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We present a new method for obtaining photometric redshifts (photo-z) forsources observed by multiple photometric surveys using a combination(conflation) of the redshift probability distributions (PDZs) obtainedindependently from each survey. The conflation of the PDZs has severaladvantages over the usual method of modelling all the photometry together,including modularity, speed, and accuracy of the results. Using a sample ofgalaxies with narrow-band photometry in 56 bands from J-PAS and deeper grizyphotometry from the Hyper-SuprimeCam Subaru Strategic program (HSC-SSP), weshow that PDZ conflation significantly improves photo-z accuracy compared tofitting all the photometry or using a weighted average of point estimates. Theimprovement over J-PAS alone is particularly strong for i>22 sources, whichhave low signal-to-noise ratio in the J-PAS bands. For the entire i<22.5sample, we obtain a 64% (45%) increase in the number of sources with redshifterrors |Dz|<0.003, a factor 3.3 (1.9) decrease in the normalised medianabsolute deviation of the errors (sigma_NMAD), and a factor 3.2 (1.3) decreasein the outlier rate compared to J-PAS (HSC-SSP) alone. The photo-z accuracygains from combining the PDZs of J-PAS with a deeper broadband survey such asHSC-SSP are equivalent to increasing the depth of J-PAS observations by~1.2--1.5 magnitudes. These results demonstrate the potential of PDZ conflationand highlight the importance of including the full PDZs in photo-z catalogues.

The miniJPAS survey: Maximising the photo-z accuracy from multi-survey datasets with probability conflation