Tips for running Rapthor

Processing a subset of the data

To speed up processing, it is recommended that only a small fraction of the full dataset be used for self calibration. Rapthor will internally perform self calibration on 20% of the full data by default, but this number can be set with the selfcal_data_fraction parameter. Once self calibration converges, Rapthor will by default perform a final cycle using 100% of the input data (the final fraction can be set using the final_data_fraction parameter).

Number of directions / calibration patches

Increasing the number of directions (also referred to as calibration patches and imaging facets, if faceting is used) will generally result in better direction-dependent corrections. However, more directions implies fainter calibration sources as well as longer runtimes, especially during calibration. Therefore, the default strategy slowly increases the number of directions with each self calibration cycle, as the model of the field improves and fainter sources can be used for calibration. Most fields work well with a maximum of 50 directions, but fields with many bright sources may require more and those with a lack of bright sources may require fewer.

Problematic fields

Fields that lie at low declinations or that have very extended or very bright sources might pose problems for self calibration. For example, it is recommended that fields with very bright sources (> 20 Jy) use a processing strategy that starts with at least three rounds of phase-only calibration before moving to amplitude calibration (cf. the default strategy, which uses two rounds of phase-only calibration). The information here will be updated as further testing on a variety of field is done and our understanding of the sub-optimal cases improves.

Bright outlier sources

The presence of very bright outlier sources (sources that lie outside of imaged regions) can cause strong artifacts across the field that cannot be corrected during self calibration. Possible solutions to this problem are to increase the image regions to include the outliers (e.g., with the image grid parameters grid_width_ra_deg and grid_width_dec_deg) or to place small imaging sectors on each outlier (by specifying the sectors using the sector list parameters such as sector_center_ra_list). With either of these options, the outliers are imaged along with the main field and hence their models are updated each self calibration cycle.

Creating a dataset for further self calibration

Rapthor can be used to create datasets that can be used for further self calibration outside of Rapthor, for example for targets of interest. These datasets can have non-target sources peeled and calibration solutions preapplied. The optimal way to generate such datasets with Rapthor is to run a standard reduction to generate a solution table (H5parm file) and sky model for the full field and to input these to a new Rapthor run using the “image” strategy, in which only peeling and imaging are done. The following parameters should be set:

• Set the input_skymodel and input_h5parm parameters in the parset to the output of the full-field reduction. If a full-Jones solve was done, input_fulljones_h5parm can also be set. The time and frequency coverage of the solution tables must be large enough to cover the duration and bandwidth of the input dataset. The easiest way to ensure this requirement is met is to use the solutions from a solve over the full dataset (i.e., those from the final iteration of a run with final_data_fraction = 1.0)

  Note

  The sky model from a full-field reduction will contain only those sources that lie in the regions imaged during that reduction. If it is important to peel sources outside of these regions (e.g., there is a very bright source that lies outside the field, but near enough to cause problems if not peeled), then you need to add these sources to the input sky model before running Rapthor in this mode.

• Set the regroup_input_skymodel parameter to False to preserve the calibration patches that match the directions in the solutions file.

• Set the strategy parameter to “image” (or provide an equivalent custom strategy file).

• Set the save_visibilities parameter to True to save the MS files used for the imaging. The output MS files will be located in dir_working/visibilities. Furthermore, dde_method can be set to “none” to preapply the solutions in the direction closest to the sector center (other values of dde_method will not preapply the solutions, since the solutions in those cases are applied by WSClean during imaging).

• Define the imaging sectors to cover the targets of interest. Multiple sectors can be used, and a set of calibrated visibilities will be generated for each sector.