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Physics of the Intracluster Medium from Present and Future X-Ray Instruments

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Physics of the Intracluster Medium from Present and Future X-Ray Instruments Physics of the intracluster medium from present and future X-ray instruments Maxim Markevitch (NASA Goddard) August 7, 2015 Cluster precision cosmology − 0.6 B AO −0.7 all −0.8 SN Ia −0.9 Cosmological −1.0 0 constant W w MA −1.1 P −1.2 clusters +WMAP −1.3 clusters −1.4 −1.5 0.60 0.65 0.70 0.75 0.80 0.85 ΩDE Vikhlinin 09 Cluster precision cosmology only as precise as our knowledge of cluster physics − 0.6 B AO −0.7 all −0.8 SN Ia −0.9 Cosmological −1.0 ±10% mass error 0 constant W w MA −1.1 P −1.2 clusters +WMAP −1.3 clusters −1.4 −1.5 0.60 0.65 0.70 0.75 0.80 0.85 ΩDE Vikhlinin 09 “Nuisance parameters” AGN and star formation feedback — Chandra bubbles, shocks around them Radiative cooling — match simulations with observed density profiles; high-res XMM RGS and Astro-H spectra ICM clumpiness (related to cooling) Chandra ultra-deep observations Turbulence, bulk motions — Astro-H details in this talk Thermal conduction — T maps, profiles details in this talk Viscosity — cold front stability Electron-ion non-equipartition — shock fronts Magnetic fields, cosmic ray electrons (mostly radio) match radio with X-ray Cosmic ray protons — Fermi upper limit Helium abundance — SZ / X-ray Cold fronts in A2142 100 kpc • KH instabilities — await MHD simulations to constrain effective viscosity “Nuisance parameters” AGN and star formation feedback — Chandra bubbles, shocks around them Radiative cooling — match simulations with observed density profiles; high-res XMM RGS and Astro-H spectra ICM clumpiness (related to cooling) Chandra ultra-deep observations Turbulence, bulk motions — Astro-H details in this talk Thermal conduction — T maps, profiles details in this talk Viscosity — cold front stability Electron-ion non-equipartition — shock fronts Magnetic fields, cosmic ray electrons (mostly radio) match radio with X-ray Cosmic ray protons — Fermi upper limit Helium abundance — SZ / X-ray Electron-proton equilibration timescale from shock fronts Bullet cluster shock τep ≪ Coulomb 3D τep = Coulomb 1600 km/s MM 06 • 95% confidence: τep ≪ Coulomb “Nuisance parameters” AGN and star formation feedback — Chandra bubbles, shocks around them Radiative cooling — match simulations with observed density profiles; high-res XMM RGS and Astro-H spectra ICM clumpiness (related to cooling) Chandra ultra-deep observations Turbulence, bulk motions — Astro-H details in this talk Thermal conduction — T maps, profiles details in this talk Viscosity — cold front stability Electron-ion non-equipartition — shock fronts Magnetic fields, cosmic ray electrons (mostly radio) match radio with X-ray Cosmic ray protons — Fermi upper limit Helium abundance — SZ / X-ray “Nuisance parameters” AGN and star formation feedback — Chandra bubbles, shocks around them Radiative cooling — match simulations with observed density profiles; high-res XMM RGS and Astro-H spectra ICM clumpiness (related to cooling) Chandra ultra-deep observations Turbulence, bulk motions — Astro-H details in this talk Thermal conduction — T maps, profiles details in this talk Viscosity — cold front stability Electron-ion non-equipartition — shock fronts Magnetic fields, cosmic ray electrons (mostly radio) match radio with X-ray Cosmic ray protons — Fermi upper limit Helium abundance — SZ / X-ray New constraints on large-scale heat conduction (B. Russel 2014 PhD thesis; Russell, MM, ZuHone in prep.) Observational constraints on ICM conductivity so far • Conduction across cold fronts must be strongly suppressed (Ettori & Fabian 2000, ...) • Stripped tails of infalling groups survive → strong suppression (Eckert et al. 14) — both can be explained by magnetic draping • Small-scale temperature structure in mergers, e.g., A754 → suppressed by ×10 – 40 (Markevitch et al. 03) — can be a selection effect (pick thermally isolated regions) Cluster-wide, large-scale thermal conduction? Cluster temperature profiles — radial decline 1.5 1.0 i T h / T 0.5 ASCA (Markevitch et al. 98) Chandra (Vikhlinin et al. 05) 0.0 0.2 0.4 0.6 0.8 r/r180 • XMM, Suzaku results similar (Molendi & Leccardi 08; George et al. 09; ...) A2029, a prototypical hot relaxed cluster 1017 r 500•a r 500 •b 1016 ρtot 3 − 10 1015 Mpc ρgas ⊙ V e 2D M 14 , 10 ,k ρ T 5 3D ⊙ 1013 M , M 1012 0 1011 10 100 1000 10 100 1000 r, kpc r, kpc Vikhlinin et al. 06 If the cluster were a solid body ... no cooling, 0.3 Spitzer isotropic conduction r 2500 r 500 0 Gyr 1 2 8 B. Russell 14 • conduction erases T gradient If the cluster is hydrostatic ... no cooling, 0.3 Spitzer isotropic conduction, allow gas redistribution r 2500 r 500 0 Gyr 1 8 B. Russell 14 • T gradient maintained because of cluster compression (result very similar to McCourt 13) Evolution of gas density profile no cooling, 0.3 Spitzer isotropic conduction r 2500 r 500 8 1 0 Gyr B. Russell 14 Evolution of gas density profile cooling, 0.3 Spitzer isotropic conduction r 2500 r 500 8 1 0 Gyr B. Russell 14 • for r > 0.5 r 2500, result doesn’t depend on details of heating and feedback in cool core Observed differential f gas profiles in hot relaxed clusters T > 5 keV, z < 0.25 relaxed clusters • very low scatter! ) ∆ r ( gas f fractional intrinsicfractional scatter 0.05 0.1 0.2 0.5 500 2500 0.00 0.05 0.10 0.15 0.20 105 104 103 102 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 ∆ r r2500 Mantz et al. 14 • The sample of relaxed clusters should contain clusters of different “ages” (time since last major disturbance) • If κ , 0, clusters of different age should have different f gas = scatter in the sample Evolution of differential f gas profile with conduction 30% Spitzer 2 • 1 • • 1 • • Mantz 14 0 Gyr • • B. Russell 14 Evolution of differential f gas profile with conduction 20% Spitzer 3 • 2 • 1 • • • 1 • Mantz 14 0 Gyr • • B. Russell 14 Evolution of differential f gas profile with conduction 10% Spitzer 3 • 5 • 4 • 2 • • • 3 • 2 • Mantz 14 1 • 1 • 0 Gyr • • B. Russell 14 Evolution of differential f gas profile with conduction 5% Spitzer 5 • 8 • 4 • 7 • 6 • 3 • • • 5 2 • 4 • Mantz 14 3 • 1 • 2 • • 0 Gyr 1 • • B. Russell 14 Conclusions on conduction • Under simple assumptions, κ > 5 – 10% Spitzer (in the cluster radial direction) contradicts the observed lack of scatter in f gas at r ∼ r 2500 in hot, relaxed clusters • Cosmological simulations including heat conduction and the relaxed cluster selection as in Mantz 14 may place stronger constraints ICM turbulence (direct measurements) Astro-H instruments /20 /+!+/2/+/D:B9+('+ /20 .+!+/2. B9:+;+B9A+/(<C+0)--CD2 8EF+/'C0G(C3+0CH&2 1 *7764B:C6+&@63+/4< $ $# $## $### #"$ $ $# $## $### $3&-45+/6&72 Astro-H instruments (relevant for clusters) Soft X-ray Spectrometer Soft X-ray Imager Hard X-ray Imager (SXS) (SXI) (HXI) Detectortechnology microcalorimeter CCD Si/CdTecross-strips Effectivearea 210cm2 at6keV 300cm2 at30keV 360cm2 at 6 keV Energyrange 0.4–12keV 0.3–12keV 5–80keV Energy resolution, FWHM 5 eV < 200eV 2keV Angularresolution,HPD 1.2′ 1.2′ 1.7′ FOV 3′ × 3′ (6×6pixelarray) 38′ × 38′ 9′ × 9′ Can resolve turbulently broadened Fe line: 5 eV resolution at E = 6.5 keV → σ LOS = 100 km/s 100 ks simulation of Perseus core (expected exposure much longer) Likely early cluster projects (Astro-H White Paper, arxiv:1412.1176) • Perseus core: turbulence, bulk motions, rare elements, 3.5 keV line • Centaurus: line-rich cool core, cooling gas EM distribution • M87: velocity of SW arm • A2029, the most relaxed cluster: constrain turbulence at r 2500 to σ LOS < 150 km/s ( ∼ 2% of thermal pressure) • Power spectrum of turbulence in Coma Power spectrum of turbulence r (arcmin) 1 2 3 5 10 15 100 100 kpc -1 100 10 200 kpc 10-2 300 kpc 500 kpc 10-3 cascade 1000 kpc ) 3 -1 10-4 10 2 z (Mpc w -5 2 z 10 / w / -6 injection 10 SF(r) (k) 3D P 10-7 10-2 dissipation 10-8 10-9 10-10 10-3 10-4 10-3 10-2 10-1 101 102 103 k (kpc−1 ) r (kpc) • Dissipation scale, power-law slope → plasma microphysics (can’t measure) • Injection scale + normalization (can measure) → (a) energy flow down the cascade, (b) diffusion and mixing rate (for metals, entropy, cosmic rays, ...) Coma is the best cluster to study turbulence A simple system: • No cooling flow, a big flat core → turbulence should develop in an isotropic, textbook fashion on all scales • No central AGN → turbulence is driven only by cluster mergers A well-studied radio halo — can estimate efficiency of turbulent acceleration of cosmic rays Expected constraints on power spectrum • fit line width and “structure function” (average velocity difference as a function of angular separation) 5× 100 ks pointings Coma 0.7 100 kpc 200 kpc 0.6 big cross 300 kpc 500 kpc 1000 kpc 0.5 M Z = 0.3 ) 3 0.4 (Mpc 2 z w / 0.3 n C 0.2 spectrum normalization 0.1 200 kpc 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 lmax (Mpc) ZuHone et al. 15 injection scale but ... with 5 eV resolution for the first time, expect surprises.
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