# Robbie: A Batch Processing Work-flow for the Detection of Radio Transients andVariables

## TL;DR

Robbie is a flexible, modular workflow designed for detecting and analyzing radio transients and variability in image data, emphasizing reproducibility and adaptability across different datasets.

## Contribution

It introduces a modular, open-source batch processing workflow for radio transient detection that can be customized for various data types and analysis needs.

## Key findings

- Successfully applied to real and simulated data
- Demonstrates flexibility and reproducibility
- Open-source implementation on GitHub

## Abstract

We present Robbie: a general work-flow for the detection and characterization of radio variability and transient events in the image domain. Robbie is designed to work in a batch processing paradigm with a modular design so that components can be swapped out or upgraded to adapt to different input data, whilst retaining a consistent and coherent methodological approach. Robbie is based on commonly used and open software, and is encapsulated in a Makefile to aid portability and reproducibility. In this paper wedescribe the methodology behind Robbie, and demonstrate its use on real and simulated data. Robbie is available on GitHub.