Congratulations on getting EVN data! What's next?
JIVE correlates all EVN observations and performs a preliminary reduction using the EVN pipeline. At this point you would have received an email from your EVN Support Scientist with details on how to access and download your data. You should take a look at the results from the pipeline analysis. In general the pipeline results are expected to be used only as a guide and should not be considered as a final science product. We recommend using the amplitude calibration table from the pipeline as the starting point of a manual calibration of the data. The fringe-fit, bandpass calibration, and imaging should thus be done by the user.
We recommend using AIPS to perform the initial reduction and calibration of EVN data as, to-date, other packages do not have the ability to fringe fit data, which is integral for non-connected element arrays. Martin Shepherd's Difmap program can also be used for imaging and self-calibrating EVN data.
This page is intended to be a guide for new users that want to analyze EVN data, describing the standard steps that are performed during the data reduction. A basic knowledge of radio interferometric data and AIPS is required to fully understand all the steps.
After correlation, the EVN Support Scientists will send you an email with details on how to access and download your data. The data, together with the EVN pipeline results, are stored at the EVN Data Archive, where you can find useful information concerning your experiment:
AIPS runs in a dedicated environment that do not support long path names. For this reason it is recommended to set up an environment variable, MYDIR, with the working directory where your data are:
We note that AIPS automatically recognizes PWD as an environment variable, thus in case that your working directory is the same as the directory from where AIPS is launched you do not need the previous step.
Now we can start AIPS by typing:
The tv=local:0 parameter is optional but it assures that a new graphical window will be open in case of having other AIPS sessions already opened.
AIPS will then ask you for a user number. This guide assumes you are using an "empty" AIPS user number (not used before or with no data inside).
Loading the data into AIPS using the task FITLD:
Now we need to load the file containing the calibration tables and copy the appropriate ones to our data:
We generally recommend using the a-priori amplitude calibration provided by the EVN pipeline (CL2 from this last file), and applying the flags from FG1 (which for example automatically flags the off-source times for each telescope). We can copy these tables to our data using TACOP:
We can check that both tables have been correctly copied by typing getn 1 and imh, which shows us the header of that catalog entry. The output should be equivalent to:
AIPS 1: Image=MULTI (UV) Filename=EM121B .UVDATA. 1 AIPS 1: Telescope=EVN Receiver=VLBA AIPS 1: Observer=EM121B User #= 1212 AIPS 1: Observ. date=23-OCT-2016 Map date=31-MAR-2017 AIPS 1: # visibilities 679677 Sort order TB AIPS 1: Rand axes: UU-L-SIN VV-L-SIN WW-L-SIN TIME1 SUBARRAY AIPS 1: FREQSEL SOURCE INTTIM ANTENNA1 ANTENNA2 CORR-ID AIPS 1: ---------------------------------------------------------------- AIPS 1: Type Pixels Coord value at Pixel Coord incr Rotat AIPS 1: COMPLEX 3 0.0000000E+00 1.00 1.0000000E+00 0.00 AIPS 1: STOKES 4 -1.0000000E+00 1.00 -1.0000000E+00 0.00 AIPS 1: FREQ 32 4.9269900E+09 1.00 5.0000000E+05 0.00 AIPS 1: IF 8 1.0000000E+00 1.00 1.0000000E+00 0.00 AIPS 1: RA 1 20 31 51.780 1.00 3600.000 0.00 AIPS 1: DEC 1 41 31 18.300 1.00 3600.000 0.00 AIPS 1: ---------------------------------------------------------------- AIPS 1: Coordinate equinox 2000.00 AIPS 1: Maximum version number of extension files of type HI is 1 AIPS 1: Maximum version number of extension files of type FG is 1 AIPS 1: Maximum version number of extension files of type AT is 1 AIPS 1: Maximum version number of extension files of type NX is 1 AIPS 1: Maximum version number of extension files of type CL is 2 AIPS 1: Maximum version number of extension files of type CT is 1 AIPS 1: Maximum version number of extension files of type FQ is 1 AIPS 1: Maximum version number of extension files of type AN is 1 AIPS 1: Maximum version number of extension files of type SU is 1 AIPS 1: Keyword = 'OLDRFQ ' value = 4.92699000D+09 AIPS 1: Keyword = 'CORRELAT' value = 'SFXC 'Here AIPS shows us the basic data from our experiment. In particular, we can see:
Before starting the calibration we should take a look at the data. We can start running LISTR and PRTAN to get information about the observed sources and the stations that participated during the observation.
One of the (many!) nice things about VLBI is that most terrestrial RFI will not correlate. The FG1 table that we already imported flags some data such as the edge-channels or the off-source times. Nonetheless, there are times that flagging is necessary. AIPS has several flagging tasks such as UVFLG, TVFLG, SPFLG and RFLAG. Use plotting tasks such as POSSM and UVPLT to determine if you wish to flag any data. You should also look at the pipeline plots (e.g., plots of amplitude and phase against frequency channel) as they will provide invaluable information about the location of bad data. It is recommended that obvious bad data is flagged from your calibrators to ensure a good calibration. See an example of the plots that you can produce with these tasks in the following buttons:
If your observation was conducted at frequencies ≲ 5 GHz you probably want to correct for ionospheric effects. Given that the stations are located at huge distances (up to 10,000 km apart), the ionospheric conditions can be really different at each location, affecting in a different way to each station.
Although there are different approaches to correct for the ionospheric effects, here we will show how to run VLBATECR, which is part of the VLBA utilities. First, we need to type (if we have not done it before) run vlbautil to load all these utilities. And then:
This task will download the appropriate files from CDDIS and then it will run TECOR with these files. We will get a new CL table (CL3) containing these corrections. Note that in the following the user guide assumes that you did not perform this correction and the next calibration takes CL2. In case you correct for this effect, all gainu/gainv parameters will need to use one version higher than mentioned in theuUser guide (i.e. gainv 3 instead of gainv 2, and so on).
You may have noticed in POSSM that there is not only a gradient in phase within each IF, but the mean phases for each IF are also quite different with jumps in between. This is due to the independent signal paths for each IF, and must be corrected for (there are not physical jumps in the phases between IFs, they clearly have an instrumental origin).
In this step we will be correcting for instrumental delays, the phase jumps between IFs, and as such we only want data over a short time period because we do not want changes as a function of time to come into play (these delays should be constant along the whole observation). This is why it is important to have bright calibrators for VLBI observations! The effect of removing instrumental delays is to bring all the phases to zero, at least for the chosen time range. To correct the instrumental delay choose a few minutes on a bright fringe-finder (FF) when all antennas observed and the data is free of RFI.
If you look now at the header of the file (with imh), you will notice that there is a new table: SN1. This table contains the solutions from this fringe-fit. You can use SNPLT to look at the delay solutions:
The reference antenna should display a zero delay correction.
When you are happy with the SN table, you can apply it to your CL table (we will take CL2, apply the solutions in SN1 and it will create a CL3 table).
We can look at the new calibration table with SNPLT (using inext 'cl') and POSSM again.
We have considered here the most common case where we have a time range where all stations were observing without problems. However, this is not always true. We can have observations were only part of the stations were observing the fringe-finder in given scan, and the other stations were observing the fringe finder in a different scan (either the same source or a different one). This can happen, for example, in the case of observing with Asian, European, and American stations. At a particular time not all stations are available to observe.
We have corrected for the instrumental delay. However, we now need to correct for delays and rates as a function of time, which will be done by fringe-fitting the data. Consequently we will be using a smaller solution interval.
LOCALH> FRING2: Fitted phases, rates, delays and SNR: [ P = phase(deg), LOCALH> FRING2: R = rate(mHz), D = Single-Band Delay(nsec), S = SNR ] LOCALH> FRING2: Ant(02): Phas= 19.6 rate= -0.70 delay= 0.05 SNR=2666.8 LOCALH> FRING2: Ant(03): Phas= -20.6 rate= -0.22 delay= 0.02 SNR=1886.7 LOCALH> FRING2: Ant(07): Phas= 29.0 rate= -0.01 delay= 0.03 SNR=2861.0 LOCALH> FRING2: Ant(08): Phas= -66.3 rate= -1.71 delay= 0.03 SNR=1680.1 LOCALH> FRING2: Standard RMS errors (deg, mHz, nsec): LOCALH> FRING2: Ant(02): Phas= 0.02 rate= 0.002 delay= 0.000 LOCALH> FRING2: Ant(03): Phas= 0.03 rate= 0.003 delay= 0.001 LOCALH> FRING2: Ant(07): Phas= 0.02 rate= 0.002 delay= 0.000 LOCALH> FRING2: Ant(08): Phas= 0.03 rate= 0.003 delay= 0.001 LOCALH> FRING2: Found 800 good solutions LOCALH> FRING2: Failed on 24 good solutions LOCALH> FRING2: Appears to have ended successfully
Now we can repeat the same steps that we conducted after the first FRING to look at the solutions (now recorded in SN2) with SNPLT.
If the solutions look OK we can apply them to create a new calibration table (CL4). In this case, we will apply the solutions from each of the used calibrators to themselves, and finally the solutions from the phase calibrator will be also extrapolated to the target source (if we have conducted a phase-referencing observation).
We should look for possible bad times were the solutions were not properly obtained (e.g. the phases were rapping and coherence is completely lost). Those times would produce bad-quality data that should be manually removed in the final stages of the calibration.
Finally, we need to correct for the response of the receiver as a function of frequency. This is done via a bandpass calibration using BPASS.
We can now look at the solutions again with POSSM, for example setting aparm 0, 1, 0, 2, -180, 180, 0, 2, 3 to show both amplitude and phase at the same time.
We are now ready to apply our calibration tables to the data. We will split the data to make imaging easier (e.g. creating different data sets for each source), and in the process of splitting the data we will apply CL4, BP1 and all FG tables to these data.
If you check now the available catalogue entries in our session (with pcat) you will see that there is a SPLIT file for each source, containing the calibrated data.
If you wish to store these files outside AIPS, in FITS format, you can run FITTP:
As mentioned in the introduction, the imaging process can be done either in AIPS or in Difmap. Here we show a basic running of the AIPS imaging and how to obtain a map of your source. See the end of this page to find a more detailed tutorial on how to image and self-calibrate your data within Difmap and AIPS in case of phase-referencing experiments, or how to analyze EVN spectral line data.
The AIPS task to image your data is IMAGR.
You can look at your images by selecting the file with getn i and tvall. You can change interactively the colorscale and contrast with the mouse and keys. Run tvps to switch between colorscales or grayscales.
There are two basic tasks in AIPS to perform measurements in your image, imstat (or tvstat) and jmfit.
imstat tells you the statistics of the image. After showing your image with tvall you just need to run imstat. You will see a message log as the following, reporting the mean, rms, maximum, minimum and minimum brightness and their positions in the image.
AIPS 2: Mean= 7.078E-04 rms= 5.194E-02 JY/BEAM over 1048576. pixels AIPS 2: Maximum= 1.5677E+00 at 512 513 1 1 1 1 1 AIPS 2: Skypos: RA 05 55 30.80561200 DEC 39 48 49.1649800 AIPS 2: Skypos: IPOL 4867.125 MHz AIPS 2: Minimum=-1.9778E-01 at 121 1020 1 1 1 1 1 AIPS 2: Skypos: RA 05 55 30.80900551 DEC 39 48 49.2156799 AIPS 2: Skypos: IPOL 4867.125 MHz AIPS 2: Flux density = 5.1963E+00 Jy Beam area = 142.82 pixels
tvstat is analog to imstat but you are able to select a particular region of the image where to perform the statistics. This can be useful to measure the rms of the image (selecting a large region around your source but without including it), and the flux density of your source. Once you run tvstat you are able to set the region graphically with the mouse.
jmfit fits a gaussian to your image. The recommended way to run it is with tvall; tvwin; go jmfit, which shows you the image (tvall), allows you to select a region of the image around your source (tvwin), and run the gaussian fit (jmfit). This last command writes the solution in the message log:
LOCALH> JMFIT2: ********* Solution from JMFIT ********************************* LOCALH> JMFIT2: LOCALH> JMFIT2: Component 1-Gaussian LOCALH> JMFIT2: Peak intensity = 1.5311E+00 +/- 4.93E-02 JY/BEAM ( 31.05) LOCALH> JMFIT2: Integral intensity= 1.7172E+00 +/- 9.23E-02 JANSKYS LOCALH> JMFIT2: X-position = 512.138 +/- 0.2548 pixels LOCALH> JMFIT2: Y-position = 513.182 +/- 0.1116 pixels LOCALH> JMFIT2: RA 05 55 30.80561080 +/- 0.000002211 LOCALH> JMFIT2: DEC 39 48 49.1649981 +/- 0.00001116 LOCALH> JMFIT2: Major axis = 18.914 +/- 0.6092 pixels LOCALH> JMFIT2: Minor axis = 7.474 +/- 0.2407 pixels LOCALH> JMFIT2: Position angle = 100.857 +/- 1.222 degrees LOCALH> JMFIT2: Major axis = 0.0018914 +/- 0.0000609 asec LOCALH> JMFIT2: Minor axis = 0.0007474 +/- 0.0000241 asec LOCALH> JMFIT2: Position angle = 100.857 +/- 1.222 degrees LOCALH> JMFIT2: RASHIFT= -0.000014 DECSHIFT= 0.000018 to center on pixel LOCALH> JMFIT2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - LOCALH> JMFIT2: Deconvolution of component in pixels LOCALH> JMFIT2: Nominal minimum maximum LOCALH> JMFIT2: Major ax 4.810 0.000 5.845 LOCALH> JMFIT2: Minor ax 0.000 0.000 7.051 LOCALH> JMFIT2: Pos ang 65.386 41.485 102.263 LOCALH> JMFIT2: Deconvolution of component in asec LOCALH> JMFIT2: Nominal minimum maximum LOCALH> JMFIT2: Major ax 0.000481 0.000000 0.000584 LOCALH> JMFIT2: Minor ax 0.000000 0.000000 0.000705 LOCALH> JMFIT2: Pos ang 65.386246 41.485229 102.263382 LOCALH> JMFIT2: Component may be unresolved or resolved, use caution LOCALH> JMFIT2: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - LOCALH> JMFIT2: returns adverbs to AIPS LOCALH> JMFIT2: Appears to have ended successfully
We have shown the basics steps to analyze EVN data. But further steps can be done to improve the results and/or specific actions must be done as a function of what kind of observation you are analyzing.
In the following you can select the chapters that best suit for your data.