Define Data Products: Catalogs

BASIC, NRAO Produced

As stated in the current version of the TIP (§ 7.1.5) the basic Single-Epoch Catalogs for an “object” (component) to contain:

  1. 1.

    Position, and uncertainty (likely centroid of I emission)

  2. 2.

    Peak Flux Density (continuum) in IQU, and uncertainty

  3. 3.

    Spectral Index at Peak (Stokes I) and uncertainty

  4. 4.

    Integrated Flux Density (continuum) in IQU, and uncertainty

  5. 5.

    Integrated Spectral Index (Stokes I) and uncertainty

  6. 6.

    Basic Shape information IQU (TBD, likely Gaussian fit parameters including deconvolved sizes)

For the linear polarization Stokes Q and U values, we will report these as the more traditional polarized flux density (amplitude of Q+iU) and polarization angle (\(0.5\,\tan^{-1}(U/Q)\)). It is also likely that for bright sources we will be able to compute IQU spectra (averaged over the source region). These would be extracted from the temporary full-resolution cubes. LR note: since this is only ”likely”, let’s drop the whole spectra thing, which increases the value of the enhanced products. We know NRAO can’t do this and there’s no such thing as high resolution cubes.
As defined in the TIP (§ 4.1.7), we consider the Basic Object Catalog entry for an “object” in the cumulative catalogs to contain:

  1. 1.

    Position, and uncertainty (likely centroid of I emission)

  2. 2.

    Peak Flux Density (continuum) in IQU, and uncertainty in I, Q+iU

  3. 3.

    Spectral Index at Peak (Stokes I) and uncertainty

  4. 4.

    Spectral Curvature at Peak (Stokes I) and uncertainty

  5. 5.

    Integrated Flux Density (continuum) in IQU, and uncertainty in I, Q+iU

  6. 6.

    Integrated Spectral Index (Stokes I) and uncertainty

  7. 7.

    Basic Shape information IQU (TBD, likely Gaussian fit parameters including deconvolved sizes)

  8. 8.

    Spectrum in IQU integrated over the source region (for bright sources) LR Note: described as ”likely” above. Eliminate here. I added it to image products, because they will be Faraday cubes.

Note that for the QU spectrum we do not promise to deliver robust rotation measures (RM) derived from RM synthesis, the exact characterization of that spectrum over the 2-4GHz band is TBD (e.g. it may be a simple single RM fit, or some polynomial for Q and U separately).LR Note: confusing and unnecessary and not promised, so drop this paragraph.

ENHANCED
    1. Gathering ”components” into ”sources”
        a) Source properties: total size, total flux, number of components, axial ratio, simple morphological classifier
    2. Optical/infrared cross-identifications (Bayesian, with one or more possibilities and their probabilities)
    3. Polynomial fit to total intensity spectrum per component (for complex spectra)
    4. Polarized intensity (and error) at peak of Faraday spectrum, or upper limit
    5. Rotation Measure (and error) for each total intensity ”component”
    6. Identification of multiple polarized components for each total intensity component
        a) RM, Q0, U0, P0
    7. Mean RM and \(\sigma_{RM}\) for each ”source”
    8. First order characterization of Faraday complexity (2 or more RMs along single line of sight)
        a) Multiple-component Q,U fitting
        b) Open-ended decomposition of Faraday spectrum (e.g., clean, wavelet, compressive sampling)
    9. Transient & Variable Source (Component?) Catalog / Web Resource
        a) A watch list of potential sources of interest over a wide range of categories
        b) Archival S Band fluxes where available?
        c) As quick as possible addition of the VLASS fluxes to the table