Long term variability of Cygnus X-1. VIII. A spectral-timing look at low energies with NICER
Ole K\"onig, Guglielmo Mastroserio, Thomas Dauser, Mariano M\'endez,, Jingyi Wang, Javier A. Garc\'ia, James F. Steiner, Katja Pottschmidt, Ralf, Ballhausen, Riley M. Connors, Federico Garc\'ia, Victoria Grinberg, David, Horn, Adam Ingram, Erin Kara, Timothy R. Kallman

TL;DR
This study uses NICER data to analyze the spectral-timing behavior of Cygnus X-1 at energies below 1 keV, revealing distinct physical processes and a universal low-energy timing phenomenon across black hole binaries.
Contribution
It identifies and characterizes a low-energy timing phenomenon linked to Lorentzian components, providing new insights into the physical processes in accreting black hole systems.
Findings
The power spectrum decomposes into two Lorentzians with a transition at 1 Hz.
A low-energy timing phenomenon involves an abrupt lag change and reduced coherence.
The phenomenon is common in accreting black hole binaries and varies with spectral state.
Abstract
The Neutron Star Interior Composition Explorer (NICER) monitoring campaign of Cyg X-1 allows us to study its spectral-timing behavior at energies keV across all states. The hard state power spectrum can be decomposed into two main broad Lorentzians with a transition at around 1 Hz. The lower-frequency Lorentzian is the dominant component at low energies. The higher-frequency Lorentzian begins to contribute significantly to the variability above 1.5 keV and dominates at high energies. We show that the low- and high-frequency Lorentzians likely represent individual physical processes. The lower-frequency Lorentzian can be associated with a (possibly Comptonized) disk component, while the higher-frequency Lorentzian is clearly associated with the Comptonizing plasma. At the transition of these components, we discover a low-energy timing phenomenon characterized by an abrupt lag…
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.
