Within the BaStA project, we developed a procedure to correct the spectral indices from SDSS fiber spectra for aperture bias, calibrated on spatially resolved CALIFA integral-field observations. This is fully documented in Zibetti, Pratesi et al. (2026, A&A). Below you can find a summary of the method and the links to all necessary data to correct SDSS indices to aperture-free estimates.
Catalogs of aperture-corrected indices for the SDSS-DR7 dataset of Mattolini et al. (2025, A&A) are provided on the SDSS catalog page.
SDSS spectra are collected through a fixed 3″ fiber, which captures only the central region of nearby galaxies. Because stellar population gradients are common — galaxies tend to have older, more metal-rich centres — the fiber systematically misrepresents the integrated light, biasing the inferred stellar population parameters. BaStA corrects for this fiber-aperture bias before fitting, using a procedure calibrated on spatially resolved CALIFA integral-field observations (Zibetti et al. 2026).
The procedure is applied independently at each redshift on a grid spanning 0.005 < z < 0.4, using CALIFA galaxies as the calibration sample. For each galaxy and each index, the difference ΔX between the integrated and fiber values is modelled in two successive steps:
The systematic variation of ΔX across the plane of fiber-index versus total g−r colour is regularised using a 2D LOESS regression. This first-order correction removes most of the systematic bias — in the case of HδA+HγA, a median offset of ~1.4 Å is reduced to negligible levels.
Residual trends in the first-order corrected values are visible in the plane of Re versus absolute magnitude. A second LOESS regression in this plane provides a refinement correction that substantially reduces the tail and skewness of the residual distribution, even when the median bias is already small.
The correction functions are defined on the discrete set of CALIFA galaxies. Local smoothing and 3σ rejection loops regularize these functions and remove outlier CALIFA galaxies. To extend them to any point in the planes of fiber-index versus total g−r colour and of Re versus absolute magnitude (for any SDSS galaxy), a nearest-neighbour interpolation is used, with distances defined by an observationally motivated metric that weights each parameter by its measurement uncertainty:
1st-order plane — fiber index & g−r colour:
d1,i = √[ (Δg−r)2 / σ2g−r + (ΔX)2 / σ2X ]
2nd-order plane — size & luminosity:
d2,i = √[ (ΔMr)2 / σ2Mr + log2(R50,obs / R50,i) / σ2log R50 ]
The two correction terms are found independently — the nearest neighbour in the first-order plane need not be the same galaxy as in the second-order plane. This allows each correction to use the most relevant information available for each object.
At each step, a 3σ rejection algorithm removes outlier CALIFA galaxies from the calibration before the corrections are finalised. Typically only a handful of galaxies per index per redshift are excluded. Crucially, the scatter in the residuals after correction is smaller than the typical SDSS measurement uncertainties, meaning that aperture correction errors contribute negligibly to the final error budget.
For each spectral index (including some composite indexes), one FITS file is provided, named fiber_corr_SDSSfibz_{index_name}_SB235_FW16.fits, containing the aperture correction data computed from 375 CALIFA galaxies over a grid of 49 redshifts (0.005 < z < 0.4). SB235 indicate that the IFS footprint is defined by the 23.5 mag arcsec-2 isophote and the seeing of the SDSS spectroscopy is assumed as FWHM=1.6".
Each file has 6 HDUs: the redshift grid (HDU 0), the kpc/arcsec scale (HDU 1), the first- and second-order corrections (HDU 2–3, 375 galaxies × 49 redshifts each), the fiber index values used for interpolation (HDU 4), and a galaxy parameter table (HDU 5) with CALIFA IDs, integrated index, g−r colour, absolute magnitude, and effective radius for each calibration galaxy.
To apply the corrections, add CORR_1 + CORR_2 to the fiber-measured index, selecting the nearest neighbour in the calibration sample as described in the method section above.
In addition, we provide figures that illustrate the correction flow for each index, analogous to Figure 5 in Zibetti al. (2026).
Any work using all or part of these catalogs must reference the following papers:
An explicit acknowledgement to the BaStA dataset and a reference to the BaStA website is also appreciated.