HR observations for which non-standard data or bespoke settings were used to obtain improved Feature Finder (FF) products

1. Non-standard data

Highly Processed Data Products

• Highly Processed Data Products (HPDPs) are available for the repeated observations of SPIRE Spectrometer calibration sources presented in Hopwood et al. (2015) (arXiv:1502.05717). These HPDPs are SPIRE spectra that have been corrected for pointing offset and, where necessary, for source extent or high background emission.
• If a HPDP was used instead of the standard Herschel Science Archive product, this is reported under the metadata entry "hpdp" for the individual FF feature catalogues, and in the "HPDP" column of SAFECAT.
• The "Flag" column (in the FF HR Sparse point-source calibrated product pages) indicates whether a HPDP was used, with a "HPDP" flag.
• The HPDPs themselves can be accessed from the SPIRE-S calibration targets legacy data page.

Background Subtracted Spectra

• A number of high resolution (HR) observations were visually assessed as suffering from the same "double bump" systematic noise that is corrected in LR data (where it was more extreme and prevalent in a large fraction of LR observations).
• This issues is only seen in a small number of HR observations of faint point-like targets (84)
• The observations were corrected by subtracting a mean sum of smoothed off-axis detectors, as described in Hopwood et al. (2015).
• All BGS data were corrected using the HIPE Background Subtraction useful script in interactive mode.
• If BGS data were used instead of the standard Herschel Science Archive product, this is reported under the metadata entry "bgs" for the individual FF feature catalogues, and in the "BGS" column of SAFECAT.
• The "Flag" column (in the FF HR Sparse point-source calibrated product pages) indicates whether BGS data was used, with a "BGS" flag.
• The BGS spectra are available here

2. Bespoke FF settings

If, for a particular observations, non-default FF parameters were used or bespoke treatment was applied, this is indicated with a "1" in the "bespokeTreatment" column of hrSparseObservations_FF_1stRelease.csv, which lists all HR observations for which there is a set of FF products.

Fewer negative SNR thresholds

• By default, the FF iterates over a number of SNR thresholds when looking for peaks: +[100, 50, 30, 10, 5, 3] followed by -[100, 50, 30]
• For one particularly spectral rich observation (1342210847), if the default set of negative SNR thresholds are used, so many features are found there are not enough unmasked data points available for the final SNR estimates and many features are thus discarded
• This lost of features is prevented by omitting the -30 and -10 SNR thresholds

Final SNR estimate

• To optimise the final SNR estimate, the FF stipulates that the number of unmasked data points in the local region used to calculate the residual standard deviation must be at least 17 (5 GHz)
• If this condition is not met, then the local region around the fitted peak is widened.
• For the observations of two spectral rich sources (1342192834,1342197466) this condition is never matched for the majority of the features found, and so for the default settings, the majority of features are discarded. So in these two cases no minimum is set for the number of data points required for the the final SNR estimate to go ahead.

Features added by hand

• During the FF SNR threshold iterations, the SNR is taken using the spectral dataset "error" column.
• For a handful of observations this can lead to no significant SNR peak at the position of significant spectral peaks and the corresponding features are therefore never found by the FF, regardless of how low the SNR threshold drops
• A handful of missing significant features were added at the appropriate SNR threshold during the FF process for six observations: 1342197466, 1342248242, 1342216879, 1342197466, 1342193670, 1342210847