Simulations of relativistic outflows in Astrophysics with Ratpenat - PowerPoint PPT Presentation

Simulations of relativistic outflows in Astrophysics with Ratpenat Manel Perucho Pla Universitat de València

Introduction: jets in general Active galactic nuclei: X-ray binaries: • 10% AGN (radio-loud AGN) • 20% • v jet = 0.9 - 0.995c • v jet < 0.9c • L jet = 10 43 - 10 48 erg/s • L jet = 10 38 - 10 40 erg/s • Size = 0.1-1 Mpc • Size = 10 -3 – 10 -1 pc • Collimation: few degrees • Collimation: few degrees • Central engine: SMBH + • Central engine: stellar disc BH/NS + disc Gamma-ray bursts: • v jet/wind = 0.99995-0.999999995c • L GRB = 10 52 erg/s (T = 1s) Young stellar objects: • Size = 1 pc (late afterglow • v jet = 10 -3 c evolution) • L jet = 10 35 erg/s • Collimation: few tens of degrees • Size = 10 -2 – 10 -1 pc • Central engine: stellar BH + torus • Collimation: few degrees • Central engine: YSO + inflow

Introduction:standard model of AGN NGC5728 NGC4261

Introduction:extragalactic jets Jets are a common ingredient of radio-loud AGNs detected and imaged at very different spatial scales with different radio interferometry arrays (kpc scales: VLA, Merlin; pc scales: VLBA, EVN…) Jets: Relativistic collimated ejections of thermal (e+/e-, ep) plasma + ultrarelativistic electrons/positrons + magnetic fields + radiation, generated in the vicinity of SMBH (GENERAL) RELATIVISTIC MHD + ELECTRON TRANSPORT + RADIATION TRANSFER

What do numerical simulations tell us Hydrodynamical non-relativistic simulations (Rayburn 1977; Norman et al. 1982) verified the basic jet model for classical radio sources (Blandford & Rees 1974; Scheuer 1974) and allowed to identify the structural components of jets. Shocked ambient medium Cocoon (backflow) Supersonic beam Terminal shock Contact discontinuity Bow shock Morphology and dynamics governed by the interaction with the external medium.

What do numerical simulations tell us 2D RHD simulations: – morphology of jets depending on internal energy (van Putten 1993, Martí et al. 1994, 1995, 1997; Duncan & Hughes 1994). – observed phenomenology explained by simulations (e.g., Komissarov & Falle 1996, 1997,Gómez et al 1996, 1997, Agudo et al. 2001). – stability (Rosen et al. 1999, Perucho et al. 2004, 2005, 2007). – relativistic equation of state allows to study the influence of the jet composition and the interaction with the ambient medium (Scheck et al. 2002, Perucho & Martí 2007). 3D RHD simulations: – Jet evolution and stability (Nishikawa et al. 1997, 1998; Aloy et al. 1999, 2003; Hughes et al. 2002, Perucho et al. 2006, …). RMHD simulations: – Influence of the magnetic field strength and structure on the jet evolution and stability (Nishikawa et al. 1997, 1998; Komissarov 1999; Leismann et al. 2005; Keppens et al. 2008; 3D: Mizuno et al. 2007).

RHD numerical simulationswith RATPENAT • RATPENAT, a 3D RHD code: – The code has been parallelised by the BSC staff Y N (Cela – de la Cruz – Rubio). – It includes MPI and OMP parallelisation. – The MPI parallelisation of the numerical grid has been performed in the direction of NZ propagation of the flow. NX

Relativistic hydrodynamics: SRHD equations

RHD numerical simulations with RATPENAT • Code scales depending on the number of total cells in the axial direction. Ny = 8192 cells Nt = 64 2 = 4096 Ny = 8192 cells Nt = 256 2 = 65536 N axial cells/N time N axial cells/N time 2 4096 203m35s 32 256 126m01s 4 2048 89m25s 64 128 64m27s 8 1024 43m02s 128 64 33m43s 16 512 18m44s 256 32 19m45s 32 256 8m45s

Stability of relativistic jets with RATPENAT Perucho et al. 2007, Phys. Rev. E • Perucho et al. (2004a,b, 2005): – Simulations of the stability of relativistic flows in two dimensions. • Infinite jet with periodic boundary conditions. • The perturbations are allowed to grow in time. – The conclusions: • Fast and cold jets are very stable against the growth of instabilities. • Slower jets are disrupted by the growth of instabilities. – An important point: • The growth of “resonant modes” (Perucho et al. 2007) in fast jets is crucial for their TIME long-term stability. • These modes have very short wavelength and generate a hot shear layer around a faster core. • Are we able to recover these structures in a 3D simulation? And are they so important for jet stability in 3D? • Ratpenat: – 3 simulations, with 512 3 cells, using 128 processors for each, during ∼ 20-30 days. • A cold and slow jet. • A hot and fast jet. • A cold and fast jet. Lorentz factor 20 jet Lorentz factor 5 jet

Stability of relativistic jets with RATPENAT Cold, slow jet (Lorentz factor=5). Lorentz factor axial cuts. 0 < t < 300 R/c

Stability of relativistic jets with RATPENAT Cold, slow jet (Lorentz factor=5). Jet mass fraction transversal cuts. 0 < t < 300 R/c

Stability of relativistic jets with RATPENAT Cold, slow jet (Lorentz factor=5). Evolution of axial momentum. < 10 %

Stability of relativistic jets with RATPENAT Cold, fast jet (Lorentz factor=20). Lorentz factor axial cuts. 0 < t < 450 R/c

Stability of relativistic jets with RATPENAT Cold, fast jet (Lorentz factor=20). Jet mass fraction transversal cuts. 0 < t < 450 R/c

Stability of relativistic jets with RATPENAT Hot, fast jet (Lorentz factor=20). Evolution of axial momentum. 75 %

Microquasar jets with RATPENAT Sketch of a X-ray binary system with a relativistic outflow We focus on the inner region Bosch-Ramon and Khangulyan 2009 Sketch of the different regions in a X-ray binary system with

Microquasar jets with RATPENAT 2D simulations: Perucho and Bosch-Ramon 2008 weak jet mild jet 3D simulations: Perucho, Bosch-Ramon and Khangulyan 2009, in preparation

Microquasar jets with RATPENAT 3D simulations: Perucho, Bosch-Ramon and Khangulyan 2009, in preparation 1.6 10 12 cm SIM. 1 weak jet t_f = 750 s SIM. 2 3.6 10 12 cm powerful jet t_f = 370 s

Microquasar jets with RATPENAT SIM. 1 SIM. 2 weak jet powerful jet

CONCLUSIONS • Ratpenat is a 3D RHD code for the study of relativistic outflows. – Parallelised using MPI and OMP. – Scales nicely, as long as the number of cells in each process is large enough and the axial size of the grid is large compared to the transversal directions. • Limitation on the RAM memory available in each node. – It allows to perform realistic simulations of astrophysical scenarios. – The next steps are: • Including relativistic equation of state (done). • 3D RMHD.