Speaker
Description
To obtain final results one needs to perform data corrections for detector inefficiencies. Simple multiplication by a constant factor or bin-by-bin weighing does not account for event migration or event losses and gains. The deconvolution of distributions is provided in the Unfolding method by RooUnfold. This poster shows several tests of applying Unfolding techniques to 1d- and 2d-dimensional distributions on MC-generated data in NA61/SHINE acceptance. Results for the scaled variance of multiplicity distributions and strongly intensive quantities $\Delta[P_T, N]$, $\Sigma[P_T, N]$, and $\Sigma[N_F, N_B]$ are presented.
This work is supported by the Russian Science Foundation under grant 17-72-20045. We thank all the members of the CERN NA61/SHINE Collaboration for the support and help.
