TL;DR
This paper develops statistical proxies to evaluate how different survey cadences affect AGN variability measurements, aiding in optimizing future time-domain survey strategies for better AGN analysis.
Contribution
It introduces new regression-based proxies to predict the impact of survey cadence on AGN variability observables, considering different variability levels and redshifts.
Findings
Regression models predict similar cadences for time-lags and periodicity detection.
Cadences for oscillation detection vary with variability amplitude.
Dense, homogeneous cadences yield more consistent SF behavior.
Abstract
Motivated by upcoming photometric and spectroscopic surveys (Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Manuakea Spectroscopic Explorer), we design the statistical proxies to measure the cadence effects on active galactic nuclei (AGN) variability-observables (time-lags, periodicity, and structure-function (SF)). We constructed a multiple-regression model to statistically identify the cadence-formal error pattern knowing AGN time-lags and periodicity from different surveys. We defined the simple metric for the SF's properties, accounting for the 'observed' SF's deviation relative to those obtained from the homogenously-sampled light curves. We tested the regression models on different observing strategies: the optical dataset of long light-curves of eight AGN with peculiarities and the artificial datasets based on several idealized and LSST-like cadences. The SFs…
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