Spectral-timing the emission from close to black holes Phil Uttley University of Amsterdam with thanks to: Abigail Stevens, Jakob van den Eijnden, Adam Ingram and Julien Malzac
Spectral states: evolution of the central engine in BHXRBs Corona/disk luminosity Accretion rate Winds Jets Soft State Hard State We can understand the evolving structure broadly in terms of model-able spectral components
Dependence of variability on state: the rms amplitude and power spectrum Hard Intermediate Soft Broadband noise Broadband dominates Strong quasi- noise periodic dominates oscillations (QPOs)
SPECTRAL-TIMING WITH BROADBAND NOISE Constraining accretion and the coronal geometry
Power-law component: time-lags vs. frequency and energy Kotov et al. 2001 Lag vs frequency Lag vs energy • Variations of power-law emission in hard bands lag behind variations of power-law emission at softer energies • Time-lags increase towards lower frequencies (longer time-scales) • Lag vs energy dependence is approximately log-linear
Models for the broadband noise lags • Compton scattering (light-travel delays) in the corona/jet (e.g. Kazanas & Hua 1999, Reig et al. 2003) : • Can explain log-linear energy dependence þ (time-delay proportional to number of scatterings which scales with log(E)) • Cannot explain the large size of the lags: ý requires X-ray emitting region which is much too big (>10 3 R g ). • Propagation through an accretion flow with radially-dependent temperature profile (Kotov et al. 2001, Arévalo & Uttley 2006) : • Explains large lags and frequency þ dependence (longer time-scale variations travel from further out). ☐ • Cannot easily explain log-linear energy dependence (must hard-wire into model) ☐ • Requires a hot accretion flow: truncated disk with large inner radius???
Probing the disk lags with XMM-Newton GX 339-4 energy spectrum: lag vs frequency disk dominates below 1 keV Disk photons show very power spectrum different lag behaviour!
GX 339-4 hard state: the causal connection between disk and power-law variability The disk varies substantially before the power-law: no Uttley et immediate upscattering of al. 2011 disk photons by the corona. Therefore the corona must be central and compact (also consistent with reverberation measurements and microlensing of X-rays in AGN). But we still need to explain the lags between different power-law energies!
Modelling power-law variability driven by mdot fluctuations propagating through the disk Observer sees slow disk Corona sees a later, photon response, rising more rapid rise in before the power-law seed photons from responds Finally, the corona is the disk, causing heated by the mdot Impulse response: cooling of corona fluctuation reaching it ◆ 1 / 6 ✓ l seed Intensity Γ ∝ l heat (Beloborodov 2000) Power-law softens then hardens: hard lags! 0 Time
Large hard lags from a compact (few R g ) corona Lag of PL vs. dissipated (disk) flux (Uttley & We can now explain Malzac in the power-law lags in prep) terms of a varying disk, and log-linear Lag of 4 , 16 and 64 energy dependence! keV photons wrt 1 keV We still need to lag ∝ log( E 2 /E 1 ) explain the lag ‘steps’: multiple coronal components? GX 339-4 hard state, De Marco et al. 2015 2-9 vs. 0.5-1.5 keV 10-30 vs 2-9 keV
SPECTRAL-TIMING WITH QPOS Revealing GR effects with Doppler tomography of the accretion flow
Low-frequency QPOs • Low-frequency QPOs (~1-10’s Hz) are seen in the X-ray light curves of X-ray binaries • General relativistic precession of the central corona/hot flow? (Stella & Vietri 1998; Ingram, Done & Fragile 2009) • Use LF QPOs to probe strong-field general relativity -- How does matter behave in strong gravitational fields? • Basic prediction: should see quasiperiodic heating of the inner disk by the precessing flow (“lighthouse” effect)
Origin of the technique (or why it’s good to think about new missions … ): The method we use to study low-frequency QPOs was developed for the LOFT M3 mission proposal, to carry out Doppler tomography of high-frequency QPOs, associated with an orbiting hotspot in the inner disk. E (keV) → 0 5 10 15 Time (ms) → Now we apply the method for the first time to real (RXTE) data!
GX 339-4: Type B vs. Type C QPOs Here we use Type B LF QPOs from GX 339-4, to give a stronger, cleaner signal
(Quasi-)phase-resolved spectroscopy with the 2-D (energy-time) cross-correlation function Stevens & Uttley, MNRAS submitted No counts in this channel 8.15 ms )
QPO-Phase-Resolved Energy Spectra Deviations from mean spectrum, “fluxed” 0.5 keV 2 (Photons cm − 2 s − 1 keV − 1 ) • Spectral 0 shape is varying with QPO phase 5 10 20 Energy (keV)
Spectral fitting the phase-resolved spectra Used variations on: absorption × (power law ★ blackbody + iron line) Parameters that are Same 4 phases, as required by the data to previous, added vary: to mean 1. PL normalization (scattering fraction) 2. PL index 3. BB temperature
Parameter Variations with QPO Phase Parameter variations with relative QPO phase • Blackbody variation is ~0.3 out of phase with power law • Power law variation: ~25% fractional rms • Blackbody variation: ~1.4% fractional rms • Small BB variation implies only small variability of illumination of inner disk: large scale- height corona (jet-like?)
QPO amplitude depends on binary system inclination (Motta et al. 2015, see also Heil, Uttley & Klein-Wolt 2015) High inclination: more edge-on disks Low inclination: more face-on disks Type B Type C • Type C higher rms at higher inclination: disk-like power-law emitting region • Type B higher rms at lower inclination: jet-like power-law emitting region
Precession Model Interpretation a b c d
SHORT TERM QPO PHASE-LAG EVOLUTION Revealing a possible physical origin for coherence/ decoherence of QPOs
GRS 1915+105: QPO frequency depends on energy Qu et al. (2010) 2 possibilities: • Same intrinsic frequency. The frequency and energy-dependent amplitude causes apparent difference in frequency. Phase difference is constant. • Different intrinsic frequencies. Phase difference increases with time. (but it must reset?)
Optimal filtering to track QPO cycles
Coherent intervals Coherent Interval After filtering, it is clear that the QPO amplitudes are themselves modulated on a time-scale we call the ‘coherent interval’ since it corresponds also to the coherence-time of the QPO. We can use the CCF to measure the phase lag between hard and soft bands as a function of position in this interval … .
Result 1: phase lag ‘runs away’ during a coherent interval, then resets (van den Eijnden, Ingram & Uttley 2016) Phase lag [rad] Coherent Start End Interval Thus different energy bands do show an intrinsically different QPO frequency!
Result 2: the ‘run-away speed’ of phase-lag depends on the length of the coherent interval (van den Eijnden, Phase lag [rad] Ingram & Uttley 2016) 4 cycles 6 cycles 8 cycles 10 cycles QPO cycles since start of coherent interval The faster the run-away, the faster the QPO decoheres: the ‘quasi-period’ mechanism may be intrinsically linked to the run-away effect!
Interpretation: differential precession The runaway soft phase lags can be explained if the hotter, inner part of the flow has a higher precession frequency than the cooler, outer part: differential precession! The outcome of differential precession is a warped or ‘twisted’ disk: Figure from Armitage & Natarajan 1999 QPO rise and decay linked to growth of ‘twist’ in hot flow?
Summary • Spectral-timing offers a unique probe of the innermost regions of accreting black holes, allowing us to resolve scales which are nano-arcseconds on the sky. • We now have a ~complete, self-consistent model for the X-ray lags seen from the broadband noise, which can be explained by mdot variations propagating through the accretion disk which illuminates a central, compact corona. • Our technique for QPO phase-resolved spectroscopy reveals evidence for variable heating of the disk by a more vertically extended, precessing corona. • Short-time-scale measurements of type C QPO phase lag evolution in GRS 1915+105 shows evidence for differential precession of the inner hot-flow/corona, which may explain the formation mechanism of visible QPOs in terms of a ‘twisted’ flow.
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