We derive a sample of photometric redshift estimates for objects in the DELVE DR2 catalog using a Mixture Density Network (MDN) trained on griz magnitudes and colors. This network outputs the weights, means, and standard deviations of 20 Gaussian distributions, which are then combined into a single probability density function (PDF) from which samples of the photo-z can be drawn. The resulting photo-z information can be accessed using the interfaces described on the Data Access page, and the delve_dr2.photoz table can be browsed using the Data Lab table browser.
More information about the construction and quality of this value added catalog can be found below.
The MDN photo-z estimator was trained on a sample of objects with measured spectroscopic redshifts. This spec-z catalog was assembled by cross-matching sources from DELVE DR2 with several spectroscopic catalogs: SDSS, 2DF, 6DF, VIPERS, GAMA, 2dFLens, DES_AAOMEGA, DES_IMACS, WIGGLEZ, DEEP2, 3D-HST, VVDS, CLASH-VLT, ACES, N17B331, SAGA, SPT_GMOS, UDS, C3R2, ATLAS, , VANDELS, SPARCS, GLASS, CDB, ELG FIGS, VUDS, ZFIRE, and MOSFIRE.We selected the matched objects that remained after a set of cuts.
- SNR > 5 in the g band and SNR > 3 in the riz bands (when each band was available).
- g < 22.5
- 0.01 < z-spec < 2
- We removed objects with 178 < RA < 182 and Dec < 5 due to issues in a preliminary version of the DELVE catalog.
- Objects with g, r, i and z measurements available were requited to have: (g-r) < 4, -1 < (r-i) < 4, and -1 < (i-z) < 4
- Objects with just g, r and i measurements available were required to have: (g-r) < 4 and -1 < (r-i) < 4
- 13.478 < g < 22.500
- 12.634 < r < 23.297
- 12.270 < i < 22.751
- 12.016 < z < 22.859
Performance MetricsWe used point estimates (taking the most probable value from the PDF) to build our metrics (“point-like metrics”). We define the following metrics:
- The photo-z bias is defined as Δz = zphot - zspec.
- The median bias, median(Δz), is useful for identifying possible systematic effects in the redshift estimation
- The outlier fraction is defined as |Δz|/( 1 + zspec) > 0.15 within a given redshift bin.
- The normalized median absolute deviation measures the dispersion of the bias and is defined as σNMAD = 1.48 × median(| (Δz - median(Δz)) / (1 + zspec) |)
- The relative errors are defined as mean( Δz / (1 + z) ) within photo-z intervals of 0.05.