Gaia Photometric Catalogue: the calibration of the DR2 photometry

2018 ◽  
Vol 14 (A30) ◽  
pp. 466-470
Author(s):  
D. W. Evans ◽  
M. Riello ◽  
F. De Angeli ◽  
J. M. Carrasco ◽  
P. Montegriffo ◽  
...  
Keyword(s):  
Scientific Community ◽  
Photometric Data ◽  
Photometric System ◽  
Gaia Dr1 ◽  
System A ◽  
Data Release ◽  
Definition Of ◽  
High Level ◽  
Crucial Part ◽  
Gaia Dr2

AbstractGaia DR2 was released in April 2018 and contains a photometric catalogue of more than 1 billion sources. This release contains colour information in the form of integrated BP and RP photometry in addition to the latest G-band photometry. The level of uncertainty can be as good as 2 mmag with some residual systematics at the 10 mmag level. The addition of colour information greatly enhances the value of the photometric data for the scientific community. A high level overview of the photometric processing, with a focus on the improvements with respect to Gaia DR1, was given. The definition of the Gaia photometric system, a crucial part of the calibration of the photometry, was also explained. Finally, some of the photometric improvements expected for the next data release were described.

Gaia Photometric Data: DR1 results and DR2 expectations

2017 ◽  
Vol 12 (S330) ◽  
pp. 30-34
Author(s):  
Dafydd Wyn Evans ◽  
Marco Riello ◽  
Francesca De Angeli ◽  
Giorgia Busso ◽  
Floor van Leeuwen ◽  
...  
Keyword(s):  
Photometric Data ◽  
The South ◽  
Gaia Dr1 ◽  
Preliminary Validation ◽  
Data Release ◽  
High Level ◽  
Gaia Dr2

AbstractGaia DR1 was released in September 2016 and contained a photometric catalogue of over 1 billion sources. At this stage, this only included mean G-band photometry and an estimate of the error. Even though this may sound limited in nature, interesting science can still be achieved with this data thanks to its quality. A high level overview of the photometric processing and some validation results will be presented. Additionally, epoch photometry in the G-band was released in Gaia DR1 for a small number of variable sources in the South Ecliptic Pole which covers the LMC. The second data release (Gaia DR2) is currently being prepared and, if available, some preliminary validation results will be presented. It is planned that this release will contain colour information in the form of integrated BP and RP photometry in addition to the latest G-band photometry.

The Gaia mission status

2017 ◽  
Vol 12 (S330) ◽  
pp. 7-12
Author(s):  
T. Prusti
Keyword(s):  
Data Processing ◽  
Spectroscopic Measurements ◽  
Gaia Dr1 ◽  
Intermediate Data ◽  
Sky Survey ◽  
Data Release ◽  
Scientists And Engineers ◽  
Gaia Dr2 ◽  
Extension Period ◽  
Operational Time

AbstractGaia is an ESA cornerstone mission conducting a full sky survey over its 5 year operational period. Gaia performs astrometric, photometric and spectroscopic measurements. The data processing is entrusted to scientists and engineers who have formed the Gaia Data Processing and Analysis Consortium (DPAC). The photometric science alerts started in 2014. The first intermediate data release (Gaia DR1) took place 14 September 2016 and it has been extensively used by the community. Gaia DR2 is scheduled for April 2018. Gaia is expected to be able to continue observations roughly for another 5 years after the nominal phase. The procedure to grant funding for the extension period has been initiated. In case funding is granted, the total operational time of Gaia may be 10 years.

scholarly journals The period–luminosity relation of red supergiants with Gaia DR2

2019 ◽  
Vol 487 (4) ◽  
pp. 4832-4846 ◽  
Author(s):  
Filip W Chatys ◽  
Timothy R Bedding ◽  
Simon J Murphy ◽  
László L Kiss ◽  
Dougal Dobie ◽  
...  
Keyword(s):  
Power Spectra ◽  
Large Magellanic Cloud ◽  
Photometric Data ◽  
Computing Power ◽  
Andromeda Galaxy ◽  
Data Release ◽  
Red Supergiants ◽  
Red Giant ◽  
Plate Collection ◽  
Gaia Dr2

Abstract We revisit the K -band period–luminosity (P–L) relations of Galactic red supergiants using Gaia Data Release 2 parallaxes and up to 70 yr of photometry from AAVSO and ASAS campaigns. In addition, we examine 206 LMC red supergiants using 50 yr of photometric data from the digitized Harvard Astronomical Plate Collection. We identified periods by computing power spectra and calculated the period–luminosity relations of our samples and compared them with the literature. Newly available data tighten the P–L relations substantially. Identified periods form two groups: one with periods of 300–1000 d, corresponding to pulsations, and another with Long Secondary Periods between 1000 and 8000 d. Among the 48 Galactic objects we find shorter periods in 25 stars and long secondary periods in 23 stars. In the LMC sample we identify 85 and 94 red supergiants with shorter and long secondary periods, respectively. The P–L relation of the Galactic red supergiants is in agreement with the red supergiants in both, the Large Magellanic Cloud and the Andromeda galaxy. We find no clear continuity between the known red giant period–luminosity sequences, and the red supergiant sequences investigated here.

scholarly journals Gaia Data Release 2

2018 ◽  
Vol 616 ◽  
pp. A3 ◽  
Author(s):  
M. Riello ◽  
F. De Angeli ◽  
D. W. Evans ◽  
G. Busso ◽  
N. C. Hambly ◽  
...  
Keyword(s):  
Processing System ◽  
Photometric System ◽  
Flexible System ◽  
Accuracy And Precision ◽  
Data Release ◽  
Operations And Maintenance ◽  
Ccd Observations ◽  
Data Volume ◽  
Hadoop Platform ◽  
Definition Of

Context. The second Gaia data release is based on 22 months of mission data with an average of 0.9 billion individual CCD observations per day. A data volume of this size and granularity requires a robust and reliable but still flexible system to achieve the demanding accuracy and precision constraints that Gaia is capable of delivering. Aims. We aim to describe the input data, the treatment of blue photometer/red photometer (BP/RP) low-resolution spectra required to produce the integrated GBP and GRP fluxes, the process used to establish the internal Gaia photometric system, and finally, the generation of the mean source photometry from the calibrated epoch data for Gaia DR2. Methods. The internal Gaia photometric system was initialised using an iterative process that is solely based on Gaia data. A set of calibrations was derived for the entire Gaia DR2 baseline and then used to produce the final mean source photometry. The photometric catalogue contains 2.5 billion sources comprised of three different grades depending on the availability of colour information and the procedure used to calibrate them: 1.5 billion gold, 144 million silver, and 0.9 billion bronze. These figures reflect the results of the photometric processing; the content of the data release will be different due to the validation and data quality filters applied during the catalogue preparation. The photometric processing pipeline, PhotPipe, implements all the processing and calibration workflows in terms of Map/Reduce jobs based on the Hadoop platform. This is the first example of a processing system for a large astrophysical survey project to make use of these technologies. Results. The improvements in the generation of the integrated G–band fluxes, in the attitude modelling, in the cross-matching, and and in the identification of spurious detections led to a much cleaner input stream for the photometric processing. This, combined with the improvements in the definition of the internal photometric system and calibration flow, produced high-quality photometry. Hadoop proved to be an excellent platform choice for the implementation of PhotPipe in terms of overall performance, scalability, downtime, and manpower required for operations and maintenance.

scholarly journals White dwarf-open cluster associations based on Gaia DR2

2020 ◽  
Vol 645 ◽  
pp. A13
Author(s):  
M. Prišegen ◽  
M. Piecka ◽  
N. Faltová ◽  
M. Kajan ◽  
E. Paunzen
Keyword(s):  
Open Cluster ◽  
Open Clusters ◽  
Photometric Data ◽  
Mass Relation ◽  
Physical Processes ◽  
Satellite Mission ◽  
Cluster Membership ◽  
Fundamental Parameters ◽  
Data Release ◽  
Gaia Dr2

Context. Fundamental parameters and physical processes leading to the formation of white dwarfs (WDs) may be constrained and refined by discovering WDs in open clusters (OCs). Cluster membership can be utilized to establish the precise distances, luminosities, ages, and progenitor masses of such WDs. Aims. We compile a list of probable WDs that are OC members in order to facilitate WD studies that are impractical or difficult to conduct for Galactic field WDs. Methods. We use recent catalogs of WDs and OCs that are based on the second data release of the Gaia satellite mission (GDR2) to identify WDs that are OC members. This crossmatch is facilitated by the astrometric and photometric data contained in GDR2 and the derived catalogs. Assuming that most of the WD members are of the DA type, we estimate the WD masses, cooling ages, and progenitor masses. Results. We have detected several new likely WD members and reassessed the membership of the literature WDs that had been previously associated with the studied OCs. Several of the recovered WDs fall into the recently reported discontinuity in the initial-final mass relation (IFMR) around Mi ∼ 2.0 M⊙, which allows for tighter constrains on the IFMR in this regime.

Asteroid phase curve parameters from Gaia photometry

2020 ◽  
Author(s):  
Julia Martikainen ◽  
Grigori Fedorets ◽  
Antti Penttilä ◽  
Karri Muinonen
Keyword(s):  
Photometric Data ◽  
Surface Scattering ◽  
Phase Curve ◽  
The Past ◽  
Current State ◽  
Data Release ◽  
Rotation Parameters ◽  
Inversion Techniques ◽  
Gaia Dr2

<p>Asteroids have remained mostly the same for the past 4.5 billion years, and provide us information on the origin, evolution and current state of the Solar System. For the physical characterization of asteroids, one of the best data sources is photometry: the measurement of the disk-integrated brightness of the asteroid.  An asteroid's lightcurve (i.e. the dependency of the brightness as a function of time) is indicative of its surface scattering properties, as well as its shape and the state of spin. <br /><br />In this work, we apply novel Bayesian inverse methods (Muinonen et al., A&A 2020, in revision) to derive phase curve parameters from photometric lightcurve observations. Our aim is to validate and expand the existing analyses by applying the methods to of the order of tens to hundreds of asteroids using photometric data from the Gaia Data Release 2 (Gaia Collaboration, Spoto et al., A&A 616, A13, 2018) and ground-based photometry (Durech et al., A&A 513, A46, 2010) from Database of Asteroid Models from Inversion Techniques (DAMIT). We derive phase curve linear slopes by using four techniques:  1) convex inversion on all data, 2) convex inversion on all data with fixed rotation parameters from DAMIT, 3) ellipsoid inversion on Gaia DR2 data only, and 4) ellipsoid inversion on Gaia DR2 data only with fixed rotation parameters from DAMIT. Finally, we compare the obtained slope parameters with the presumed Bus-DeMeo (DeMeo et al., Icarus 202, 160, 2009) taxonomic classes of the asteroids, and study possible correlations with the geometric albedos. The Gaia photometry has milli-magnitude precision and is thus extremely valuable when used to carry out asteroid taxonomic classification.</p>

scholarly journals Photometric Data in Machine-Readable Form

1973 ◽  
Vol 50 ◽  
pp. 285-287 ◽  
Author(s):  
B. Hauck
Keyword(s):  
Data Center ◽  
Photometric Data ◽  
Second Step ◽  
Photometric System ◽  
System A ◽  
Readable Form ◽  
Machine Readable ◽  
Machine Readable Form ◽  
Standard List

For two years we have undertaken the collection of photoelectric data in view of their utilization by computer techniques. At present we are preparing a fine for each photometric system with the measurements published. As a second step, we shall form another file, alike for each system, with homogeneous measurements. This file will be obtained with weighed means of the published measurements. For that we need to compare each published list with a standard list before attributing the weights.After that, we shall form a file indicating in which system a star is measured.This work is undertaken in connection with the Data Center of Strasbourg and the group on spectroscopic and photometric data of the Commission 45.

scholarly journals Synthetic RGB photometry of bright stars: definition of the standard photometric system and UCM library of spectrophotometric spectra

2021 ◽  
Author(s):  
Nicolás Cardiel ◽  
Jaime Zamorano ◽  
Salvador Bará ◽  
Alejandro Sánchez de Miguel ◽  
Cristina Cabello ◽  
...  
Keyword(s):  
Stellar Atmosphere ◽  
Variable Stars ◽  
Photometric Data ◽  
Color Filter ◽  
Photometric System ◽  
Sensitivity Curves ◽  
Solar System Bodies ◽  
Definition Of ◽  
Celestial Sphere ◽  
Large Telescopes

Abstract Although the use of RGB photometry has exploded in the last decades due to the advent of high-quality and inexpensive digital cameras equipped with Bayer-like color filter systems, there is surprisingly no catalogue of bright stars that can be used for calibration purposes. Since due to their excessive brightness, accurate enough spectrophotometric measurements of bright stars typically cannot be performed with modern large telescopes, we have employed historical 13-color medium-narrow-band photometric data, gathered with quite reliable photomultipliers, to fit the spectrum of 1346 bright stars using stellar atmosphere models. This not only constitutes a useful compilation of bright spectrophotometric standards well spread in the celestial sphere, the UCM library of spectrophotometric spectra, but allows the generation of a catalogue of reference RGB magnitudes, with typical random uncertainties ∼0.01 mag. For that purpose, we have defined a new set of spectral sensitivity curves, computed as the median of 28 sets of empirical sensitivity curves from the literature, that can be used to establish a standard RGB photometric system. Conversions between RGB magnitudes computed with any of these sets of empirical RGB curves and those determined with the new standard photometric system are provided. Even though particular RGB measurements from single cameras are not expected to provide extremely accurate photometric data, the repeatability and multiplicity of observations will allow access to a large amount of exploitable data in many astronomical fields, such as the detailed monitoring of light pollution and its impact on the night sky brightness, or the study of meteors, solar system bodies, variable stars, and transient objects. In addition, the RGB magnitudes presented here make the sky an accessible and free laboratory for the calibration of the cameras themselves.

Europe

2020 ◽  
pp. 649-666
Author(s):  
Andrea Renda
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Policy Framework ◽  
Expert Group ◽  
Ethical Guidelines ◽  
Ethical Implications ◽  
Strong Focus ◽  
Ethics Guidelines ◽  
Definition Of ◽  
High Level

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.

scholarly journals Shape Sensing of a Complex Aeronautical Structure with Inverse Finite Element Method

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1388
Author(s):  
Daniele Oboe ◽  
Luca Colombo ◽  
Claudio Sbarufatti ◽  
Marco Giglio
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Boundary Conditions ◽  
Strain Field ◽  
Element Analysis ◽  
Inverse Finite Element Method ◽  
Shape Sensing ◽  
Definition Of ◽  
High Level ◽  
Element Method

The inverse Finite Element Method (iFEM) is receiving more attention for shape sensing due to its independence from the material properties and the external load. However, a proper definition of the model geometry with its boundary conditions is required, together with the acquisition of the structure’s strain field with optimized sensor networks. The iFEM model definition is not trivial in the case of complex structures, in particular, if sensors are not applied on the whole structure allowing just a partial definition of the input strain field. To overcome this issue, this research proposes a simplified iFEM model in which the geometrical complexity is reduced and boundary conditions are tuned with the superimposition of the effects to behave as the real structure. The procedure is assessed for a complex aeronautical structure, where the reference displacement field is first computed in a numerical framework with input strains coming from a direct finite element analysis, confirming the effectiveness of the iFEM based on a simplified geometry. Finally, the model is fed with experimentally acquired strain measurements and the performance of the method is assessed in presence of a high level of uncertainty.

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