PyTICS: An Iterative Method for Photometric Lightcurve Intercalibration using Comparison Stars

Fuente: arXiv
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Autori principali: Vieliute, Roberta, Santisteban, Juan V. Hernández, Horne, Keith, Cornfield, Hannah
Natura: Preprint
Pubblicazione: 2025
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author Vieliute, Roberta
Santisteban, Juan V. Hernández
Horne, Keith
Cornfield, Hannah
author_facet Vieliute, Roberta
Santisteban, Juan V. Hernández
Horne, Keith
Cornfield, Hannah
contents Intensive reverberation mapping monitoring programs combine ground-based photometric observations from different telescopes, requiring intercalibration of lightcurves to reduce systematic instrumental differences. We present a new iterative algorithm to calibrate photometric time-series data of active galactic nuclei (AGN) using 100s of comparison stars on the same images, building upon the established method of ensemble photometry. The algorithm determines telescope-specific and epoch-specific correction parameters, and simultaneously computes a multi-component noise model to account for underestimated uncertainties based on the scatter in the comparison star data, effectively identifying problematic epochs, telescopes, and stars. No assumptions need to be made about the AGN variability shape, and the algorithm can in principle be applied to any astronomical object. We demonstrate our method on lightcurves taken with ten 1-m telescopes from the Las Cumbres Observatory (LCO) robotic telescope network. Comparing our results to other intercalibration tools, we find that the algorithm can more accurately quantify the uncertainties in the data. We describe additional corrections that can be made for particularly bluer AGNs like Fairall 9, arising due to systematic effects dependent on star colour.
format Preprint
id arxiv_https___arxiv_org_abs_2505_23328
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PyTICS: An Iterative Method for Photometric Lightcurve Intercalibration using Comparison Stars
Vieliute, Roberta
Santisteban, Juan V. Hernández
Horne, Keith
Cornfield, Hannah
Instrumentation and Methods for Astrophysics
Astrophysics of Galaxies
Intensive reverberation mapping monitoring programs combine ground-based photometric observations from different telescopes, requiring intercalibration of lightcurves to reduce systematic instrumental differences. We present a new iterative algorithm to calibrate photometric time-series data of active galactic nuclei (AGN) using 100s of comparison stars on the same images, building upon the established method of ensemble photometry. The algorithm determines telescope-specific and epoch-specific correction parameters, and simultaneously computes a multi-component noise model to account for underestimated uncertainties based on the scatter in the comparison star data, effectively identifying problematic epochs, telescopes, and stars. No assumptions need to be made about the AGN variability shape, and the algorithm can in principle be applied to any astronomical object. We demonstrate our method on lightcurves taken with ten 1-m telescopes from the Las Cumbres Observatory (LCO) robotic telescope network. Comparing our results to other intercalibration tools, we find that the algorithm can more accurately quantify the uncertainties in the data. We describe additional corrections that can be made for particularly bluer AGNs like Fairall 9, arising due to systematic effects dependent on star colour.
title PyTICS: An Iterative Method for Photometric Lightcurve Intercalibration using Comparison Stars
topic Instrumentation and Methods for Astrophysics
Astrophysics of Galaxies
url https://arxiv.org/abs/2505.23328