DHARA: Data Handling and Automated Reduction pipeline for AIMPOL

Abstract

We present an automated data-reduction and analysis for optical linear polarimetric data obtained from a dual-beam polarimeter. The pipeline is optimized for observations acquired with the ARIES Imaging POLarimeter mounted at the Cassegrain focus of the 1.04-m Sampurnanand Telescope at ARIES. It is implemented using interactive Python routines that process raw images to derive the Stokes parameters, from which the degree of polarization and polarization angle are computed along with their uncertainties. The pipeline framework is designed to handle the reduction of both single-source and crowded-field observations. The identification of extraordinary (e-ray) and ordinary (o-ray) image pairs is a crucial step and is performed using different strategies for single-source and crowded-field data, while subsequent stages, such as photometric and polarimetric analysis, follow a common procedure. We validate the pipeline using observations of polarized standard stars acquired over multiple epochs between 2017 to 2025, and compare the results with values reported in the literature. To demonstrate the applicability of the pipeline to crowded-field observations, we apply it to polarimetric data of the Alessi~1 open cluster and compare with previously published results derived using traditional reduction methods. In both cases, the polarization parameters derived using the pipeline agree with literature values within $2σ$ uncertainties. Although developed for AIMPOL, the pipeline is readily adaptable to any dual-channel imaging polarimeter in which the e-ray and o-ray images are recorded in a FITS image from a single CCD.