AAVSO Photometric All-Sky Survey (APASS), underway since 2010,
covers the entire sky from 7.5 < V < 16.5 magnitude, and in the BVugrizY
bandpasses. A northern and a southern site are used, each with twin ASA
20cm astrographs and Apogee Aspen CG16m cameras, covering 2.9x2.9 square
degrees with 2.6arcsec pixels. Landolt and SDSS standards are used for
all-sky solutions, with typical 0.02mag calibration errors on the bright
end.
Data Release 10 is a complete reprocessing of all 500K images taken with
the system, including hundreds of nights not part of DR9. Sextractor is
used for star finding and centroiding; DAOPHOT is used for aperture
photometry; the astrometry.net plate-solving library is used for basic
astrometry, supplanted with more precise WCS that utilizes knowledge of the
optical train distortions. With these changes, DR10 includes many more
stars than prior releases.
More information is available at http://www.aavso.org/apass.
This brief tutorial shows you how to quickly add proper motions and
photometry from Gaia to (almost) any object list using the Virtual
Observatory. The VO protocol most suited to this kind of this is TAP
("table access protocol") and lets you transfer data and queries to
database servers. In the example, we will be using TOPCAT as a client.
There is no lock-in to it: There are libraries and other tools
allowing an integration of TAP operations into arbitrary workflows –
that's what standards are about. Tutorial supplements apply the
techniques to Simbad, show how to use TAP from Python, and introduce
UCDs.
This is a course on the Virtual Observatory's main query language
ADQL (short for Astronomical Data Query Language), which is a SQL
dialect standardised so users do not have to learn new languages each
time they want to use a new resource. We also introduce the basic
aspects of the Table Access Protocol TAP, which transports ADQL
queries, their results as well as the metadata necessary to write
meaningful queries.
The course comes with many exercises, most of which also have
solutions. We hope it is suitable for both self-study and as lecture
notes in teacher-led situations.
This is a course on pyVO, an astropy-affiliated Python library
implementing client parts for many protocols in the Virtual
Observatory: Simple discovery protocols like SCS, SIAP, and SSAP as
well as the sophisticated Table Access Protocol TAP, which allows
users to send complex queries to remote tables and retrieve
metadata-rich results. There is also an interface to the VO Registry
to enable data and service discovery.
The course comes with many exercises, most of which also have
solutions. We hope it is suitable for both self-study and as lecture
notes in teacher-led situations.
The VO client Aladin offers powerful facilities of creating an
astrometrical calibration to images lacking WCS (World Coordinate
System) information. This tutorial shows how to go about doing this
for an image of the Ring Nebula in Lyr.
This tutorial uses SPLAT-VO to search the VO registry for spectra of
galaxies and quasars. From the obtained spectra, the Hydrogen Lyman
Alpha line will be used to compute redshift and velocity
Within this intermediate use case you learn about supernovae (see
also the tutorial “Distance to the Crab Nebula“,
ivo://edu.euro-vo.org/tutorials/08_m1_distance) and determine the
celestial coordinates of a just discovered candidate supernova on an
provided image without astrometric calibration. This use case provides
a glimpse of an activity that is representative of the practical tasks
that astronomers have to perform when they analyze data.
Introduction to Simulation Databases - Density Fields and Dark Matter
Halos
Date:
27 Dec 2024 08:31:06
Publisher:
The GAVO DC team
Description:
This tutorial was created for a physics teacher workshop (~ high
school level). It shows how to extract density fields and information
on dark matter halos from the CosmoSim database using SQL queries. It
is optimized for brevity.
Introduction to Simulation Databases Using CosmoSim
Date:
27 Dec 2024 08:31:03
Publisher:
The GAVO DC team
Description:
This tutorial shows how to do first SQL-queries on cosmological
databases, including retrieving mass functions, extracting merger
trees or particles of a specific dark matter halo.