Variability Timescale and Spectral Index of Sgr A* in the Near Infrared: Approximate Bayesian Computation Analysis of the Variability of the Closest Supermassive Black Hole
G. Witzel, G. Martinez, J. Hora, S. P. Willner, M. R. Morris, C., Gammie, E. E. Becklin, M. L. N. Ashby, F. Baganoff, S. Carey, T. Do, G. G., Fazio, A. Ghez, W. J. Glaccum, D. Haggard, R. Herrero-Illana, J. Ingalls, R., Narayan, and H. A. Smith

TL;DR
This study analyzes extensive near-infrared variability data of Sgr A* using a novel Bayesian method, revealing a characteristic timescale of about 4 hours, a featureless power spectral density down to 8.5 minutes, and spectral behavior indicating synchrotron emission.
Contribution
It introduces an approximate Bayesian computation approach for analyzing variability, providing new insights into Sgr A*'s timescales and spectral properties beyond traditional Fourier methods.
Findings
Characteristic coherence timescale of ~243 minutes
No detectable PSD features down to 8.5 minutes
NIR spectral index indicates bluer spectra during higher flux
Abstract
Sagittarius A* (Sgr A*) is the variable radio, near-infrared (NIR), and X-ray source associated with accretion onto the Galactic center black hole. We present an analysis of the most comprehensive NIR variability dataset of Sgr A* to date: eight 24-hour epochs of continuous monitoring of Sgr A* at 4.5 m with the IRAC instrument on the Spitzer Space Telescope, 93 epochs of 2.18 m data from Naos Conica at the Very Large Telescope, and 30 epochs of 2.12 m data from the NIRC2 camera at the Keck Observatory, in total 94,929 measurements. A new approximate Bayesian computation method for fitting the first-order structure function extracts information beyond current Fast Fourier Transformation (FFT) methods of power spectral density (PSD) estimation. With a combined fit of the data of all three observatories, the characteristic coherence timescale of Sgr A* is $\tau_{b} =…
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.
