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Quasi-Periodic Oscillations in Black Hole Candidates as an Indicator of Transition Between Low and High States

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arxiv astro-ph/9807235 v1 pith:WNZ3LOR4 submitted 1998-07-23 astro-ph

classification astro-ph
keywords observedspectraltransitionvariabilitybhcshardhardnesshigh
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By comparing positions on a spectral color-color diagram from 10 black hole candidates (BHCs) observed with Ginga (1354-64, 1826-24, 1630-47, LMC X-1, LMC X-3, GS 2000+25, GS 2023+33, GS 1124-68, Cyg X-1, and GX 339-4) with the observed broad-band noise (0.001-64 Hz; BBN) and quasi-periodic oscillation (QPO) variability, we find that the so-called ``Very High State'' is spectrally intermediate to the Soft/High-State and Hard/Low-State. We find a transition point in spectral hardness where the dependence of the BHC QPO centroid frequency (of GS 1124-68 and GX 339-4) on spectral hardness switches from a correlation to an anti-correlation; where the BBN variability switches from High-State to Low-State; and where the spectral hardness of the QPO relative to that of the BBN variability is a maximum. This coincidence of changing behavior in both the QPO and the broad-band variability leads us to hypothesize that the QPO is due to interaction between the physical components which dominate the behaviors of BHCs when they occupy the Hard/Low and Soft/High States. We conclude that these QPO should be observed from BHCs during transition between these two states. Comparison with QPO and BBN behavior observed during the 1996 transition of Cyg X-1 supports this hypothesis. We also report 1-3 Hz QPO observed in GS 2000+25 and Cyg X-1 in the Hard/Low State, and we compare these to the QPO observed in GS 1124-68 and GX 339-4.

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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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