  We present an optimized way of producing the fast semi-analytical covariance
matrices for the Legendre moments of the two-point correlation function, taking
into account survey geometry and mimicking the non-Gaussian effects. We
validate the approach on simulated (mock) catalogs for different galaxy types,
representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release
1, used in 2024 analyses. We find only a few percent differences between the
mock sample covariance matrix and our results, which can be expected given the
approximate nature of the mocks, although we do identify discrepancies between
the shot-noise properties of the DESI fiber assignment algorithm and the faster
approximation used in the mocks. Importantly, we find a close agreement (<~ 5%
relative differences) in the projected errorbars for distance scale parameters
for the baryon acoustic oscillation measurements. This confirms our method as
an attractive alternative to simulation-based covariance matrices, especially
for non-standard models or galaxy sample selections, in particular, relevant to
the broad current and future analyses of DESI data.
