The NICER "Reverberation Machine": A Systematic Study of Time Lags in Black Hole X-Ray Binaries
Jingyi Wang, Erin Kara, Matteo Lucchini, Adam Ingram, Michiel van der, Klis, Guglielmo Mastroserio, Javier A. Garc\'ia, Thomas Dauser, Riley, Connors, Andrew C. Fabian, James F. Steiner, Ron A. Remillard, Edward M., Cackett, Phil Uttley, Diego Altamirano

TL;DR
This study systematically analyzes NICER data to detect and understand reverberation lags in black hole X-ray binaries, revealing their evolution during state transitions and implications for coronal geometry.
Contribution
It provides the first comprehensive detection of reverberation lags in 8 sources, expanding the sample and analyzing their evolution during outbursts, offering new insights into accretion physics.
Findings
Reverberation lags increase and dominate at lower frequencies during state transitions.
Lag evolution indicates the corona may be the base of a jet that expands or ejects.
In the hard state, lags shorten even as QPO frequencies rise.
Abstract
We perform the first systematic search of all NICER archival observations of black hole (and candidate) low-mass X-ray binaries for signatures of reverberation. Reverberation lags result from the light travel time difference between the direct coronal emission and the reflected disk component, and therefore their properties are a useful probe of the disk-corona geometry. We detect new signatures of reverberation lags in 8 sources, increasing the total sample from 3 to 11, and study the evolution of reverberation lag properties as the sources evolve in outbursts. We find that in all of the 9 sources with more than 1 reverberation lag detection, the reverberation lags become longer and dominate at lower Fourier frequencies during the hard-to-soft state transition. This result shows that the evolution in reverberation lags is a global property of the state transitions of black hole…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
