$30 off During Our Annual Pro Sale. View Details »

Comparing origins of low-frequency quasi-period...

Comparing origins of low-frequency quasi-periodic oscillations with spectral-timing

Presented at the 16th AAS High Energy Astrophysics Division (HEAD) meeting in Sun Valley, Idaho.

Abstract: The light curves of low-mass X-ray binaries show variability on timescales from milliseconds to months. The rapid (sub-second) variability is particularly interesting because it is thought to probe the inner region of the accretion disk and the central compact object. Observations suggest that different types of low-frequency quasi-periodic oscillations (QPOs) are associated with different emitting-region geometries (e.g., disk-like or jet-like) in the innermost part of the X-ray binary, that are varying possibly due to general relativistic precession. A new way to analyze QPOs is with spectral-timing, which seeks to investigate how matter behaves in the strong gravitational field around the compact object by causally linking the variations from different spectral components. We developed a technique for phase-resolved spectroscopy of QPOs, and are applying it to two types of low-frequency QPOs from the black hole X-ray binary GX 339-4. Over a QPO “period”, we find that the energy spectrum changes not only in normalization, but also in spectral shape. We can quantify how the spectral shape changes as a function of QPO phase, and the two different QPOs show markedly different spectral changes. The "Type B" low-frequency QPO shows evidence of a large-scale-height (jet-like) power-law- emitting precessing region, while in the same outburst the "Type C" low-frequency QPO shows evidence of a small-scale-height (disk-like) power-law-emitting precessing region. These interpretations can be used to look into the evolution of matter in the strong-gravity regime.

Dr. Abbie Stevens

August 24, 2017
Tweet

More Decks by Dr. Abbie Stevens

Other Decks in Science

Transcript

  1. Comparing origins of low-frequency quasi-periodic oscillations with spectral-timing Abigail Stevens,

    Phil Uttley University of Amsterdam 16th HEAD meeting [email protected] @abigailStev github.com/abigailStev      
  2. Low-mass X-ray binaries (LMXBs) Roche-lobe overflow Accretion disk Compact object

    Low-mass companion star Jet Figure: ESO/L. Calçada How does matter behave in strong gravitational fields? A.L. Stevens Ÿ U. Amsterdam      
  3. Low-mass X-ray binaries (LMXBs) Roche-lobe overflow Accretion disk Compact object

    Low-mass companion star Jet Figure: ESO/L. Calçada How does matter behave in strong gravitational fields? A.L. Stevens Ÿ U. Amsterdam 10 5 20 0.1 1 keV2 (Photons cm−2 s−1 keV−1) Energy (keV)      
  4. Low-mass X-ray binaries (LMXBs) Roche-lobe overflow Accretion disk Compact object

    Low-mass companion star Jet Figure: ESO/L. Calçada How does matter behave in strong gravitational fields? A.L. Stevens Ÿ U. Amsterdam 1700 1702 1704 1706 1708 1710 2000 4000 6000 8000 10 4 1.2×10 4 Count/sec Time (s) Start Time 12339 7:28:14:566 Stop Time 12339 7:29:32:683 Bin time: 0.7812E−02 s      
  5. Binary inclination dependence QPO amplitude: Schnittman, Homan & Miller 2006;

    Motta et al 2015 (figures); Heil et al 2015b 1 10 QPO centroid Frequency (Hz) 2 4 6 8 10 12 14 Fractional rms (%) 2 4 6 8 10 12 Fractional rms (%) QPO rms (HI) QPO rms (LI) QPO rms (HI) Average QPO rms (HI) QPO rms (LI) Average QPO rms (LI) 0.1 1.0 10.0 QPO centroid Frequency (Hz) 5 10 15 20 25 Fractional rms (%) 5 10 15 20 Fractional rms (%) QPO rms (HI) QPO rms (LI) QPO rms (HI) Average QPO rms (HI) QPO rms (LI) Average QPO rms (LI) 25 Type B’s: stronger face-on Type C’s: stronger edge-on (binary system inclination) A.L. Stevens Ÿ U. Amsterdam Lags: van den Eijnden et al 2017      
  6. Binary inclination dependence 1 10 QPO centroid Frequency (Hz) 2

    4 6 8 10 12 14 Fractional rms (%) 2 4 6 8 10 12 Fractional rms (%) QPO rms (HI) QPO rms (LI) QPO rms (HI) Average QPO rms (HI) QPO rms (LI) Average QPO rms (LI) 0.1 1.0 10.0 QPO centroid Frequency (Hz) 5 10 15 20 25 Fractional rms (%) 5 10 15 20 Fractional rms (%) QPO rms (HI) QPO rms (LI) QPO rms (HI) Average QPO rms (HI) QPO rms (LI) Average QPO rms (LI) 25 Type B’s: stronger face-on Type C’s: stronger edge-on (binary system inclination) A.L. Stevens Ÿ U. Amsterdam Want to study energy spectra on sub-QPO timescale •  Determine LF QPO emission mechanism •  Different mechanism for Type B vs Type C? QPO amplitude: Schnittman, Homan & Miller 2006; Motta et al 2015 (figures); Heil et al 2015b Lags: van den Eijnden et al 2017      
  7. × QPO model       A.L.

    Stevens Ÿ U. Amsterdam Stella & Vietri 1998; Fragile & Anninos 2005; Schnittman, Homan & Miller 2006; Ingram, Done & Fragile 2009; Ingram & van der Klis 2015; Fragile et al. 2016; Ingram et al. 2016a,b
  8. QPO model       A.L. Stevens

    Ÿ U. Amsterdam Stella & Vietri 1998; Fragile & Anninos 2005; Schnittman, Homan & Miller 2006; Ingram, Done & Fragile 2009; Ingram & van der Klis 2015; Fragile et al. 2016; Ingram et al. 2016a,b × Expect changing energy spectrum on sub-QPO timescale: •  Normalization •  Blackbody •  Iron line profile
  9. Phase-resolved spectroscopy Periodic signals: –  fold light curve at pulse

    period, stack signal in time domain –  need to know ephemerides of source Quasi-periodic signals: –  not coherent enough to fold light curve –  in time domain, signal would smear out! è  average together signals in frequency domain –  ephemerides not needed A.L. Stevens Ÿ U. Amsterdam      
  10. Phase-resolved spectroscopy Periodic signals: –  fold light curve at pulse

    period, stack signal in time domain –  need to know ephemerides of source Quasi-periodic signals: –  not coherent enough to fold light curve –  in time domain, signal would smear out! è  average together signals in frequency domain –  ephemerides not needed A.L. Stevens Ÿ U. Amsterdam       See also Miller & Homan 2005; Ingram & van der Klis 2015
  11. Phase-resolved spectroscopy No counts in this channel Energy- dependent cross-

    correlation function A.L. Stevens Ÿ U. Amsterdam      
  12. Phase-resolved spectroscopy Deviations from mean energy spectrum •  Spectral shape

    is varying with QPO phase! 10 5 20 0 0.5 keV2 (Photons cm−2 s−1 keV−1) Energy (keV) 0° 90° 180° 270° Type B A.L. Stevens Ÿ U. Amsterdam       Stevens & Uttley 2016
  13. Type B QPO spectral variations •  Blackbody variation leads the

    power-law variation by ~0.3 (110°) •  Power-law: 25% rms variation •  Blackbody: 1.4% rms variation A.L. Stevens Ÿ U. Amsterdam       Stevens & Uttley 2016
  14. Type B QPO interpretation Large scale height, weakly modulated illumination

    A.L. Stevens Ÿ U. Amsterdam      
  15. •  Different parameter- phase relationship •  Power-law: smaller variation (compared

    to Type B) •  Blackbody: larger variation Type C QPO spectral variations A.L. Stevens Ÿ U. Amsterdam       Stevens & Uttley, in prep
  16. Type C QPO interpretation Image: ESA/NASA/A. Ingram Small scale height,

    strongly modulated illumination A.L. Stevens Ÿ U. Amsterdam      
  17. Not just LF QPOS! Also kHz QPOs! Lower kHz QPO

    in 4U 1608-522      
  18. Not just LF QPOS! Also kHz QPOs! 10 5 20

    −0.4 −0.2 0 0.2 0.4 keV2 (Photons cm−2 s−1 keV−1) Energy (keV) Lower kHz QPO in 4U 1608-522       PRELIMINARY See poster J. Troyer Stevens, Altamirano & Uttley, in prep.
  19. NICER, eXTP, and STROBE-X Current limitation: •  RXTE cannot sample

    peaks of blackbodies •  Which blackbody varies? •  Further complications for NSs With NICER, eXTP SFA, STROBE-X XRCA/LAD: •  ~13ks simulations (no bkgd) can easily differentiate spectral models A.L. Stevens Ÿ U. Amsterdam      
  20. NICER, eXTP, and STROBE-X Current limitation: •  RXTE cannot sample

    peaks of blackbodies •  Which blackbody varies? •  Further complications for NSs With NICER, eXTP SFA, STROBE-X XRCA/LAD: •  ~13ks simulations can easily differentiate models A.L. Stevens Ÿ U. Amsterdam Fast time readout + CCD energy resolution + soft response è Resolve how the blackbody varies, where it’s located      
  21. Summary •  X-ray QPOs come from inner region of X-ray

    binaries •  Understand QPO origins with phase-resolved spectroscopy, especially with current and future instruments •  Type B QPO in GX 339—4: “Jet-like” precessing region •  Type C QPO in GX 339—4: “Disk-like” precessing region •  kHz QPO in 4U 1608-522: QPO emission coming from Comptonized region GitHub: abigailStev Email: [email protected] Twitter: @abigailStev ✉ A.L. Stevens Ÿ U. Amsterdam