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Source Statistics

This page details the source statistics that are calculated by the pipeline.

Overview

The table below provides a summary of all the statistic and counts provided by the pipeline. See the Variability Statistics section for the table containing the variability metrics.

Note

Remember that all source statistics and counts are calculated from the individual measurements that are associated with the source.

Parameter Includes Forced Meas. Description
wavg_ra No The weighted average of the Right Ascension, degrees.
wavg_dec No The weighted average of the Declination, degrees.
wavg_uncertainty_ew No The weighted average uncertainty in the east-west (RA) direction, degrees.
wavg_uncertainty_ns No The weighted average uncertainty in the north-south (Dec) direction, degrees.
avg_flux_int Yes The average integrated flux, mJy.
max_flux_int Yes The maximum integrated flux value, mJy.
min_flux_int Yes The minimum integrated flux value, mJy.
avg_flux_peak Yes The average peak flux, mJy/beam.
max_flux_peak Yes The maximum peak flux value, mJy/beam.
min_flux_peak Yes The minimum peak flux value, mJy/beam.
min_flux_int_isl_ratio Yes The minimum integrated flux value island ratio (int_flux / total_isl_int_flux).
min_flux_peak_isl_ratio Yes The minimum peak flux value island ratio (peak_flux / total_isl_peak_flux).
avg_compactness No The average compactness of the source (compactness is defined by int_flux / peak_flux).
min_snr No The minimum signal-to-noise ratio of the source.
max_snr No The maximum signal-to-noise ratio of the source.
n_neighbour_dist n/a On sky separation distance to the nearest neighbour within the same run, degrees (arcmin on webserver).
new_high_sigma n/a The largest sigma value a new source would have if it was placed at its location in the previous images it was not detected in. See New Sources for more information. New sources only.
n_meas Yes The total number of measurements associated to the source. Named Total Datapoints on the webserver.
n_meas_sel No The total number of selavy measurements associated to the source. Named Selavy Datapoints on the webserver.
n_meas_forced Yes The total number of forced measurements associated to the source. Named Forced Datapoints on the webserver.
n_rel n/a The total number of relations the source has. See Source Association. Named Relations on the webserver.
n_sibl n/a The total number measurements that has a sibling. On the webserver tables this is firstly presented as a boolean column of if the source contains measurements that have a sibling.

Variability Statistics

Below is a table describing the variability metrics of the source. See the following sections for further explanation of these metrics.

Parameter Includes Forced Meas. Description
v_int Yes The \(V\) metric for the integrated flux.
v_peak Yes The \(V\) metric for the peak flux.
eta_int Yes The \(\eta\) metric for the integrated flux.
eta_peak Yes The \(\eta\) metric for the peak flux.
vs_abs_significant_max_int Yes The \(\mid V_{s}\mid\) value of the most significant two-epoch pair using the integrated fluxes. Will be 0 if no significant pair.
m_abs_significant_max_int Yes The \(\mid m \mid\) value of the most significant two-epoch pair using the integrated fluxes. Will be 0 if no significant pair.
vs_abs_significant_max_peak Yes The \(\mid V_s \mid\) value of the most significant two-epoch pair using the peak fluxes. Will be 0 if no significant pair.
m_abs_significant_max_peak Yes The \(\mid m \mid\) value of the most significant two-epoch pair using the peak fluxes. Will be 0 if no significant pair.

V and η Metrics

The \(V\) and \(\eta\) metrics are the same as those used by the LOFAR Transients Pipeline (TraP), for a complete description please refer to Swinbank et al. (2015). In the VAST Pipeline, the metrics are calculated twice, for both the integrated and peak fluxes.

\(V\) is the proportional flux variability of the source and is given by the ratio of the sample standard deviation (\(s\)) and mean of the flux, \(I\):

\[ V = \frac{s}{\overline{I}} = \frac{1}{\overline{I}} \sqrt{\frac{N}{N - 1}\left(\overline{I^{2}}-\overline{I}^{2}\right)}. \]

The \(\eta\) value is the significance of the variability, based on \(\chi^{2}\) statistics, and is given by:

\[ \eta = \frac{N}{N - 1}\left(\overline{wI^{2}} - \frac{\overline{wI}^{2}}{\overline{w}}\right) \]

where \(w\) is the uncertainty (\(e\)) in \(I\) of a measurement, and is given by \(w=\frac{1}{e}\).

Two-Epoch Metrics

Alternative variability metrics, \(V_s\) and \(m\), are also calculated which we refer to as the 'two-epoch metrics'. They are calculated for each unique pair of measurements assoicated with the source, with the most significant pair of values attached to the source (see section below). Please refer to Mooley et al. (2016) for further details.

Note

All the two-epoch pair \(V_s\) and \(m\) values for a run are saved in the output file measurement_pairs.parquet for offline analysis.

\(V_s\) is a statistic to compare the flux densities of a source between two-epochs and is given by:

\[ V_s = \frac{\Delta S}{\sigma} = \frac{S_1 - S_2}{\sqrt{\sigma_{1}^{2} + \sigma_{2}^{2}}} \]

where \(S\) is the flux and \(\sigma\) is the associated error. This metric is known to follow a Student-t distribution. Typically, in the literature, a source is defined as variable if this parameter is beyond the 95% confidence interval, i.e.:

\[ \mid V_s \mid \geq 4.3. \]

\(m\) is a moduluation index variable given by:

\[ m = \frac{\Delta S}{\overline{S}} \]

where \(\overline{S}\) is the mean of the flux densities \(S_1\) and \(S_2\). Typically, in the literature, the threshold for this value for a source to be considered variable is:

\[ \mid m \mid \gt 0.26, \]

which equates to a variability of 30%. However the user is free to set their own level to define variablity.

Significant Source Values

The \(V_s\) and \(m\) metrics of the 'maximum signficant pair' is attached to the source. The maximum significant pair is determind by selecting the most significant \(\mid m \mid\) value given a minimum \(V_s\) threshold which is defined in the pipeline configuration file variability.source_aggregate_pair_metrics_min_abs_vs:

config.yaml

variability:
  # Only measurement pairs where the Vs metric exceeds this value are selected for the
  # aggregate pair metrics that are stored in Source objects.
  source_aggregate_pair_metrics_min_abs_vs: 4.3

By default this value is set to 4.3. For example, if a source with three associatied measurements gave the following pair metrics:

Pair \(\mid V_s \mid\) \(\mid m \mid\)
A-B 4.5 0.1
B-C 2.5 0.05
A-C 4.3 0.4

then the A-C pair metrics are attached to the source as the most significant. This can be used to quickly determine significant two-epoch variability for a source. If there are no pair values above the minimum \(V_s\) threshold then these values attached to the source will be 0. The measurement_pairs.parquet file can be used to manually explore the measurement pairs if one wishes to lower the threshold.


Last update: April 27, 2021
Created: March 15, 2021