Clustering redshift distribution calibration of weak lensing surveys using the DESI-DR1 spectroscopic dataset

We estimate the source redshift distribution of current weak lensing surveys by applying the clustering-based redshift calibration technique, using the galaxy redshift sample provided by the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1). We cross-correlate the Bright Galaxy Survey (BGS), Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) from DESI, within the redshift range \(0.1 < z < 1.6\), with overlapping tomographic source samples from the Dark Energy Survey (DES), Kilo-Degree Survey (KiDS), and Hyper Suprime-Cam (HSC) survey. Using realistic mock catalogues, we test the stability of the clustering redshift signal to fitting scale, reference-sample choice, and the evolution of source galaxy bias. We calibrate a source galaxy bias correction from simulations with conservative (factor-of-two inflated) priors to account for modelling uncertainties, and we explicitly model and marginalise over magnification contributions, which become non-negligible at \(z \gtrsim 1\) due to the depth of the DESI ELG sample. We then compare the resulting bias-weighted redshift distributions to previously calibrated redshift distributions from the literature, based on self-organising map (SOM) techniques, finding agreement within uncertainties for all surveys and tomographic bins. Our results demonstrate that clustering redshifts enabled by DESI’s unprecedented spectroscopic sample provide a robust, complementary, and independent constraint capable of reducing one of the dominant systematic uncertainties in weak lensing cosmology.