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

Active galactic nuclei:

• 10% AGN (radio-loud AGN)
• vjet = 0.9 - 0.995c
• Ljet = 1043 - 1048 erg/s
• Size = 0.1-1 Mpc
• Collimation: few degrees
• Central engine: SMBH +

disc Young stellar objects:

• vjet = 10-3 c
• Ljet = 1035 erg/s
• Size = 10-2 – 10-1 pc
• Collimation: few degrees
• Central engine: YSO +

inflow X-ray binaries:

• 20%
• vjet < 0.9c
• Ljet = 1038- 1040 erg/s
• Size = 10-3 – 10-1 pc
• Collimation: few degrees
• Central engine: stellar

BH/NS + disc Gamma-ray bursts:

• vjet/wind = 0.99995-0.999999995c
• LGRB = 1052 erg/s (T = 1s)
• Size = 1 pc (late afterglow

evolution)

• Collimation: few tens of degrees
• Central engine: stellar BH + torus

Introduction: jets in general

NGC4261 NGC5728

Introduction:standard model of AGN

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…)

Introduction:extragalactic jets

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

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. Morphology and dynamics governed by the interaction with the external medium.

Supersonic beam Cocoon (backflow) Terminal shock Contact discontinuity Bow shock Shocked ambient medium

What do numerical simulations tell us

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). –

• bserved 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).

• RATPENAT, a 3D RHD

code:

– The code has been parallelised by the BSC staff (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 propagation of the flow.

RHD numerical simulationswith RATPENAT

NX NZ N Y

Relativistic hydrodynamics: SRHD equations

• Code scales depending on the number of total cells in the axial direction.

N axial cells/N time 2 4096 203m35s 4 2048 89m25s 8 1024 43m02s 16 512 18m44s 32 256 8m45s

RHD numerical simulations with RATPENAT

N axial cells/N time 32 256 126m01s 64 128 64m27s 128 64 33m43s 256 32 19m45s Ny = 8192 cells Nt = 642 = 4096 Ny = 8192 cells Nt = 2562 = 65536

• 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 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 5123 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.

Stability of relativistic jets with RATPENAT

Perucho et al. 2007, Phys. Rev. E Lorentz factor 20 jet Lorentz factor 5 jet TIME

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 %

Stability of relativistic jets with RATPENAT

Microquasar jets with RATPENAT

Sketch of a X-ray binary system with a relativistic

• utflow

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

Microquasar jets with RATPENAT

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

Microquasar jets with RATPENAT

3D simulations: Perucho, Bosch-Ramon and Khangulyan 2009, in preparation 1.6 1012 cm 3.6 1012 cm

• SIM. 1

weak jet

• SIM. 2

powerful jet t_f = 370 s t_f = 750 s

Microquasar jets with RATPENAT

• SIM. 2

powerful jet

• SIM. 1

weak jet

• 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.

CONCLUSIONS