[論文レビュー] Time-Lag properties associated with LFQPO in X-ray variability classes of GRS 1915+105: Findings from AstroSat

Prajjwal Majumder, Broja Gopal Dutta+1 more|arXiv (Cornell University)|Mar 17, 2026

Astrophysical Phenomena and Observations被引用数 0

ひとこと要約

The paper analyzes low-frequency QPO time-lags in GRS 1915+105 using 441 ks of AstroSat data, linking LFQPO properties to spectral parameters and Comptonized flux across multiple variability classes.

ABSTRACT

We present a comprehensive analysis of Low Frequency Quasi-periodic Oscillation (LFQPO) associated time-lags in the persistently variable black hole binary GRS 1915+105 using 441 ks of extit{AstroSat} observations from March 2016 to March 2019. LFQPO frequency ($1.38-7.38$ Hz) are detected across the $θ$, $β$, $ρ$, and $χ$ classes, with the $χ$ class further subdivided into $χ_1$, $χ_2$, $χ_3$, and $χ_4$ based on spectro-temporal characteristics. Class transitions occur on timescales of a few hours, appearing either as a simultaneous increase in X-ray count rate and QPO frequency, or vice versa, indicating rapid changes in the accretion flow geometry. The $ ext{rms}_{ m QPO}$ increases with QPO frequency up to $\sim 3.4$ Hz and declines at higher frequencies, a trend similar to extit{RXTE} observations, where peak occurred at $\sim 2$ Hz. Spectro-temporal correlations reveal that increasing $F_{ m Comp}$ drives higher $ ext{rms}_{ m QPO}$ and decreases the soft-lag magnitude, while $ν_{ m QPO}$ and $Γ$ also decline, suggesting that the observed time lag may result from the combined effects of multiple physical mechanisms. The consistent increase of $ ext{rms}_{ m QPO}$ with $F_{ m Comp}$ provides clear evidence that modulated Comptonized photons enhance the rms power ($ ext{rms}_{ m QPO}$). Moreover, the soft-lag ($1.59-13.49$ ms) observed across all QPO frequencies, without the sign reversal at $\sim$ 2 Hz observed in extit{RXTE} observations, is interpreted within the framework of a dynamical accretion disk model around the black hole.

研究の動機と目的

• Investigate LFQPO-associated time-lags across different X-ray variability classes of GRS 1915+105.
• Sub-classify Chi class observations into finer categories (Chi1, Chi2, Chi3, Chi4) and study spectro-temporal correlations.
• Correlate timing properties (QPO frequency, rms, time-lags) with broad-band spectral parameters (disk and Comptonized flux, photon index, corona properties).
• Compare AstroSat results with previous RXTE findings to understand the evolution of lag behavior with QPO frequency and accretion geometry.

提案手法

• Perform timing analysis with 1 ms binned AstroSat LAXPC data to obtain PDS and identify LFQPOs (QPOs with Q≥3 and significance≥3).
• Compute time-lags using the complex cross-spectrum between 6–20 keV and 3–6 keV bands and average over the QPO FWHM.
• Extract energy-dependent QPO rms across seven energy bands (3–6, 6–9, 9–12, 12–15, 15–18, 18–21, 21–25 keV) to study spectral evolution of the QPO.
• Perform wide-band spectral fitting (0.7–60 keV) with constant × TBabs × (thcomp ⊗ diskbb) to derive Γ, kT_e, kT_in, F_comp, F_disc, and τ, and compute L_Edd and Comptonized flux fraction.
• Use SXT plus LAXPC data for broad-band (0.7–60 keV) spectroscopy, applying gain corrections and accounting for instrumental edges.]
• research_questions:["What are the LFQPO frequency ranges and rms amplitudes observed in GRS 1915+105 across AstroSat variability classes?","How do LFQPO time-lags depend on QPO frequency and energy, and how do they compare with RXTE results?","What spectro-temporal correlations exist between QPO properties (rms, lag, frequency) and spectral components (disk vs Comptonized flux, photon index, corona parameters)?","Does sub-classifying the Chi class reveal distinct timing/spectral behavior or corona geometry evolution?","What physical mechanisms can explain the observed lag behavior in the context of two-component advective flow and Comptonization?"]
• key_findings:[

Figure 1: The MAXI/GSC (2 $-$ 10 keV) and Swift/BAT ( $15-50$ keV) lightcurves of GRS 1915+105 from January 2016 to April 2019 are plotted in the unit of Crab, shown in the upper and middle panels respectively. The ‘Colour’ in the lower panel is defined as the ratio of BAT flux to the MAXI flux. The

実験結果

主な発見

Mission (ID)	ObsID	MJD	r_det (cts/s)	HR1	HR2	Class	ν_QPO (Hz)	FWHM (Hz)	rms_QPO (%)	Time-lag (ms)
AS1	T01_030T01_9000000358	57451.81	8336	0.68	0.12	θ	5.32	1.82	4.18	-8.80
AS8	T01_030T01_9000000358	57452.41	8445	0.68	0.13	χ3	5.61	0.45	4.18	-11.51
AS11	T01_030T01_9000000358	57452.62	4549	0.71	0.16	χ1	3.55	0.48	10.65	-7.00
AS18	T01_030T01_9000000358	57453.21	8351	0.69	0.13	θ	4.93	1.02	5.54	-9.07
AS25	T01_030T01_9000000358	57453.21	10664	0.67	0.11	χ3	7.38	1.32	3.37	-11.50

• LFQPOs are detected in 1.38–7.38 Hz across theta, beta, rho, and chi classes; chi is further subdivided into chi1–chi4.
• rms_QPO increases with QPO frequency up to ~3.4 Hz and then declines at higher frequencies, consistent with RXTE results where the peak is near ~2 Hz.
• Spectro-temporal correlations show that increasing F_Comp drives higher rms_QPO and lowers soft-lag magnitude, while ν_QPO and Γ also decline, suggesting multiple mechanisms shaping the lag.
• Soft-lags of 1.59–13.49 ms are observed across all QPO frequencies without the sign reversal around 2 Hz seen in RXTE data, interpreted via a dynamical accretion disk model.
• The study supports modulated Comptonized photons as a driver of rms power, evidenced by the consistent increase of rms_QPO with F_Comp.
• AstroSat results show a corona size and spectral parameter evolution correlating with QPO frequency, aligning with broader accretion-flow models

Figure 2: Lightcurve and CCD of variability classes ( $\theta$ , $\chi$ , $\beta$ , $\rho$ ) of the source GRS 1915+105 during LFQPO observations using AstroSat . The background subtracted and dead-time corrected 1s binned LAXPC lightcurves are plotted in the 3–60 keV energy range with CCD (top-righ