Difference between revisions of "Simalma v2"

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(Created page with "Category: Simulations To create a script of the Python code on this page see Extracting scripts from these tutorials. __NOTOC__ == The simalma task == ALMA consists ...")
 
 
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[[Category: Simulations]]
 
[[Category: Simulations]]
  
To create a script of the Python code on this page see [[Extracting scripts from these tutorials]].
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'''This link is no longer active.'''
__NOTOC__
 
== The simalma task ==
 
  
ALMA consists of the high resolution array of 12m antennas, the ALMA Compact Array of 7m antennas, and Total Power measurements using 12m antennas. One can simulate all of these in CASA.
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You can find a CASA guide for using <tt>simalma</tt> here: [[Simalma_(CASA_4.2)]]
  
One could use '''simobserve''' generate simulated observations for each component separately, and then combine the Measurement Sets in '''simanalyze'''.  This technique is general and can be used to simulate observations using multiple 12 m array configurations, as well.  Total power observations can be simulated either in an independent run of '''simobserve''', or along with one of the interferometric simulations.  Note that if you simulate total power and an interferometric observation ssimultaneously with simobserve, they must have the same set of pointing centers and the same integration and total time, which is probably not realistic. (For example it is generally recommended to observe a larger area by 1/2 primary beam in total power mode to combine with a 12 m ALMA mosaic).
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You can find a guide specific to simulating ALMA data here: [[Guide_To_Simulating_ALMA_Data]]
  
This "manual" method is described in the [[ACA_Simulation_(CASA_4.1)]] guide. 
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You can find a guide to simulating interferometric data in CASA version 4.2 here: [[Simulating_Observations_in_CASA_4.2]]
  
New in 4.1 is the '''simalma''' task, which takes one set of parameters describing the region of the sky to observe, and makes the appropriate calls to '''simobserve''' and '''simanalyze''' for the user.  How this works is described here.
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You can find a guide to simulating interferometric data in CASA version 4.1 here: [[Simulating_Observations_in_CASA_4.1]]
 
 
<font color="purple">As of CASA 4.1, ALMA is still optimizing the algorithms for combining total power and interferometric data, so the parameters used here are likely to change.</font>
 
 
 
 
 
=====Set simalma as current task=====
 
Reset all parameters to default, and then set the project name to ''m51''
 
<source lang="python">
 
# Set simalma to default parameters
 
default("simalma")
 
# Our project name will be m51, and all simulation products will be placed in a subdirectory m51/
 
project="m51"
 
</source>
 
 
 
=====Specify sky model image=====
 
We'll use an Halpha image of M51 as a model of the sky, for this example.  The ''curl'' command will copy the file from a URL and rename it.
 
 
 
<source lang="python">
 
# Model sky = Halpha image of M51
 
os.system('curl http://casaguides.nrao.edu/images/3/3f/M51ha.fits.txt -f -o M51ha.fits')
 
skymodel        =  "M51ha.fits"
 
</source> 
 
 
 
Note that '''simalma''' will not modify your original input image.  Rather, it will make a copy ''m51/m51.skymodel''.
 
 
 
We will override most of the parameters in the Halpha FITS image to make the image more suitable to a sub-millimeter ALMA observation.  We will:
 
* place the source in the southern hemisphere with the ''indirection'' parameter,
 
* set the pixel size to 0.1arcsec, to simulate an observation of a galaxy that is smaller in angular size. (M51 itself would require a quite large mosaic, and in any case we'd like the input model pixels to be significantly smaller than the synthesized beam.)
 
* set the peak brightness to 0.004 Jy/pixel
 
* set the frequency to 330GHz, and since it's a 2D image we'll set the single "channel" width to be 50MHz, and peak brightness of 0.004 Jy/pixel.  These parameters are plausible for observing a sub-mm emission line in a galaxy.
 
<source lang="python">
 
# Set model image parameters:
 
indirection="J2000 23h59m59.96s -34d59m59.50s"
 
incell="0.1arcsec"
 
inbright="0.004"
 
incenter="330.076GHz"
 
inwidth="50MHz"
 
</source>
 
 
 
----
 
 
 
====Set up Observing Parameters====
 
[[Image:M51.alma_cycle1_3.skymodel.png|thumb|hexagonal mosaic overplotted on sky model]]
 
 
 
Based on the Cycle 1 capabilities, we would like to use array configuration number 3 which affords ~0.5 arcsec resolution:
 
<source lang="python">
 
antennalist="alma_cycle1_3.cfg"
 
</source>
 
 
 
We'll observe for a couple of hours (this is the 12m array observing time):
 
<source lang="python">
 
totaltime="7800s"
 
</source>
 
 
 
Following the Cycle 1 convention, <tt>simalma</tt> will observe 3 times longer with the 7m array and total power dishes.
 
<source lang="python">
 
acaratio=3.0
 
acaconfig="aca_cycle1.cfg"
 
</source>
 
 
 
In nominal weather:
 
<source lang="python">
 
pwv=0.6
 
</source>
 
 
 
To cover the source as we've rescaled the pixel size, we'll need a 1 arcmin mosaic, and we'll let <tt>simalma</tt> calculate the pointings for us:
 
<source lang="python">
 
mapsize="1arcmin"
 
</source>
 
 
 
----
 
 
 
=====What does it do?=====
 
 
 
[[Image:M51.alma_cycle1_3.observe.png|thumb|12m observation]]
 
 
 
The 12m array observation is simulated first -- <tt>simalma</tt> simply calls <tt>simobserve</tt> with your input parameters.
 
<tt>simobserve</tt> generates a graphic about the elevation and showing the dirty synthesized beam:
 
 
 
The 12m-only visibilities are not currently imaged separately from the 7m visibilities, but this is an expected upgrade in a future release.  One could easily image the generated measurement set, which will be named according to the <tt>antennalist</tt> parameter above -- in this example, it is called <tt>m51.alma_cycle1_3.noisy.ms/</tt>.
 
 
 
<p>
 
----
 
 
 
[[Image:M51.aca_cycle1.skymodel.png|thumb|ACA hex map]]
 
Next, the 7m ACA observation is simulated, with a second call to <tt>simobserve</tt>:
 
<tt>simobserve</tt> follows the same conventions as the ALMA Observation Preparation Tool, and sets the mosaic pointings to cover the area requested -- it takes fewer 7m pointings to cover the region than it did 12m pointings.
 
 
 
It is useful to know that a version of the input sky model convolved to the ACA resolution is generated, in this example <tt>m51.aca_cycle1.skymodel.flat.regrid.conv/</tt>.  That image can be useful to better understand the simulation results.
 
 
----
 
 
 
Next, <tt>simobserve</tt> is called a third time to generate the total power image.  Again according to Cycle 1 conventions, the same size region as the 12m array mosaic are used, except that an extra pointing is added around the outside edge of the map, to guarantee that the total power map is larger than the interferometric mosaic (total power maps usually have noise and artifact at their edges).  Furthermore, a square raster pattern is used instead of the hexagonal patter of the interferometric array maps:
 
[[Image:M51.aca.tp.skymodel.png|thumb|TP map]]
 
 
 
----
 
 
 
====Deconvolve the visibilities back into images====
 
 
 
Next <tt>simalma</tt> uses '''simanalyze''' to combine the three measurement sets and create a single image.
 
 
 
There are many ways to do this, and you may wish to discuss options with scientists at your ARC.  At time of writing, <tt>simalma</tt> concatenates the two sets of interferometric visibilities, images them, images the single dish spectra, and then uses the <tt>feather</tt> to combine the two images.
 
 
 
First, the total power image is generated using the ASAP gridding tools inside of CASA.  <tt>simalma</tt> attempts to use the optimal gridding kernel to achieve maximum sensitivity and resolution of the single dish map, but the optimal parameters to use is an area of active investigation.
 
 
 
<font color="red">It is critical that the relative weights be set between the two different interferometric arrays. Simulated data has weights=1, since the thermal noise is generated uniformly per baseline.  However, in reality the 7m baselines have lower sensitivity than the 12m baselines, and their weights must be decreased by that sensitivity ratio.  <tt>simalma</tt> uses the <tt>visweightscale</tt> parameter of <tt>concat</tt> to apply that lower weight of (7./12)**2 to the 7m visibilities.  If you wish to combine data manually, you must do this step yourself.</font>
 
 
 
The concatted visibilities are imaged, and diagnostic graphics with "concat" in their names are generated:
 
 
 
[[Image:M51.concat.image.png|thumb|combined interferometric map]]
 
 
 
 
 
----
 
 
 
When combining the single dish and interferometric maps in the image plane using the <tt>feather</tt> task, one must use the interferometric map <it>without</it> the primary beam correction, and first multiply the total power map by the interferometric sensitivity image (".flux") -- this is ensure that noise effects are properly handled on the edges of each map, and do not grow artificially.  After running <tt>feather</tt>, the output is masked to 0.2 times the interferometric primary beam, since the total power map was created larger than the interferometric map on purpose, so the edges of the combined image do not contain any interferometric information.:
 
 
 
[[Image:M51.combine.png|thumb|combined maps]]
 
 
 
 
 
 
 
{{Checked 4.1.0}}
 

Latest revision as of 14:37, 23 October 2013


This link is no longer active.

You can find a CASA guide for using simalma here: Simalma_(CASA_4.2)

You can find a guide specific to simulating ALMA data here: Guide_To_Simulating_ALMA_Data

You can find a guide to simulating interferometric data in CASA version 4.2 here: Simulating_Observations_in_CASA_4.2

You can find a guide to simulating interferometric data in CASA version 4.1 here: Simulating_Observations_in_CASA_4.1