ELEPHANT: ExtragaLactic alErt Pipeline for Hostless AstroNomical Transients

This repository contains the ELEPHANT pipeline described in the Pessi et al., 2024.

To use the pipeline, you can clone this repository with the command below

git clone https://github.com/COINtoolbox/extragalactic_hostless.git

After cloning install the necessary packages with the command below

pip install -r requirements.txt

The pipeline parameters can be configured in pipeline_config.json file. A subset of sample data used in the paper is available in data folder. The entire dataset used in the paper can be downloaded from the Fink broker data server

{
    "parquet_files_list": path to downloaded input parquet files (An example file available in data folder)
    "save_directory": path to a folder to save results
    "fwhm_bins":  A list of FWHM bin values, default is [1.0, 2.0, 3.0]
    "image_shape": Input stamps shape
    "is_save_stacked_images": If true, stacked images are saved in results "save_directory" folder,
    "sigma_clipping_kwargs": kwargs parameters for astropy sigma_clip function
    "hostless_detection_with_clipping": sigma clipping hosteless detection threshold parameters defined in pixels
    "number_of_processes": Number of workers used in pythong multiprocessing to process files in parallel
}

To run the pipeline use the command below

python run_pipeline.py

The pipeline generates a result parquet file with the following columns for each input parquet file

• b:cutoutScience_stampData_stacked: stacked science images
• b:cutoutTemplate_stampData_stacked: stacked template images
• b:cutoutDifference_stampData_stacked: stacked difference images
• science_clipped: stacked sigma clipped science image
• template_clipped: stacked sigma clipped template image
• number_of_stamps_in_stacking: number of images used for stacking after FWHM stamp preprocessing
• is_hostless_candidate_clipping: True, if the candidate flagged as hostless by sigma clipping approach
• distance_science: distance from transient to the nearest mask in pixels
• kstest_SCIENCE_N_statistic: Kolmogorov-Smirnov test statistic value for N x N cutout science image
• kstest_SCIENCE_N_pvalue: Kolmogorov-Smirnov test p-value for N x N cutout science image
• kstest_TEMPLATE_N_statistic: Kolmogorov-Smirnov test statistic value for N x N cutout template image
• kstest_TEMPLATE_N_pvalue: Kolmogorov-Smirnov test p-value for N x N cutout template image

Acknowledgements

The project is a result from COIN Residence Program #7, Portugal, 2023, held in Lisbon, Portugal, from 9 to 16 September 2023 and supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) through the Strategic Programme UIDP/FIS/00099/2020 and UIDB/FIS/00099/2020 for CENTRA. The Cosmostatistics Initiative (COIN) is an international network of researchers whose goal is to foster interdisciplinarity inspired by astronomy.