PACIFIC conference Gump Station, Moorea Sept 14, 2015 Multi-D SNR Simulations with Particle Acceleration Gilles Ferrand, University of Manitoba ([email protected]) in collaboration with Samar Safi-Harb (U of M) and Anne Decourchelle (CEA Saclay) Outline of the Talk Introduction: particle acceleration in supernova remnants - SNRs as Cosmic Ray accelerators - SNR structure and evolution 3D numerical simulations - hydro+kinetic code (Ramses+Blasi) - thermal emission - non-thermal emission - perspetives 1.1 The 3 dimensions of Cosmic Radiation mass spectrum energy spectrum angular spectrum isotropic radiation (random walk in B) [Iyono et al 2005] 99% of nucleons + 1% e- power-law, with breaks quasi-solar abundance, > 10 orders of magnitude with particularities in energy ! even at the highest energies? [Israel 2004] [Nagano & Watson 2000] [Pierre Auger Coll. 2010, 2012] 1.2 Particle acceleration in the Universe Engines of acceleration : massive stars, compact objects Physics of shocks, of accretion/ejection, of magnetic fields Active Gamma-Ray Galactic Bursts Nuclei interacting galaxies cosmic flows structures formation binary systems micro-quasars superbubbles supernovae and remnants Sun pulsars Galactic center OB associations stellar winds 1.3 The structure of a young supernova remnant Tycho’s SNR Warren et al 2005 seen by Chandra 0.95 – 1.26 keV (at age 433 yr) 1.63 – 2.26 keV 4.10 – 6.10 keV 1.4 The evolution of a supernova remnant radius R non-radiative radiative momentum-driven values given for pressure-driven 1.4 solar masses 46 pc of ejecta with kinetic energy of 1051 erg, expanding in a Sedov-Taylor medium of density 7 pc 0.1 cm-3 ejecta-dominated 600 yr 30 000 yr time t G1.9+0.3 Tycho RCW 86 Simeis 147 Monoceros Loop 140 yr 500 yr 2,000–10,000 yr ∼40,000 yr ∼300,000 yr 1.5 SNRs as a key link between stars and the ISM enrichment in heavy elements stars: average stars: up to C-O Big Bang: Cosmic Rays: all other elements massive stars: up to Fe H, He Li, Be, B from C to U supernovae: everything else injection of energy heating hydrodynamic magnetic field impact on subsequent of the gas turbulence amplification star formation cycles? acceleration of particles the acceleration of charged particles is SNRs main sources? < 1015 eV: > 1018 eV: an important feature Also PSRs and binaries Galactic extra-Galactic of magnetized shocks in collisionless plasma 1.6 Supernova Remnants as Galactic CR sources mass spectrum energy spectrum angular spectrum Chandra gamma ! standard overall ! energetic budget ! observational proofs of composition " but can we reach acceleration of e- " but what about all the knee / the ankle? " difficult to find the "anomalies"? energetic protons! ! mechanism producing power-law spectra " but of which slope? [recent reviews: Drury 2012, Blasi 2013, Bell 2013] 1.7 SNR broad-band emission A&A 516, A62 (2010) SN 1006 Fig. 6. Azimuthal profile obtained from HESS data and XMM-Newton data in the 2–4.5 keV energy band and smoothed to HESS PSF, re- stricted to radii 0.12◦ r 0.36◦ from the centre of the SNR. Azimuth ≤ ≤ 0◦ corresponds to East, 90◦ corresponds to North, 180◦ to West and 90◦ to South. − radio optical X Fig. 4. HESS γ-ray image ofgamma SN 1006. The linear colour scale is in units 2 2 of excess counts per π (0.05◦) .Pointswithin(0.05◦) are correlated. The white cross indicates× the geometrical centre of the SNR obtained from XMM data as explained in the text and the dashed circlesE cor- respond to R dR as derived from the fit. The white star shows the centre of the circle± encompassing the whole X-ray emission as derived keV by Rothenflug et al. (2004) andTeV the white triangle the centre derived by Cassam-Chenaï et al. (2008) from Hα data. The white contours corre- cm µm spond to a constant X-ray intensity as derived from the XMM-Newton flux map and smoothed to the HESS point spread function, enclosing ! respectively 80%, 60%, 40% and 20% of the X-ray emission. The inset shows the HESS PSF using an integration radius of 0.05◦. synchrotron Balmer lines atomic lines of Inverse Compton ? in B field forbidden lines heavy elements pion decay ? Fig. 7. Differential energy spectra of SN 1006 extracted from the two regions NE and SW as defined in Sect. 2.Theshadedbandscorrespond + synchrotron to the range of the power-law fit, taking into account statistical errors. Table 2. Fit results for power-law fits to the energy spectra. Region Photon index ΓΦ(>1TeV) 12 2 1 (10− cm− s− ) NE 2.35 0.14stat 0.2syst 0.233 0.043stat 0.047syst SW 2.29 ± 0.18 ± 0.2 0.155 ± 0.037 ± 0.031 hot ejecta > TeV e- ? ± stat ± syst ± stat ± syst GeV e- blast wave Fig. 5. Radial profile around the centre of the SNR obtained from HESS data and XMM-Newton data in the 2–4.5 keV energy band smoothed to HESS PSF. > TeV p ? + TeV e- The spectra for the NE and SW regions are compatible with Γ power law distributions, F(E) E− ,withcomparablephoton indices Γ and fluxes. Confidence∝ bands for power-law fits are centred on 143.6◦ 6.1◦ (SW region) and 29.3◦ 4.0◦ (NE − ± ± shown in Fig. 7 and Table 2.Theintegralfluxesabove1TeV region) and with similar widths of 33.8◦ 7.0◦and 27.9◦ 4.0◦. [review for CR evidence: Helder et al 2012] ± ± correspond to less than 1% of the Crab flux, making SN 1006 one of the faintest known VHE sources (Table 2). The derived 4. Spectral analysis fluxes are well below the previously published HESS upper lim- its (Aharonian et al. 2005). The observed photon index Γ 2.3is Differential energy spectra of the VHE γ-ray emission were de- somewhat steeper than generally expected from diffusive≈ shock rived for both regions above the energy threshold of 260 GeV. acceleration theory and may indicate that the upper cut-off of the These regions correspond to 80% of the X-ray emission∼ (after high-energy particle distribution is being observed; however, the smearing with the HESS PSF) and therefore slightly underesti- uncertainties on the spectrum preclude definitive conclusions on mate the TeV emission of the full remnant. this point. Page 4 of 7 2.1 Modelling DSA at different scales focus on superbubble source description supernova remnant collective effects? magnetized shock [Ferrand & Marcowith acceleration mechanism acceleration 2010] u / r shock ushock SNOB back-reaction on morphology? [Ferrand, Decourchelle et al accelRSN wave - particle 2010] interaction !B shock repeated [Ferrand, Downes, MARCOS modified Marcowith 2008] shocks ? 2.2 Diffusive shock acceleration: the coupled system IR Opt radio UV X " X shock wave cosmic-rays injection, acceleration (thermal magnetized shock modification (non-thermal plasma) population) conservation laws damping particle distribution: heating ∂X n (x, t)= f (x, p, t)4πp2 dp +div(F (X)) = 0 ∂t p ρ ρu transport equation: X = ρu F (X)= ρu u + pI 3 ⊗ diffusion, injection,∂f ∂ ∂ ∂f 1 ∂p f ∂u P (e + P ) u generation (instabilities) + (uf)= D + ∂t ∂x ∂x ∂x 3p2 ∂p ∂x stochastic acceleration magnetic waves hydrodynamic (collective movements kinetic treatment of charges) treatment [reviews : Drury 1983, Jones and Ellison 1991, Malkov and Drury 2001] 2.3 Numerical simulations with Ramses parameters: Tycho (SN Ia) tSN = 440 years 51 ESN = 10 erg n =7,Mej =1.4M ⊙ 3 s =0,nH,ISM =0.1 cm− Chevalier 1982, 1983 Teyssier 2002, Fraschetti et al 2010 SNR initialization: SNR evolution: self-similar profiles 3D hydro code Ferrand et al 2010 from Chevalier ramses (A&A 509 L10) shock back-reaction: diagnostics varying gamma Ellison et al 2007 Blasi et al particle acceleration: 2002, 2004, 2005 non-linear model + Caprioli 2008, 2009 of Blasi 2.4 Hydro- and thermodynamics of the plasma Thermal emission in each cell depends on: • plasma density n2 • electron temperature T e n progressive equilibration with protons temperature Tp via Coulomb interactions • ionization states fi(Z) computation of non-equilibrium ionization Tp with the exponentiation method t τI = n(t).dt tS τI Note: all these parameters depend slices at t = 500 yr from a 10243 simulation with particle on the history of the material back-reaction after it was shocked. 2.5 Thermal emission Ferrand, Decourchelle, Safi-Harb 2012 (ApJ 760 34) using the emission code from Mewe (depends on density, temperature emissivity [erg/s/cm3/eV] and ionisation states) 1024^3 cells t = 500 yr energy [eV] test particle vs. back-reaction test particle vs. back-reaction test particle vs. back-reaction 2.6 Magnetic field and radiative losses Non-thermal emission in each cell depends on: • pion decay: plasma density n(x, t) • synchrotron: magnetic field B ( x, t) n (amplified at the shock, then frozen in the flow) • Compton: ambiant photon fields (CMB) B Note: the acceleration model gives the CR spectra just behind the shock fp(p, x, t) ,fe(p, x, t) they must be transported to account for losses: ρ(x, t) slices at t = 500 yr from a θ • adiabatic decompression α = 10243 simulation without ρ(xS,tS) particle back-reaction t and MF amplification 2 1 • radiative losses Θ B α 3 dt ∝ tS 2.7 Non-thermal emission Ferrand, Decourchelle, Safi-Harb 2014 synchrotron (ApJ 789 49) (e) using the pion decay (p) emission code from P. Edmon (depends on density and magnetic field) Inverse Compton 1024^3 cells (e) t = 500 yr emissivity [erg/s] energy [eV] efficient MF amplification ! high B no net MF amplification ! low B 2.8 Thermal + non-thermal emission simulations observations Energetic protons, accelerated at the shock front, don’t radiate as efficiently as electrons, however: 1/ they impact the test-particlecase dynamics of the shock wave, and therefore the thermal emission from the shell (optical, X-rays) 2/ they impact the evolution of the magnetic field, and therefore the non-thermal emission from the modifiedshock electrons (radio – X- rays – !-rays) with magneticfield amplification 2.9 Perspectives: the shock in context • impact of the progenitor : ejecta profiles (stratification, asymmetries) stellar wind (for core-collapse) • impact of the environment : molecular clouds (radiative? ionized?) ISM turbulence (hydro + mag) shock wave progenitor wind SN ejecta profiles molecular cloud.