and the Secretaría de Ciencia y Tecnología de la Universidad Nacional de Córdoba (SeCyT-UNC, Argentina). MS has been supported by the European Union's Horizon 2020 research and innovation programme under the Maria Skłodowska-Curie grant agreement No 754510 and National Science Centre (grant UMO-2016/23/N/ST9/02963). MM acknowledges support from the Beat-riu de Pinos fellowship (2017-BP-00114).

Pi of the Sky is a system of robotic telescopes designed for observations of short timescale astrophysical phenomena, e.g. prompt optical GRB emissions. The apparatus is designed to monitor a large fraction of the sky with 12–13 m range and time resolution of the order of 1–10 seconds. In October 2010 the first unit of the new Pi of the Sky detector system was successfully installed in the INTA El Arenosillo Test Centre in Spain. We also moved our prototype detector from Las Campanas Observatory to San Pedro de Atacama Observatory in March 2011. The status and performance of both detectors is presented.

In any imaging survey, measuring accurately the astronomical background light is crucial to obtain good photometry. This paper introduces BKGNET, a deep neural network to predict the background and its associated error. BKGNET has been developed for data from the Physics of the Accelerating Universe Survey (PAUS), an imaging survey using a 40 narrow-band filter camera (PAUCam). The images obtained with PAUCam are affected by scattered light: an optical effect consisting of light multiply reflected that deposits energy in specific detector regions affecting the science measurements. Fortunately, scattered light is not a random effect, but it can be predicted and corrected for. We have found that BKGNET background predictions are very robust to distorting effects, while still being statistically accurate. On average, the use of BKGnet improves the photometric flux measurements by 7 per cent and up to 20 per cent at the bright end. BKGNET also removes a systematic trend in the background error estimation with magnitude in the i band that is present with the current PAU data management method. With BKGNET, we reduce the photometric redshift outlier rate by 35 per cent for the best 20 per cent galaxies selected with a photometric quality parameter. ; Funding for PAUS has been provided by Durham University (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512) and University College London. The PAUS participants from Spanish institutions are partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV-2016-0588, SEV-2016-0597, and MDM-2015-0509, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA program of the Generalitat de Catalunya. The PAU data center is hosted by the Port d'Informacio Cientifica (PIC), maintained through a collaboration of CIEMAT and IFAE, with additional support from Universitat Autonoma de Barcelona and ERDF. CosmoHub has been developed by PIC and was partially funded by the 'Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion program of the Spanish government. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPU used for this research. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 776247. AA is supported by a Royal Society Wolfson Fellowship. MS has been supported by the National Science Centre (grant UMO2016/23/N/ST9/02963). ; Peer reviewed