Shear LensMC Training

$SetSchemaPath she/euc-she-LensMcTraining.xsd

Data product name

$PrintDataProductName

Data product custodian

$PrintDataProductCustodian

Name of the Schema file

$PrintSchemaFilename

Last Edited for DPDD Version

1.1

Data product elements

$PrintDataProductElements

Processing Element(s) creating/using the data product

SHE

Processing function using the data product

SHE

Detailed description of the data product

An XML data product containing training data for the LensMC shear measurement algorithm. This algorithm requires prior knowledge on the unlensed distribution of galaxy shapes in order to properly estimate weights that will be associated to the shear catalogue. Additionally, further prior distributions on other parameters (e.g. galaxy size) could be derived as well. There is no particular constraint on what type of dataset should be used - most likely LensMC will get these priors directly from data - Euclid deep fields or HST images. It is evident that the same dataset could be used for training (estimation of weights and priors) and calibration (bias subtraction). The algorithm used for training (or calibration) should be the same of that applied to the wide survey. The resulting training catalogue will be stored in a fits table in exactly the same format as per the shear measurement catalogue and LensMC chain table.