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Trace the Accretion Geometry of H 1743--322 with Type C Quasi-periodic Oscillations in Multiple Outbursts

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arxiv 2211.16679 v1 pith:FVZVUKJT submitted 2022-11-30 astro-ph.HE

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keywords analysisdifferencesdifferentoutburstphasecoronaldecayfindings
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We present a systematic analysis of type C quasi-periodic oscillation (QPO) observations of H 1743--322 throughout the Rossi X-ray Timing Explorer (RXTE) era. We find that, while different outbursts have significant flux differences, they show consistent positive correlations between the QPO fractional root-mean-square (rms) amplitude and non-thermal fraction of the emission, which indicate an independence of the intrinsic QPO rms on individual outburst brightness in H 1743--322. However, the dependence of the QPO rms on frequency is different between the outburst rise and decay phases, where QPO fractional rms of the decay phase is significantly lower than that of the rise phase at low frequencies. The spectral analysis also reveals different ranges of coronal temperature between the two outburst stages. A semi-quantitative analysis shows that the Lense-Thirring precession model could be responsible for the QPO rms differences, requiring a variable coronal geometric shape. However, the variable-Comptonization model could also account for the findings. The fact that the rms differences and the hysteresis traces in the hardness-intensity diagram (HID) accompany each other indicates a connection between the two phenomena. By correlating the findings with QPO phase lags and the quasi-simultaneous radio flux previously published, we propose there could be corona-jet transitions in H 1743--322 similar to those that have been recently reported in GRS 1915+105.

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  1. Phase-resolved QPO Analysis of GX 339-4: Improved Technique and Consistent Behaviors between QPOs and Broadband Noise

    astro-ph.HE 2026-08 conditional novelty 6.0 of 10

    Type-C QPOs and broadband noise in GX 339-4 show consistent phase-resolved spectral behavior, suggesting a shared physical origin and favoring corona oscillation models.

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