Learning about Galactic structure with Gaia astrometry

The Gaia mission is reviewed together with the expected contents of the final catalogue. It is then argued that the ultimate goal of Galactic structure studies with Gaia astrometry should be to build a dynamical model of our galaxy which is capable of explaining the contents of the Gaia catalogue. This will be possible only by comparing predicted catalogue data to Gaia's actual measurements. To complement this approach the Gaia catalogue should be used to recalibrate photometric distance and abundance indicators across the HR-diagram in order to overcome the lack of precise parallax data at the faint end of the astrometric survey. Using complementary photometric and spectroscopic data from other surveys will be essential in this respect.Comment: Presented at the "Classification and Discovery in Large Astronomical Surveys" meeting, Ringberg Castle, 14-17 October, 200

New approaches to object classification in synoptic sky surveys

Digital synoptic sky surveys pose several new object classification challenges. In surveys where real-time detection and classification of transient events is a science driver, there is a need for an effective elimination of instrument-related artifacts which can masquerade as transient sources in the detection pipeline, e.g., unremoved large cosmic rays, saturation trails, reflections, crosstalk artifacts, etc. We have implemented such an Artifact Filter, using a supervised neural network, for the real-time processing pipeline in the Palomar-Quest (PQ) survey. After the training phase, for each object it takes as input a set of measured morphological parameters and returns the probability of it being a real object. Despite the relatively low number of training cases for many kinds of artifacts, the overall artifact classification rate is around 90%, with no genuine transients misclassified during our real-time scans. Another question is how to assign an optimal star-galaxy classification in a multi-pass survey, where seeing and other conditions change between different epochs, potentially producing inconsistent classifications for the same object. We have implemented a star/galaxy multipass classifier that makes use of external and a priori knowledge to find the optimal classification from the individually derived ones. Both these techniques can be applied to other, similar surveys and data sets

Towards real-time classification of astronomical transients

Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are needed; for short-lived phenomena, a rapid response is essential. Ability to automatically classify and prioritize transient events for follow-up studies becomes critical as the data rates increase. We have been developing such methods using the data streams from the Palomar-Quest survey, the Catalina Sky Survey and others, using the VOEventNet framework. The goal is to automatically classify transient events, using the new measurements, combined with archival data (previous and multi-wavelength measurements), and contextual information (e.g., Galactic or ecliptic latitude, presence of a possible host galaxy nearby, etc.); and to iterate them dynamically as the follow-up data come in (e.g., light curves or colors). We have been investigating Bayesian methodologies for classification, as well as discriminated follow-up to optimize the use of available resources, including Naive Bayesian approach, and the non-parametric Gaussian process regression. We will also be deploying variants of the traditional machine learning techniques such as Neural Nets and Support Vector Machines on datasets of reliably classified transients as they build up

Weather on the Nearest Brown Dwarfs: Resolved Simultaneous Multi-Wavelength Variability Monitoring of WISE J104915.57-531906.1AB

We present two epochs of MPG/ESO 2.2m GROND simultaneous 6-band ($r'i'z'JHK$) photometric monitoring of the closest known L/T transition brown dwarf binary WISE J104915.57-531906.1AB. We report here the first resolved variability monitoring of both the T0.5 and L7.5 components. We obtained 4 hours of focused observations on the night of UT 2013-04-22, as well as 4 hours of defocused (unresolved) observations on the night of UT 2013-04-16. We note a number of robust trends in our light curves. The $r'$ and $i'$ light curves appear to be anticorrelated with $z'$ and $H$ for the T0.5 component and in the unresolved lightcurve. In the defocused dataset, $J$ appears correlated with $z'$ and $H$ and anticorrelated with $r'$ and $i'$, while in the focused dataset we measure no variability for $J$ at the level of our photometric precision, likely due to evolving weather phenomena. In our focused T0.5 component lightcurve, the $K$ band lightcurve displays a significant phase offset relative to both $H$ and $z'$. We argue that the measured phase offsets are correlated with atmospheric pressure probed at each band, as estimated from 1D atmospheric models. We also report low-amplitude variability in $i'$ and $z'$ intrinsic to the L7.5 component.Comment: 14 pages, 5 figures, accepted to ApJ Letter

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS

The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg$^2$ region about 1000 times during the anticipated 10 years of operations (distributed over six bands, $ugrizy$). Each 30-second long visit will deliver 5$\sigma$ depth for point sources of $r\sim24.5$ on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be 1) rapid and robust classification of sources detected in difference images, and 2) {\it simultaneous} treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects.Comment: Presented at the "Classification and Discovery in Large Astronomical Surveys" meeting, Ringberg Castle, 14-17 October, 200

Two Stellar Components in the Halo of the Milky Way

The halo of the Milky Way provides unique elemental abundance and kinematic information on the first objects to form in the Universe, which can be used to tightly constrain models of galaxy formation and evolution. Although the halo was once considered a single component, evidence for its dichotomy has slowly emerged in recent years from inspection of small samples of halo objects. Here we show that the halo is indeed clearly divisible into two broadly overlapping structural components -- an inner and an outer halo -- that exhibit different spatial density profiles, stellar orbits and stellar metallicities (abundances of elements heavier than helium). The inner halo has a modest net prograde rotation, whereas the outer halo exhibits a net retrograde rotation and a peak metallicity one-third that of the inner halo. These properties indicate that the individual halo components probably formed in fundamentally different ways, through successive dissipational (inner) and dissipationless (outer) mergers and tidal disruption of proto-Galactic clumps.Comment: Two stand-alone files in manuscript, concatenated together. The first is for the main paper, the second for supplementary information. The version is consistent with the version published in Natur

Gaia Data Release 2: using Gaia parallaxes

Context. The second Gaia.data release (Gaia DR2 ) provides precise five-parameter astrometric data (positions, proper motions and parallaxes) for an unprecendented amount of sources (more than 1.3 billion, mostly stars). This new wealth of data will enable the undertaking of statistical analyses of many astrophysical problems that were previously unfeasible for lack of reliable astrometry, and in particular because of the lack of parallaxes. But the use of this wealth of astrometric data comes with a specific challenge: how does one properly infer from these data the astrophysical parameters of interest? Aims. The main - but not only - focus of this paper is the issue of the estimation of distances from parallaxes, possibly combined with other information. We start with a critical review of the methods traditionally used to obtain distances from parallaxes and their shortcomings. Then we provide guidelines on how to use parallaxes more efficiently to estimate distances by using Bayesian methods. In particular also we show that negative parallaxes, or parallaxes with relatively larger uncertainties still contain valuable information. Finally, we provide examples that show more generally how to use astrometric data for parameter estimation, including the combination of proper motions and parallaxes and the handling of covariances in the uncertainties. Methods. The paper contains examples based on simulated Gaia data to illustrate the problems and the solutions proposed. Furthermore, the developments and methods proposed in the paper are linked to a set of tutorials included in the Gaia archive documentation that provide practical examples and a good starting point for the application of the recommendations to actual problems. In all cases the source code for the analysis methods is provided. Results. Our main recommendation is to always treat the derivation of (astro-) physical parameters from astrometric data, in particular when parallaxes are involved, as an inference problem which should preferably be handled with a full Bayesian approach. Conclusions. Gaia will provide fundamental data for many fields of astronomy. Further data releases will provide more and more precise data. Nevertheless, for full use of the potential it will always be necessary to pay careful attention to the statistical treatment of parallaxes and proper motions. The purpose of this paper is to help astronomers finding the correct approach

The Fifth Data Release of the Sloan Digital Sky Survey

This paper describes the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). DR5 includes all survey quality data taken through June 2005 and represents the completion of the SDSS-I project (whose successor, SDSS-II will continue through mid-2008). It includes five-band photometric data for 217 million objects selected over 8000 square degrees, and 1,048,960 spectra of galaxies, quasars, and stars selected from 5713 square degrees of that imaging data. These numbers represent a roughly 20% increment over those of the Fourth Data Release; all the data from previous data releases are included in the present release. In addition to "standard" SDSS observations, DR5 includes repeat scans of the southern equatorial stripe, imaging scans across M31 and the core of the Perseus cluster of galaxies, and the first spectroscopic data from SEGUE, a survey to explore the kinematics and chemical evolution of the Galaxy. The catalog database incorporates several new features, including photometric redshifts of galaxies, tables of matched objects in overlap regions of the imaging survey, and tools that allow precise computations of survey geometry for statistical investigations.Comment: ApJ Supp, in press, October 2007. This paper describes DR5. The SDSS Sixth Data Release (DR6) is now public, available from http://www.sdss.or

Understanding the implementation and effectiveness of a group-based early parenting intervention : a process evaluation protocol

BACKGROUND: Group-based early parenting interventions delivered through community-based services may be a potentially effective means of promoting infant and family health and wellbeing. Process evaluations of these complex interventions provide vital information on how they work, as well as the conditions which shape and influence outcomes. This information is critical to decision makers and service providers who wish to embed prevention and early interventions in usual care settings. In this paper, a process evaluation protocol for an early years parenting intervention, the Parent and Infant (PIN) program, is described. This program combines a range of developmentally-appropriate supports, delivered in a single intervention process, for parents and infants (0–2 years) and aimed at enhancing parental competence, strengthening parent-infant relationships and improving infant wellbeing and adjustment. METHODS: The process evaluation is embedded within a controlled trial and accompanying cost-effectiveness evaluation. Building from extant frameworks and evaluation methods, this paper presents a systematic approach to the process evaluation of the PIN program and its underlying change principles, the implementation of the program, the context of implementation and the change mechanisms which influence and shape parent and infant outcomes. We will use a multi-method strategy, including semi-structured interviews and group discussions with key stakeholders, documentary analysis and survey methodology. DISCUSSION: The integration of innovations into existing early years systems and services is a challenging multifaceted undertaking. This process evaluation will make an important contribution to knowledge about the implementation of such programs, while also providing an example of how theory-based research can be embedded within the evaluation of community-based interventions. We discuss the strengths of the research, such as the adoption of a collaborative approach to data collection, while we also identify potential challenges, including capturing and assessing complex aspects of the intervention. TRIAL REGISTRATION: ISRCTN17488830 (Date of registration: 27/11/15). This trial was retrospectively registered. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-016-1737-3) contains supplementary material, which is available to authorized users