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We present an extended validation of semi-analytical, semi-empiricalcovariance matrices for the two-point correlation function (2PCF) on simulatedcatalogs representative of Luminous Red Galaxies (LRG) data collected duringthe initial two months of operations of the Stage-IV ground-based Dark EnergySpectroscopic Instrument (DESI). We run the pipeline on multiple effectiveZel'dovich (EZ) mock galaxy catalogs with the corresponding cuts applied andcompare the results with the mock sample covariance to assess the accuracy andits fluctuations. We propose an extension of the previously developed formalismfor catalogs processed with standard reconstruction algorithms. We considermethods for comparing covariance matrices in detail, highlighting theirinterpretation and statistical properties caused by sample variance, inparticular, nontrivial expectation values of certain metrics even when theexternal covariance estimate is perfect. With improved mocks and validationtechniques, we confirm a good agreement between our predictions and samplecovariance. This allows one to generate covariance matrices for comparabledatasets without the need to create numerous mock galaxy catalogs with matchingclustering, only requiring 2PCF measurements from the data itself. The codeused in this paper is publicly available athttps://github.com/oliverphilcox/RascalC.

Validation of semi-analytical, semi-empirical covariance matrices for two-point correlation function for Early DESI data