Combining Visual and Photoelectric Observations of Semi-Regular Red Variables

TL;DR

This paper discusses integrating visual and photoelectric observations of semi-regular red variables, demonstrating how combining these data sources enhances light curve analysis despite systematic differences needing correction.

Contribution

It introduces a method for combining visual and photoelectric data for SR variables, extending observational coverage and improving data comprehensiveness.

Findings

Combined observations extend the light curve coverage.

Systematic differences between datasets require correction.

Demonstration with theta Aps data validates the approach.

Abstract

Combining visual observations of SR variables with measurements of them using a photoelectric photometer is discussed then demonstrated using data obtained for the bright, southern SR variable theta Aps. Combining such observations is useful in that it can provide a more comprehensive set of data by extending the temporal coverage of the light curve. Typically there are systematic differences in the visual and photometric datasets that must be corrected for.