Calibration solvers

Two calibration solvers are available in ASKAPsoft. The solver parset parameter defines the type of the calibration solver to use with the choice between SVD, and LSQR. The SVD solver is based on calculation of the singular value decomposition. It generally performs well for small problem sizes, but shows poor performance for large number of anthennas. It does not require setting free parameters. The iterative least-squares LSQR solver is a high performance solver, that is capable of performing calibration on the SKA scales (i.e., very large number of antennas). It scales nearly linearly with the number of data, i.e., quadratically with the number of antennas. It requires setting several free parameters, such as stopping criteria and damping parameters. Due to its general least-square nature, it also allows adding additional constraints into the system of equations (for example, solution smoothness).

Common Parameters

Parameters for all solvers:

Parameter Type Default Description
solver string SVD Selection of solver. Either “SVD” or “LSQR”.

The SVD solver does not require any additional parameters. Additional parameters understood by the LSQR solver are given in the following section.

LSQR Solver Parameters

All parameters given in the next table have solver.LSQR prefix (e.g., Cbpcalibrator.solver.LSQR.niter).

Parameter Type Default Description
rmin float 1.e-13 Minimum relative residual stopping criterion.
niter int 100 Maximum number of minor cycles. This stopping criterion is used when minimum relative residual stopping criterion could not be reached within the specified number of solver iterations.
alpha float 0.01 The damping on the solution perturbation (that is performed at every major cycle). Nonzero damping values help dealing with rank deficient systems.
verbose bool false The value of “true” enables lots of output.
parallelMatrix bool false Enables regime where all frequency channels are solved together, and therefore can be coupled via frequency-dependant constraints (e.g. smoothness). The columns of the (block-diagonal) matrix, and the bandpass solution are split between different ranks. This option is only supported in ccalibrator, and must be accompanied by the following options: Ccalibrator.solver=LSQR, Ccalibrator.solve=bandpass. The data partitioning are then defined via setting Ccalibrator.chanperworker, and Ccalibrator.chunk, in analogous to Channels option in cimager (see cimager for more details).

Examples

LSQR Solver

Cbpcalibrator.solver                            = LSQR
Cbpcalibrator.solver.LSQR.niter                 = 100
Cbpcalibrator.solver.LSQR.rmin                  = 1.e-13
Cbpcalibrator.solver.LSQR.alpha                 = 0.01
Cbpcalibrator.solver.LSQR.verbose               = false

Table Of Contents

Previous topic

Solvers

Next topic

Data Selection

This Page