PSRCHIVE user documentation: pcm

1.0 Purpose

The Polarization Calibration Modeling (pcm) program may be used to estimate the polarimetric response of the observing system, as described in van Straten 2004, ApJS 152:129, and van Straten 2013, ApJS 204:13. There are two different modes of operation:

Measurement Equation Modeling (MEM), described in van Straten (2004), uses uncalibrated observations of

  • a single pulsar at multiple parallactic angles,
  • an amplitude modulated reference source (linear noise diode), and
  • [optionally] an unpolarized flux calibrator, such as Hydra A.
Please read this imporant note about assumptions made to overcome measurement equation modeling degeneracy.

Measurement Equation Template Matching (METM), described in van Straten (2013), uses

  • a single well-calibrated observation of a pulsar with high signal-to-noise ratio (the template, or standard),
  • one or more uncalibrated observations of the same pulsar, and
  • [optionally] an amplitude-modulated reference source (e.g. a noise diode coupled to the receptors).

2.0 Usage

2.1 Before running pcm

In order to run pcm in MEM mode, you will need Pulsar::Archive files containing:
  • full polarization observations of a single pulsar over a wide range in parallactic angles (Pulsar::Archive::get_type must return Signal::Pulsar).
  • one or more observations of the "linear" noise diode (CAL) made while pointing at or near the pulsar (Pulsar::Archive::get_type must return Signal::PolnCal).
  • [optionally] one or more observations of the CAL made while pointing at a strong flux calibrator with negligibly small degree of circular polarization, such as Hydra A (Pulsar::Archive::get_type must return Signal::FluxCalOn).
All observations must have the same observing parameters, such as centre frequency and bandwidth, as defined by the Pulsar::Archive::calibrator_match method. After gathering all of the required data:
  • Create a calibrator directory and database file:
    1. Copy all calibrator files (.pcal, .fcal) to one directory, say $MYCALS. The files can be organized into sub-directories if desired (see the pac manual).
    2. Run pac -wp $MYCALS to create the summary file, $MYCALS/database.txt.
  • Create a preliminary total integrated calibrated profile:
    1. Perform preliminary calibration using pac -d $MYCALS/database.txt psr*.ar
    2. Combine the calibrated output archives using psradd -T -o calib.TT psr*.calib

This last step produces a total integrated profile from which to choose the best pulse phase bins to be used as model constraints. It is best to choose these from a high S/N profile, but integration in both time and frequency will lead to depolarization (primarily due to the variation of differential phase as a function of frequency, and to the time-varying projection of the receptors onto the sky). The preliminary calibration step minimizes this depolarization.

As described in more detail in Section 4.1, it is possible to either manually choose individual phase bins or ranges of pulse phase that make good model constraints, or allow pcm to automatically choose the best pulse phase bins. When choosing phase bins manually, it is best to choose those with the highest polarized flux density and, if selecting more than one pulse phase bin, to choose states that have orthogonal polarization vectors in the Poincare space.

As more phase bins are used as constraints, more time will be required to converge to a solution. For starters, use only four phase bins; pcm will converge more quickly, providing a first order estimate of the instrumental parameters. More phase bins can then be added to descrease the experimental uncertainty of the results.

2.2 Running pcm

2.2.1 MEM mode
In MEM mode, pcm does the following (not necessarily in this order):
  • Loads all PolnCal calibrator files and solves the receiver using one of the basic models (SingleAxis or Polar, depending upon the chosen parameterization, Britton or Hamaker). The weighted mean of these solutions is used as the first guess of the instrumental response.
  • Loads the pulsar archive and prunes the Stokes parameters from the specified set of pulse phase bins. These are corrected using the best guess of the instrumental response, deparallactified, and added to a weighted mean that is used as the first guess of the Stokes parameters.
  • Loads all FluxCalOn flux calibrator files and uses the off-pulse Stokes parameters to constrain the mixing of Stokes I and V. This breaks the degeneracy described in van Straten (2004).
An example of MEM usage.
2.2.2 METM mode
When run with the -S standard.ar option, pcm performs measurement equation template matching, a global fit in which the transformation between the well-calibrated template in standard.ar and the pulsar observations specified on the command is modellded. Calibrator observations are also incorporated as constraints. With the -1 option, an unique fit if performed on each input sub-integration and a separate file is output for each solution (with the extension .mtm).

An example of METM usage. Note that this technique can be used to estimate the differential Faraday rotation between the template and the observation.

2.3 Diagnostic outputs

pcm can optionally produce a number of diagnostic outputs. These are enabled with the -D name command line option, where name is any one of:

  • report print a report of the reduced chisq for each Stokes parameter of each pulse phase bin in pcm_report_*.txt. Please see fit report for more details.
  • guess plot the initial guess of the instrumental response in guess_response.ps, the calibrator Stokes parameters in guess_cal.ps, and the pulsar Stokes parameters in guess_psr.ps.
  • residual plot the residual between each measurement and the model in channel_*.ps.
  • total plot the total integrated pulse profile in uncalibrated.ps (before) and calibrated.ps (after).
  • result plot the best fit result of the instrumental response in result_response.ps, the calibrator Stokes parameters in result_cal.ps, and the pulsar Stokes parameters in result_psr.ps.

2.4 Modeling time variations

Intrinsic variations (including interstellar scintillation)

pcm can compensate for intrinsic variations in the intensity of the pulsar signal by normalizing the Stokes parameters of the pulsar observations by the mean invariant: the square root of the mean of the invariant intervals (I^2 - p^2) of a constant selection of on-pulse phase bins.

This feature is enabled with the -s command line option. The on-pulse phase bins are chosen from either the first archive loaded or the archive specified using the -c command line option, then held fixed for all subsequent archives.

When -s is used, the pulsar is put through a signal path with constant gain set to unity, and the free gain parameter is applied only to the calibrator signal path.

Instrumental variations

pcm can model the observations with an instrumental backend that varies over time. Each of the absolute gain, differential gain, or differential phase may be independently represented as either

  • a polynomial of arbitrary order; or
  • a series of step functions (jumps).
For the series of steps, the epoch of each step is defined by the first sub-integration of each CAL file encountered. This models the typical observing pattern with the DFB at Parkes, where a LEVCAL observation is made to set the signal levels, which remain fixed until the next LEVCAL.
  -u PAR     model PAR with a step at each CAL
  -o PAR:N   model PAR as N degree polyomial
Where PAR is a single-character code:
  • g = absolute gain
  • b = differential gain
  • r = differential phase
  • a = all of the above
For example, to model all three parameters as a third order polynomial, use -o a:3; to model absolute and differential gain variations with a step function at each CAL, add -u g -u b.

3.0 Algorithms

In MEM mode, pcm implements the model of reception and the algorithm for solution described in van Straten, W. 2004, Radio Astronomical Polarimetry and Point-Source Calibration, Astrophys. J. Supp. 152, 129-135. arXiv:astro-ph/0401536

In METM mode, pcm implements the frequency-domain algorithm for matrix template matching described in van Straten, W. 2006, Radio Astronomical Polarimetry and High-Precision Pulsar Timing, The Astrophysical Journal 642, 1004-1011 arXiv:astro-ph/0510334

4.0 Testing and examples

4.1 MEM Example

4.2 METM Example

5.0 Known bugs and features that require implementation

  • Currently, pcm can handle data from only one pulsar.