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Aladin Desktop
==================================
The tutorial focuses on some basic strategies for working with
gravitational-wave sky localizations in the context of electromagnetic
follow-up activities. Here we propose the usage of `Aladin
Desktop <https://aladin.u-strasbg.fr/java/nph-aladin.pl?frame=downloading>`__.
The following main topics are addressed.
1. Sky map visualizations and credible regions.
2. Access to existing catalogs.
3. Filtering and thumbnail view generator
MOC and GW sky localizations
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The contours of a GW sky localization, which enclose a given percentage
of the total probability, are constructed using a *water-filling*
algorithm: the pixels from most probable to least are ranked, and summed
up to get a fixed level of probability \ `[1] <#cite-singer16a>`__. The
enclosed area within a given probability level contour of a GW sky map
can be effectively described through the Multi-Order Coverage (MOC)
method \ `[2] <#cite-fernique15>`__. It is a standard of the Virtual
Observatory which provides a multi-scale mapping based on HEALPix sky
tessellation. Basically, the algorithm maps irregular and complex sky
regions into hierarchically grouped predefined cells. Each MOC cell is
defined by two numbers: the hierarchy level (HEALPIX ORDER) and the
pixel index (HEALPIX NPIX).The NUNIQ scheme defines an algorithm for
packing an (ORDER, NPIX) pair into a single integer for compactness.
MOCs are serialized as ``FITS`` or ``JSON`` files. The MOC resolution is
determined by the map resolution parameter :math:`N_{side}`, which is
used for defining the resolution of the grid. For a typical
:math:`N_{side}` = 512, the MOC order resolution is :math:`order` = 9;
(:math:`N_{side}` = 2\ :math:`^{order}`). The MOC maps make database
queries for retrieving objects and logical operation (such as union,
intersection, subtraction, difference) extremely simple and fast even
for very complex sky regions. If databases are adapted to support MOC
based queries, such as
`VizieR <http://vizier.u-strasbg.fr/viz-bin/VizieR>`__, they offer a
useful method allowing any support of sky region query.
1. Running Aladin Desktop
-------------------------
`Aladin
Desktop <https://aladin.u-strasbg.fr/java/nph-aladin.pl?frame=downloading>`__
is developed in Java. As any Java tool, Aladin Desktop requires a `Java
Virtual Machine <https://www.java.com/en/>`__ on your machine. Download
the ``Aladin.jar`` file from
`here <https://aladin.u-strasbg.fr/java/Aladin.jar>`__ and execute it
from a terminal by typing
::
$ java -Xmx2g -jar Aladin.jar
The flag ``-Xmx< ammount of memory >`` specifies the maximum memory
allocation pool for a Java Virtual Machine (JVM). Here 2GB of memory is
allocated. For GW sky localizations with ``NSIDE = 2048``, increase the
memory allocated up to 3GB, ``-Xmx3g``.
2. Loading a GW sky localization
--------------------------------
You can *copy&paste* the sky map location from the
`GraceDB <https://gracedb.ligo.org/>`__ or drag the local file in the
main Aladin window. Aladin recognizes only the standard HEALPix format
with the file extension **.fits.gz**. Here we will work with the
`LALinference sky map of
GW170817 <https://dcc.ligo.org/public/0157/P1800381/006/GW170817_skymap.fits.gz>`__.
3. Building a Credible Region
-----------------------------
The sequence of the Aladin GUI (Graphical User Interface) commands to
create a credible region at a defined confidence level is reported
below. From the main menu press
``→ Coverage → Generate a MOC based on... → The current probability skymap → MOC generation window``
.. figure:: /_static/aladin_fig1.png
:alt: Create a MOC from a GW sky localization
The ``MOC generation`` window requires two mandatory parameters 1) the
*probability skymap* and 2) the *threshold*. The probability sky map
entry - that means the GW sky localization in our context - can be
selected from the drop down menu. They are the GW sky localization
previously loaded and showed in the Aladin Stack. The threshold input
represents the percentage of the credible region passed in decimal
(ranging from 0 to 1). Press the ``CREATE`` button to generate the
resulting credible region. The credible region is created and loaded in
the Aladin Stack. The credible region obtained so far are decoded in the
Multi Order Coverage map (MOC) and each new level can be independently
used.
4. *Properties* Window
----------------------
To open the ``Properties`` window, right click on the selected plan in
the Aladin stack. The associated ``Properties`` windows allows to change
the *drawing methods* in *perimeter* in order to simultaneously
visualize multiple confidence levels. This operation facilitates tiling
operations by telescopes monitoring the highest probability areas. The
enclosed sky area in square degrees and the percentage of the sky
coverage are quoted for each credible region either **i)** by leaving
the cursor on the corresponding plan loaded in the Aladin stack or
**ii)** by opening the associated Properties windows.
.. figure:: /_static/aladin_fig2.png
:alt: Properties window
You can overlap a large dataset of image backgrounds provided by the
`HiPS list aggregator <https://aladin.unistra.fr/hips/list>`__ or you
can generate your own HiPS from image/cube data. For doing this, from
the main menu press
``→ Tool → Generate a HiPS based on... → An image collections (FITS, JPEG, PNG)...``
5. Querying and Filtering a Galaxy Catalog
------------------------------------------
Singer et al. \ `[3] <#cite-singer16b>`__ discuss a fast algorithm for
obtaining a three-dimensional probability estimates of sky location and
luminosity distance from observations of binary compact object mergers
with Advanced LIGO and Virgo. Combining the reconstructed gravitational
wave volumes with positions and redshifts of possible host galaxies
provides a manageable list of sky location targets to search for the
electromagnetic counterpart of the gravitational wave signal. These
tasks can efficiently be performed in the Aladin Desktop using the data
collections tree and the filter methods as follows.
``Aladin data collections tree → Select → click on the catalog item → in the popup menu check → by region & MOC``
.. figure:: /_static/aladin_fig3.png
:alt: Aladin data collection tree
Now we can filter the galaxy catalog...
``Catalog → Create a filter → Properties window → Advanced mode→ Or enter your filter definition:``
An example about the Aladin filter using as galaxy selection the
marginal distance posterior distribution integrated over the whole sky
is reported below:
``${Dist} > DISTMEAN-DISTSTB && ${Dist} < DISTMEAN+DISTSTB {draw}``. The
posterior mean distance (Mpc) and the posterior standard deviation of
distance (Mpc) are reported in the fits file header with the keywords
``DISTMEAN`` and ``DISTSTB``. Click on ``Apply`` and then ``Export`` to
create a new plane consisting only of sources selected by the filter.
.. figure:: /_static/aladin_filter.png
:alt: Aladin filter
Finally, make thumbnails of the selected galaxies. From the main menu
press ``→ Tool → Thumbnail view generator...`` download and select in
the Aladin stack any image background to obtain the corresponding galaxy
images.
.. figure:: /_static/aladin_fig4.png
:alt: Thumbnail view generator
[1] Singer, L. P., & Price, L. R. 2016, *Phys. Rev. D*, 93, 024013.
`doi:
0.1103/PhysRevD.93.024013 <https://journals.aps.org/prd/abstract/10.1103/PhysRevD.93.024013>`__
[2] Fernique, P., Allen, et al. 2015, *Astron. Astrophys.*, 578, A114.
`doi: 10.1051/0004-6361/201526075 <10.1051/0004-6361/201526075>`__
[3] Singer, L. P., Chen, H.-Y., Holz, D. E., et al. 2016, *Astropys. J.
Lett.*, 829, L15.
`doi:10.3847/2041-8205/829/1/L15 <https://iopscience.iop.org/article/10.3847/2041-8205/829/1/L15>`__
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