We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg 2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg 2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r∼27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.

We present the first public version (v0.2) of the open-source and community-developed Python package, Astropy. This package provides core astronomy-related functionality to the community, including support for domain-specific file formats such as flexible image transport system (FITS) files, Virtual Observatory (VO) tables, and common ASCII table formats, unit and physical quantity conversions, physical constants specific to astronomy, celestial coordinate and time transformations, world coordinate system (WCS) support, generalized containers for representing gridded as well as tabular data, and a framework for cosmological transformations and conversions. Significant functionality is under active development, such as a model fitting framework, VO client and server tools, and aperture and point spread function (PSF) photometry tools. The core development team is actively making additions and enhancements to the current code base, and we encourage anyone interested to participate in the development of future Astropy versions.

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey telescopes. MOPS achieves > 99.5% efficiency in producing orbits from a synthetic but realistic population of asteroids whose measurements were simulated for a Pan-STARRS4-class telescope. Additionally, using a non-physical grid population, we demonstrate that MOPS can detect populations of currently unknown objects such as interstellar asteroids. MOPS has been adapted successfully to the prototype Pan-STARRS1 telescope despite differences in expected false detection rates, fill-factor loss and relatively sparse observing cadence compared to a hypothetical Pan-STARRS4 telescope and survey. MOPS remains >99.5% efficient at detecting objects on a single night but drops to 80% efficiency at producing orbits for objects detected on multiple nights. This loss is primarily due to configurable MOPS processing limits that are not yet tuned for the Pan-STARRS1 mission. The core MOPS software package is the product of more than 15 person-years of software development and incorporates countless additional years of effort in third-party software to perform lower-level functions such as spatial searching or orbit determination. We describe the high-level design of MOPS and essential subcomponents, the suitability of MOPS for other survey programs, and suggest a road map for future MOPS development.Comment: 57 Pages, 26 Figures, 13 Table

Context. NIKA2 is a dual-band millimetre continuum camera of 2 900 kinetic inductance detectors, operating at 150 and 260 GHz, installed at the IRAM 30-m telescope in Spain. Open to the scientific community since October 2017, NIKA2 will provide key observations for the next decade to address a wide range of open questions in astrophysics and cosmology. Aims. Our aim is to present the calibration method and the performance assessment of NIKA2 after one year of observation. Methods. We used a large data set acquired between January 2017 and February 2018 including observations of primary and secondary calibrators and faint sources that span the whole range of observing elevations and atmospheric conditions encountered by the IRAM 30-m telescope. This allowed us to test the stability of the performance parameters against time evolution and observing conditions. We describe a standard calibration method, referred to as the “Baseline” method, to translate raw data into flux density measurements. This includes the determination of the detector positions in the sky, the selection of the detectors, the measurement of the beam pattern, the estimation of the atmospheric opacity, the calibration of absolute flux density scale, the flat fielding, and the photometry. We assessed the robustness of the performance results using the Baseline method against systematic effects by comparing results using alternative methods. Results. We report an instantaneous field of view of 6.5′ in diameter, filled with an average fraction of 84%, and 90% of valid detectors at 150 and 260 GHz, respectively. The beam pattern is characterised by a FWHM of 17.6″ ± 0.1″ and 11.1″ ± 0.2″, and a main-beam efficiency of 47%±3%, and 64%±3% at 150 and 260 GHz, respectively. The point-source rms calibration uncertainties are about 3% at 150 GHz and 6% at 260 GHz. This demonstrates the accuracy of the methods that we deployed to correct for atmospheric attenuation. The absolute calibration uncertainties are of 5%, and the systematic calibration uncertainties evaluated at the IRAM 30-m reference Winter observing conditions are below 1% in both channels. The noise equivalent flux density at 150 and 260 GHz are of 9 ± 1 mJy s1/2 and 30 ± 3 mJy s1/2. This state-of-the-art performance confers NIKA2 with mapping speeds of 1388 ± 174 and 111 ± 11 arcmin2 mJy−2 h−1 at 150 and 260 GHz. Conclusions. With these unique capabilities of fast dual-band mapping at high (better that 18″) angular resolution, NIKA2 is providing an unprecedented view of the millimetre Universe.

Abstract. The Garching-Bonn Deep Survey (GaBoDS) is a virtual 12 square degree cosmic shear and cluster lensing survey, conducted with the WFI@2.2 m MPG/ESO telescope at La Silla. It consists of shallow, medium and deep random fields taken in R-band in subarcsecond seeing conditions at high galactic latitude. A substantial amount of the data was taken from the ESO archive, by means of a dedicated ASTROVIRTEL program. In the present work we describe the main characteristics and scientific goals of GaBoDS. Our strategy for mining the ESO data archive is introduced, and we comment on the Wide Field Imager data reduction as well. In the second half of the paper we report on clusters of galaxies found in the background of NGC 300, a random archival field. We use weak gravitational lensing and the red cluster sequence method for the selection of these objects. Two of the clusters found were previously known and already confirmed by spectroscopy. Based on the available data we show that there is significant evidence for substructure in one of the clusters, and an increasing fraction of blue galaxies towards larger cluster radii. Two other mass peaks detected by our weak lensing technique coincide with red clumps of galaxies. We estimate their redshifts and masses, and check for possible X-ray counterparts in deep XMM observations.