Ilya Mandel Seminar NITheP UKZN 20 Jan 2014

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TITLE: GWastrophysics of compact binaries

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Ilya Mandel Seminar NITheP UKZN 20 Jan 2014

  1. 1. LIGO GWastrophysics of compact binaries Ilya Mandel (University of Birmingham) January 20, 2014 UKZN, Durban
  2. 2. UKZN: Jan 20, 2014 2
  3. 3. UKZN: Jan 20, 2014 Gravitational Waves  Ripples in spacetime:  Caused by time-varying mass quadrupole moment; GW frequency is twice the orbital frequency for a circular, non-spinning binary  Huge amounts of energy released: GW energy output of SMBH binary greater than EM radiation from entire galaxy over a Hubble time 3
  4. 4. UKZN: Jan 20, 2014 4
  5. 5. UKZN: Jan 20, 2014 Indirect observations of GWs  PSR 1913+16  Discovered in 1974  GR precession of 4.2 deg/ yr (vs. 43 arcsec/century for Mercury, out of 5600) 5 J0737-3039A: [Kramer et al., 2005]
  6. 6. UKZN: Jan 20, 2014 Opportunity and Challenge GWs carry a lot of energy, but interact weakly: can pass through everything, including detectors! Michelson-type interferometers 6
  7. 7. UKZN: Jan 20, 2014 Detection Challenges 7
  8. 8. UKZN: Jan 20, 2014 Detection Challenges 8
  9. 9. UKZN: Jan 20, 2014 LIGO Noise Spectrum 9
  10. 10. UKZN: Jan 20, 2014 A few initial LIGO/Virgo highlights  GRB070201 overlapped Andromeda (at 770 Mpc); binary coalescence in M31 excluded at >99% confidence [LSC+Hurley, 2008, ApJ 681 1419]  Best upper limit (Ω0 < 6.9 x 10-6) on stochastic background energy density at 100 Hz [LVC, 2009, Nature 460 990]  Beat spindown limit on emission from Crab (<0.02 E) and Vela (<0.45 E) pulsars, [LVC, 2008, ApJL 683 45; 2011, ApJ 737 93] 10 M31, GRB 070201
  11. 11. UKZN: Jan 20, 2014 Types of GW sources  Continuous sources [sources with a slowly evolving frequency]: e.g., non-axisymmetric neutron stars, slowly evolving binaries  Coalescence sources [known waveforms, matched filtering]: compact object binaries  Burst events [unmodeled waveforms]: e.g., asymmetric SN collapse, cosmic string cusps  Stochastic GW background [early universe]  ??? [expect the unexpected] 11
  12. 12. UKZN: Jan 20, 2014 Predicting merger rates 12 Method Strength Weakness Direct extrapolation from observed Galactic binaries Most direct available probe; ~10 known (~5 merging) Galactic binary pulsars Low statistics, poorly known selection effects, only relevant for BNS systems
  13. 13. UKZN: Jan 20, 2014 Predicting merger rates 13 Method Strength Weakness Direct extrapolation from observed Galactic binaries Most direct available probe; ~10 known (~5 merging) Galactic binary pulsars Low statistics, poorly known selection effects, only relevant for BNS systems Extrapolation from short GRB rates Potentially direct probe of mergers involving NS out to large distances (z~2) Uncertain provenance, ill- constrained beaming factors and selection effects
  14. 14. UKZN: Jan 20, 2014 Predicting merger rates 14 Method Strength Weakness Direct extrapolation from observed Galactic binaries Most direct available probe; ~10 known (~5 merging) Galactic binary pulsars Low statistics, poorly known selection effects, only relevant for BNS systems Extrapolation from short GRB rates Potentially direct probe of mergers involving NS out to large distances (z~2) Uncertain provenance, ill- constrained beaming factors and selection effects Population synthesis of isolated binaries
  15. 15. UKZN: Jan 20, 2014 Population synthesis models  No observed NS-BH or BH-BH binaries  Predictions based on population-synthesis models for isolated binary evolution with StarTrack [Belczynski et al., 2005, astro-ph/ 0511811] or similar codes  Many poorly constrained parameters: SN kicks, stellar winds, mass transfer efficiency, common envelope physics [O’Shaughnessy et al., 2005 ApJ 633 1076; 2008 ApJ 672 479]  Also: metallicity variations, SN mechanism/fallback, fate of Hertzsprung gap donor in common envelope... [Dominik et al., 2012 ApJ, 759, 52] 15
  16. 16. UKZN: Jan 20, 2014 Population synthesis predictions 16 [Dominik et al., 2012 ApJ, 759, 52]
  17. 17. UKZN: Jan 20, 2014 Predictions of component mass distributions 17 [Dominik et al., 2012 ApJ, 759, 52]
  18. 18. UKZN: Jan 20, 2014 Predicting merger rates 18 Method Strength Weakness Direct extrapolation from observed Galactic binaries Most direct available probe; ~10 known (~5 merging) Galactic binary pulsars Low statistics, poorly known selection effects, only relevant for BNS systems Extrapolation from short GRB rates Potentially direct probe of mergers involving NS out to large distances (z~2) Uncertain provenance, ill- constrained beaming factors and selection effects Population synthesis of isolated binaries Applies to all binary types, creates models for future astrophysical inference A number of poorly known input parameters (SNe kicks, winds, common envelope)
  19. 19. Source Rlow Rhigh NS-NS (MWEG 1 Myr 1 ) 1 1000 NS-BH (MWEG 1 Myr 1 ) 0.05 100 BH-BH (MWEG 1 Myr 1 ) 0.01 30 UKZN: Jan 20, 2014 Merger Rate Predictions 19 S6 /VSR2,3 Upper Limits Predicted rates [Abadie et al., 2011] [Abadie et al., CQG 27:173001,2010]
  20. 20. UKZN: Jan 20, 2014 Predicting merger rates 20 Method Strength Weakness Direct extrapolation from observed Galactic binaries Most direct available probe; ~10 known (~5 merging) Galactic binary pulsars Low statistics, poorly known selection effects, only relevant for BNS systems Extrapolation from short GRB rates Potentially direct probe of mergers involving NS out to large distances (z~2) Uncertain provenance, ill- constrained beaming factors and selection effects Population synthesis of isolated binaries Applies to all binary types, creates models for future astrophysical inference A number of poorly known input parameters (SNe kicks, winds, common envelope) Forward evolution of observed X-ray binaries Combination of observations and population synthesis Uncertain selection effects, mass measurements, and modeling assumptions
  21. 21. UKZN: Jan 20, 2014 Predicting merger rates 21 Method Strength Weakness Direct extrapolation from observed Galactic binaries Most direct available probe; ~10 known (~5 merging) Galactic binary pulsars Low statistics, poorly known selection effects, only relevant for BNS systems Extrapolation from short GRB rates Potentially direct probe of mergers involving NS out to large distances (z~2) Uncertain provenance, ill- constrained beaming factors and selection effects Population synthesis of isolated binaries Applies to all binary types, creates models for future astrophysical inference A number of poorly known input parameters (SNe kicks, winds, common envelope) Forward evolution of observed X-ray binaries Combination of observations and population synthesis Uncertain selection effects, mass measurements, and modeling assumptions Dynamical formation in dense environments Independent scenario, less sensitive to binary evolution Poorly known dynamics of globular and nuclear clusters
  22. 22. NG (L10) = 4 3 Dhorizon Mpc ⇥3 (2.26) 3 (0.02) ˙N = R NG (Dhorizon) 8 UKZN: Jan 20, 2014 LIGO sensitivity |˜h(f)| = 2/D (5µ/96)1/2 (M/⇥2 )1/3 f 7/6 (merger rate) = (merger rate per L10) * (NG in L10's) ⇥ 4 fISCO 0 |˜h(f)|2 Sn(f) df 1/2.26 -- sky and orientation averaging; 0.02 L10 per Mpc3 S4 S5 aLIGO [plot from Kopparapu et al., 2008 ApJ 675 1459 ] 22
  23. 23. 10 1 10 2 10 3 10 −23 10 −22 10 −21 10 −20 10 −19 f, Hz Sn(f),1/ √ Hz Initial LIGO Initial Virgo Advanced LIGO Advanced Virgo IFO Source ˙Nlow ˙Nhigh yr 1 yr 1 NS-NS 2 ⇥ 10 4 0.2 Initial NS-BH 7 ⇥ 10 5 0.1 BH-BH 2 ⇥ 10 4 0.5 NS-NS 0.4 400 Advanced NS-BH 0.2 300 BH-BH 0.4 1000UKZN: Jan 20, 2014 Merger and Detection Rates 23 [IM & O’Shaughnessy, 2010, CQG 27 114007; Abadie et al., CQG 27:173001, 2010, arXiv:1003.2480]
  24. 24. UKZN: Jan 20, 2014 Advanced LIGO overview What is Advanced? EOMLaser Parameter Initial LIGO Advanced LIGO Input Laser Power 10 W (10 kW arm) 180 W (>700 kW arm) Mirror Mass 10 kg 40 kg Interferometer Topology Power- recycled Fabry-Perot arm cavity Michelson Dual-recycled Fabry-Perot arm cavity Michelson (stable recycling cavities) GW Readout Method RF heterodyne DC homodyne Optimal Strain Sensitivity 3 x 10-23 / rHz Tunable, better than 5 x 10-24 / rHz in broadband Seismic Isolation Performance flow ~ 50 Hz flow ~ 13 Hz Mirror Suspensions Single Pendulum Quadruple pendulum slide courtesy of Dave Reitze
  25. 25. UKZN: Jan 20, 2014 Advanced detector prospects 25[Aasi+ (LSC+Virgo), arXiv:1304.0670]
  26. 26. UKZN: Jan 20, 2014 The case of the buried signal 26
  27. 27. UKZN: Jan 20, 2014 Spectrograms 27
  28. 28. UKZN: Jan 20, 2014 Burst searches • Coherent WaveBurst: An algorithm which is used for unmodeled searches in a wide parameter space that could detect all parts of the coalescence event • Omega pipeline: Multi-resolution time-frequency search, equivalent to a template-based search for sinusoidal Gaussians in whitened data Laura Cadonati G070801-00 28
  29. 29. UKZN: Jan 20, 2014 The case of the resurrected signal 29 +
  30. 30. UKZN: Jan 20, 2014 Matched filtering Filter 30 slide courtesy of Damir Buskulic
  31. 31. M 50M UKZN: Jan 20, 2014 Waveform families  Typical frequency scales as 1/Mass  For massive systems ( for LIGO), merger and ringdown contribute significantly to signal-to-noise ratio (SNR)  Spins add complications 31 INSPIRAL: post-Newtonian approximate waveforms RINGDOWN: perturbative solutions MERGER: need Numerical Relativity!
  32. 32. UKZN: Jan 20, 2014 Background estimation t signal? Hanford 1 Virgo background coincidence 32  Background is highly non-Gaussian  Can be estimated with time slides between detectors Gaussian Non-Gaussian tails
  33. 33. UKZN: Jan 20, 2014 False Alarm estimation 33 Candidate GW100916 recovered with estimated False Alarm Rate < 1 in 7,000 years! [Abadie et al., Phys. Rev. D 85, 082002 (2012)]
  34. 34. UKZN: Jan 20, 2014 The Big Dog 35
  35. 35. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics » Even non-trivial upper limits can do the trick: 37 [IM & O’Shaughnessy, 2010, CQG 27 114007]
  36. 36. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics  Can learn a lot more by comparing distributions of observed parameters (masses, spins) with model predictions 38
  37. 37. UKZN: Jan 20, 2014 Predictions of component mass distributions 39 [Dominik et al., 2012 ApJ, 759, 52]
  38. 38. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics  Can learn a lot more by comparing distributions of observed parameters (masses, spins) with model predictions » Requires accurate parameter estimation on individual sources 40
  39. 39. UKZN: Jan 20, 2014 Parameter estimation: challenges 41  Explore a large physical parameter space: 9 to 15 dimensions  Analyze data streams coherently  Make use of a priori information  Infer posterior distribution on signal parameters  Could be multi-modal:
  40. 40. UKZN: Jan 20, 2014 Solution: Bayesian inference & stochastic sampling 42 [van der Sluys et al., 2008, 2008, 2009; Veitch & Vecchio, 2008, 2008; Raymond et al., 2009,2010; Farr and IM, 2011; Veitch et al., 2012...]
  41. 41. UKZN: Jan 20, 2014 43
  42. 42. UKZN: Jan 20, 2014 Accurate Parameter Estimation 44 van der Sluys, IM, Raymond, et al., 2009, CQG 26, 204010
  43. 43. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics  Can learn a lot more by comparing distributions of observed parameters (masses, spins) with model predictions » Requires accurate parameter estimation on individual sources » Requires combining information from multiple events to construct a statement about population distribution (accounting for selection bias, etc.) » Requires a library of catalogs of simulations based on different assumed astrophysical parameters » Requires a pipeline for comparing observations and catalogs » We need to be able to test population synthesis models themselves: need to over-determine the parameters... how many detections will this require? what will be the correlations/degeneracies in the astrophysical parameter space? 45
  44. 44. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics  Can learn a lot more by comparing distributions of observed parameters (masses, spins) with model predictions  (Almost) Model-independent inference 46 » Evidence for a mass gap? [Dominik, IM, Belczynski, in prep.]
  45. 45. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics  Can learn a lot more by comparing distributions of observed parameters (masses, spins) with model predictions  More model-independent inference 47 » Search for subpopulations (e.g., distinguish isolated and dynamically formed BH-BH binaries based on spin-orbit alignment) » Directly measure time delays by observing dependence of merger rate on redshift [IM+, in prep.]
  46. 46. UKZN: Jan 20, 2014 Astrophysics: the Inverse Problem  Comparing predicted rates of binary mergers with model predictions can allow us to constrain the input (astro)physics  Can learn a lot more by comparing distributions of observed parameters (masses, spins) with model predictions  More model-independent inference 48 » Search for subpopulations (e.g., distinguish isolated and dynamically formed BH-BH binaries based on spin-orbit alignment) » Measure binary kick velocities from GWs without EM counterparts [L. Kelley et al., 2010, ApJL 725 L91]
  47. 47. UKZN: Jan 20, 2014 Multimessenger astronomy  “Holy grail of GW astronomy” 49 Targeted archival search GWs from binary merger EM transient Rapid(?) followup GW candidate EM counterpart survey deep pointing
  48. 48. UKZN: Jan 20, 2014 Cosmology with Advanced Detectors  GWs as standard candles [Schutz, Nature, 1986]  Mass-redshift degeneracy can be broken by: » Direct EM associations [e.g. Nissanke et al., 2010] » Statistical EM associations [Schutz, 1986 and others] » Tidal effects [Messenger & Read, 2011] » Knowledge of mass distribution [Taylor, Gair, IM, 2011]  Could independently measure Hubble constant: 50
  49. 49. UKZN: Jan 20, 2014 Testing GR with extreme-mass-ratio inspirals  LIGO sensitive @ a few hundred Hz » NS-NS, NS-BH, BH-BH binaries » and intermediate-mass-ratio inspirals of NSs or BHs into IMBHs – could observe up to tens per year [IM+, 2008, ApJ 681 1431]  LISA sensitive @ a few mHz » massive black-hole binaries » galactic white dwarf (and compact object) binaries » extreme-mass-ratio inspirals of WDs/NSs/BHs into SMBHs – could observe tens to hundreds to z~1 [e.g., Amaro-Seoane et al., 2007, CQG 24 R113] 51
  50. 50. UKZN: Jan 20, 2014 Extreme Mass Ratio Inspirals 52
  51. 51. UKZN: Jan 20, 2014 Exploring the spacetime... 53
  52. 52. UKZN: Jan 20, 2014 ... taking lots of pictures 54
  53. 53. UKZN: Jan 20, 2014 Testing the “no-hair” theorem 55
  54. 54. UKZN: Jan 20, 2014 56 Testing the no-hair theorem
  55. 55. UKZN: Jan 20, 2014 57 Testing the no-hair theorem? Stationary, vacuum, asymptotically flat spacetimes in which the singularity is fully enclosed by a horizon with no closed timelike curves outside the horizon are described by the Kerr metric
  56. 56. UKZN: Jan 20, 2014 58 Do black holes have hair? Ryan’s theorem [1995]: GWs from nearly circular, nearly equatorial orbits in stationary, axisymmetric spacetimes encode all of the spacetime multipole moments... in principle Manko-Novikov spacetime, an exact solution of Einstein’s equations: Search for observable imprints of a “bumpy” spacetime, such as deviations from the full set of isolating integrals (energy, angular momentum, Carter constant) in Kerr [Gair, Li, IM, 2009, PRD 77:024035]
  57. 57. UKZN: Jan 20, 2014 The emergence of chaos 59 Solve the geodesic equation and study Poincare maps: - Plot dρ/dt vs. ρ for z=z0 crossings - Phase space plots should be closed curves for all z0 iff there is a third isolating integral [Carter constant] Newtonian+hexadecapole: M2=10 M0; M4=400 M0
  58. 58. UKZN: Jan 20, 2014 Order and Chaos, side by side 60 0 2 4 6 8 10 12 14 −5 −4 −3 −2 −1 0 1 2 3 4 5 ρ/Μ z/M ffective potential for geodesic motion around a bumpy black hole with χ = 0.9, q = 0.95, , and Lz = 3M. The thick dotted curves indicate zeros of the effective potential. The of a typical geodesic in the outer region is shown by a thin curve. The regular pattern of ections of the geodesic projection onto the ρ−z plane indicates (nearly) regular dynamics. is increased from the value shown in Figure 4, the two regions of bound motion y merge. When this first occurs, the “neck” joining the regions is extremely narrow. s exist which can pass through the neck, but this requires extreme fine tuning. As her increased, the neck gradually widens and eventually disappears. At that stage, e allowed region for bound orbits has a similar shape to the outer region of Figure 4. general properties of the effective potential seem to be common to all spacetimes 0 and χ = 0. More relevant for the EMRI problem is to fix q and χ and to vary z. For E = 1 and sufficiently large Lz, there are two regions of allowed motion away from the origin, in addition to the plunging zone connected to the singularity , |z| ≤ 1. The outermost of the allowed regions stretches to infinity and contains c orbits. The inner region of bounded motion is the analogue of the inner bound f
  59. 59. UKZN: Jan 20, 2014 Other signs of non-Kerr spacetimes  Location and character of ISCO  Periapsis and orbital-plane precession 61 1 2 3 4 5 6 7 8 -4 -2 0 2 4 ρISCO/M q Radially unstable - first branch Radially unstable - second branch Vertically unstable 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 -4 -2 0 2 4 (MΩφ)ISCO q Radially unstable - first branch Radially unstable - second branch Vertically unstable FIG. 11: Properties of the equatorial ISCO in spacetimes with χ = 0, as a function of q. We show the ρ coordinate of the ISCO (left panel) and the dimensionless frequency of the orbit at the ISCO (right panel). As described in the text, the ISCO radius has three branches, depending on whether it is determined by one of the two branches of radial instability or the branch of vertical instability. These branches are indicated separately in the diagram. For values of q where all three branches are present, the dashed line denotes the “OSCO” and the dotted line denotes ˜ρISCO as discussed in the text. Allowed orbits lie above the curve in the left panel, and below the curve in the right panel. comparatively small deviations from Kerr. V. PERIAPSIS AND ORBITAL-PLANE PRECESSIONS -4 -2 0 2 4 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 Δpρ MΩφ q = -0.5 q = -1 q = -5 q = 0.5 q = 1 q = 5 FIG. 17: Difference between periapsis precessions in a bumpy spacetime with χ = 0 and the -1 -0.5 0 0.5 1 1.5 2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 Δpz MΩφ q = -0.5 q = -1 q = -5 q = 0.5 q = 1 q = 5 FIG. 19: Difference between orbital-plane precessions in a bumpy spacetime with χ = 0.9 and the
  60. 60. 10 −6 10 −5 10 −4 10 −3 10 −2 10 −1 10 −1 10 0 10 1 10 2 10 3 10 4 10 5 10 6 Accumulatedcycledifference 3.5 PN vs 3 PN, M=1e4 Msun 3.5 PN vs 3 PN, M=1e5 Msun 3.5 PN vs 3 PN, M=1e6 Msun 3.5 PN vs EMRI, M=1e4 Msun 3.5 PN vs EMRI, M=1e5 Msun 3.5 PN vs EMRI, M=1e6 Msun UKZN: Jan 20, 2014 Measuring the mass quadrupole Can measure mass quadrupole moment to around 20% of Kerr value with Advanced LIGO [Brown et al., 2007, PRL 99, 201102] 62 Waveforms are a problem: both post-Newtonian and self- force waveforms currently fail in the intermediate regime [IM and Gair, 2009, PRD 72 084025]
  61. 61. UKZN: Jan 20, 2014 IMRI: null-hypothesis test of Kerrness 63 [Rodriguez, IM, Gair, PRD 85, 062002]
  62. 62. UKZN: Jan 20, 2014 Summary  Advanced LIGO is likely to observe GWs from NS-NS, NS-BH, BH-BH coalescences; tens or more coalescences may be observed according to some models, including signatures of dynamical formation  GW detections and upper limits for compact-object coalescences will allow us to constrain astrophysical parameters through comparisons with model predictions  Extreme- or intermediate- mass-ratio inspirals can serve as precise tests of General Relativity  There’s lots of work to be done in order to make true GWastrophysics a reality! 64

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