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arXiv · 2504.14193

Decoding the Origin of HFQPOs of GRS 1915+105 during 'Canonical' Soft States: An In-depth View using Multi-mission observations

Abstract

We present a comprehensive analysis of the 'canonical' soft state ($\gamma$, $\delta$, and $\phi$ spectral variability classes) of the black hole binary GRS 1915+105, using RXTE, AstroSat, and NuSTAR data from 1996 to 2017 to investigate the origin of High Frequency Quasi-periodic Oscillations (HFQPOs). Our findings reveal that HFQPOs occur only in the $\gamma$ and $\delta$ classes, with frequencies of $65.07-71.38$ Hz and are absent in the $\phi$ class. We observe an evolution of time-lag from hard-lag (1.59$-$7.55 ms) in RXTE to a soft-lag (0.49$-$1.68 ms) in AstroSat observations. Wide-band (0.7$-$50 keV) spectral modelling suggests that HFQPOs are likely observed with a higher covering fraction ($f_{cov} \gtrsim 0.5$), i.e., the fraction of seed photons being Comptonized in the corona, enhanced Comptonized flux ($\sim$ 38%), and lower optical depth ($\tau \lesssim 8.5$ ) in contrast to observations where HFQPOs are absent. We observed similar constraints for observing HFQPOs during an inter-class ($\phi \rightarrow \delta$) transition as well as in a few intra-class ($\delta \rightarrow \delta$) variations. We also find that the time-lag decreases as $\tau$ increases, indicating that a higher $\tau$ reduces Compton up-scattering, thereby decreasing the hard-lag. Interestingly, in RXTE observations, the hard-lag ($\sim$ 7 ms) gradually decreases as optical depth and Comptonization ratio increases, eventually becoming a soft-lag ($\sim$1 ms) in AstroSat observations. These constraints on spectro-temporal parameters for the likelihood of observing HFQPOs support a 'compact' coronal oscillation mechanism for generating HFQPOs, which we attempt to explain within the framework of a possible accretion scenario.

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Prajjwal Majumder, Broja G. Dutta, Anuj Nandi. 2025-04-19. Decoding the Origin of HFQPOs of GRS 1915+105 during 'Canonical' Soft States: An In-depth View using Multi-mission observations. https://arxiv.org/abs/2504.14193

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