Negative Lags on the Viscous Timescale in Quasar Photometry and Prospects for Detecting More with LSST

TL;DR

This paper explores the detection of long negative lags in quasar light curves caused by viscous timescale fluctuations, using models and simulations to forecast LSST's capability to study quasar disk structures.

Contribution

It derives a timescale for viscous long lags, evaluates detection methods, and forecasts LSST's potential to detect these lags in quasar light curves.

Findings

javelin and maximum-likelihood methods can detect long lags of several hundred days

LSST can potentially detect dozens to hundreds of long lags in quasar light curves

Detection of long lags informs about quasar disk vertical structure and scaling relations

Abstract

The variability of quasar light curves can be used to study the structure of quasar accretion disks. For example, continuum reverberation mapping uses delays between variability in short and long wavelength bands ("short" lags) to measure the radial extent and temperature profile of the disk. Recently, a potential reverse lag, where variations in shorter wavelength bands lag the longer wavelength bands at the much longer viscous timescale, was detected for Fairall 9. Inspired by this detection, we derive a timescale for these "long" negative lags from fluctuation propagation models and recent simulations. We use this timescale to forecast our ability to detect long lags using the Vera Rubin Legacy Survey of Space and Time (LSST). After exploring several methods, including the interpolated cross-correlation function, a Von-Neumann estimator, javelin, and a maximum-likelihood Fourier method, we find that our two main methods, javelin and the maximum-likelihood method, can together detect long lags of up to several hundred days in mock LSST light curves. Our methods work best on proposed LSST cadences with long season lengths, but can also work for the current baseline LSST cadence, especially if we add observations from other optical telescopes during seasonal gaps. We find that LSST has the potential to detect dozens to hundreds of additional long lags. Detecting these long lags can teach us about the vertical structure of quasar disks and how it scales with different quasar properties.