Interacting galaxies: physics and models (Christian Theis, Vienna)

Transcription

1 Interacting galaxies: physics and models (Christian Theis, Vienna) Examples What can we learn from interactions? How can we learn from interactions: simulation methods parameter space The MW satellite system: Magellanic System dsph System

2 M51: a prototype for an interaction

3 The Antennae

4 Examples of Interacting Galaxies Polar ring galaxies tadpole galaxy

5 Ram pressure stripping NGC 4522 (Kenney et al. 2004) ISM-ICM interaction (Moore & Davis 1994; Vollmer et al. 2001; Rödiger & Hensler 2005)

6 Physical processes involved in Tidal force field: galaxy interactions Structure formation (distortion, arms, bridges) Disruption Harrassment Dynamical friction: Orbital decay Minor and major merger Ram pressure Secondary processes (nuclear activity, starbursts, galactic mass loss )

7 What can we learn from galaxy interactions? kinematical history of galaxies test bed for galaxy evolution: strength,, mode and timing of perturbation dynamical stability of galaxies induced structural changes (mass flows, bars and spiral structure, mergers) reaction of ISM star formation chemical evolution nuclear activity and mass loss properties of the dark matter halo

8 Influence of dark matter halos on galaxy interactions Why interacting systems? Tidal tails can trace outer galaxy Tidal tails can probe off-plane regions Tidal features sensitive to DM halo properties (Dubinski et al. 1999, Springel & White 1999) Halo parameters: Mass Extension Flattening (?) (Rotation) Influence of a variable halo size halos act like softened gravitational forces

9 stars and stellar remnants (white dwarfs, neutron stars,, stellar black holes) interstellar medium (molecular clouds,, diffuse gas, dust) dark matter How can we learn from Components: interactions: models I (massive black holes)

10 How can we learn from interactions: models II Processes: 1. Dynamics Gravitational N-body problem Hydrodynamics (MHD) 2. Galactic microphysics Phase transitions (e.g. star formation,, stellar death) Interactions between phases (e.g.. stellar heating) Processes within a phase (e.g. cooling)

11 Restricted N-body simulations Idea (Pfleiderer & Siedentopf 1961, Toomre & Toomre 1972) Basic assumption: Galaxies follow Keplerian orbits Stars are treated as test particles Fast integration ( 1 CPU sec on modern PC) High spatial resolution in regions of interest BUT: not self-consistent (e.g.. no merging) (Theis & Spinneker 2003)

12 Self-consistent simulations include self-gravity of stars,, gas and dark matter main problem: N 2 -bottleneck simulation methods: 1. TREE-codes ( N logn,, ~N) (e.g 2. grid-based schemes ( N) (e.g. Sellwood 1982) 3. expansion methods,, ( N)( (e.g.. SCF Hernquist 4. special purpose computer,, GRAPE ( N( 2 ) BUT: e.g.. Barnes & Hut 1986, Dehnen 2000) Hernquist & Ostriker 1992) (Tokyo group [Makino, Sugimoto et al.] since 1990) no trivial stable initial configurations low resolution in low-density regions computationally expensive

13 Gas dynamics in galaxy models Single component ISM hydrodynamical models: grid codes smoothed particle hydrodynamics (SPH) phenomenological models: sticky particles (for gas clumps, clouds) Multi-component ISM often: sub-grid models high-resolution hydrodynamical models (SPH, grid) hybrid codes

14 Chemo-dynamics dynamics: towards a complete model... dissipation condensation & evaporation diffuse gas feedback star - formation clouds stars feedback dissipation dark halo gravity

15 Chemo-dynamical modelling First chemo-dynamical models (1D) multi-phase ISM galactic winds 2D chemo-dynamics delayed disk formation metallicity gradients 3D chemo-dynamics (Burkert & Hensler 1987, Theis et al. 1992) (Samland et al. 1997, Rieschick & Hensler 2002) coupling of N-body-calculations and a chemo-dynamical interaction network (Berczik et al. 2002, Harfst et al. 2002, 2006, Semelin & Combes 2002, Samland & Gerhard 2002)

16 How can we learn from interactions: parameter space Optimization problem: Fitness function: 1 f = ; 1 + δ δ cells I ref, i max( I I ref, i sim, i, I sim, i ) Goals: Finding a solution Uniqueness of a solution Problems: Extended parameter space Trapping by local optima

17 Parameters: Parameter space 1. two-body parameters (orbital plane, eccentricity, pericenter, masses...) 2. characteristics of galaxies (orientation of disk, scalelength,...,halo...)...) Example: Disk+point-like perturber: : 7 parameters grid with 5 pts././dimension:: models or 3.5 years GRAPE6 CPU time Fast N-body technique and efficient search strategy required!

18 IDEA: Genetic algorithm IDEA: imitate evolutionary optimization, i.e. adaptation of a population by survival of the fittest solution (Holland 1975, Goldberg 1989) 1. Start with a random population, i.e. N p points in parameter space 2. Apply iteratively reproduction operators

19 Example: : a model for NGC 4449 MINGA reproduces parameters to better than 10-20%, some even better than 1%! (Theis & Kohle 2001)

20 Comparison of parameters for a NGC 4449 model (Theis & Kohle 2001)

21 The Magellanic System (Lund observatory)

22 The Magellanic System in HI Leading arm Bridge LMC SMC Stream (Brüns et al. 2005)

23 The reference scenario Murai & Fujimoto (1980, 1984) model: Results: Restricted N-body model (MW: static, spherical logarithmic potential, test particles) Dynamical friction: Orbital decay Clouds gravitationally bound over 10 Gyr Orbital plane almost perpendicular to Galactic disk Distance between clouds highly variable (2-7 kpc up to 50 kpc) Stream mainly created by SMC (similar results by Lin & Lynden-Bell 1982)

24 Gardiner et al. (1994): More recent models: tidal models - I Test particle simulation for gaseous structures Bridge and extension of stream reproduced LMC almost unperturbed, except for a SMC-close encounter 200 Myr ago But: : substantial offset and no high velocity features Gardiner & Noguchi (1996): self-consistent SMC disk; MW and LMC rigid spherical potentials Stream, Bridge and Leading Arm created 1.5 Gyr ago at last perigalactic passage of SMC (and a close encounter with LMC) Yoshizawa & Noguchi (2003): Detailed simulation of SMC: N-body + gas dynamics (sticky particles); no ram pressure,, no live LMC and MW Starless stream created by extended gas disk in SMC

25 More recent models: Weinberg (1998,2000): tidal models II LMC evolution strongly affected by torque due to Milky Way and vice versa LMC disk is thickened Bekki & Chiba (2005): N-body/sticky particles for LMC; SMC and MW by rigid spherical potentials+dynamical frictions Star formation and chemical evolution included Formation of a barred, thickened disk embedded in a hot stellar halo Globular cluster formation in LMC triggered by interaction with SMC (since( the last 3 Gyr)

26 More recent models: tidal models III Connors, Kawata & Gibson (2005): N-body for SMC; LMC and MW by rigid spherical potentials+dynamical frictions Stream of tidal origin Interaction between LMC and SMC results in spatial and kinematical bifurcation of Stream and Leading Arm

27 Meurer et al. (1985): More recent models: ram pressure Ram pressure included (restricted N-body) Stream without stars created But: too high gas densities in MW halo required Moore & Davis (1994): Ram pressure important in passages through the extended MW disk Leading arm, high gas velocities? Mastropietro et al. (2005): N-body/SPH simulations for LMC motion in MW halo Removal of M gas (Stream) No response by MW disk; MW tides truncate LMC disk to 11 kpc SMC not considered

28 (Almost) Missing model ingredients Consistent LMC-SMC interaction: both dynamically live including star formation and stellar feedback including ram pressure Self-consistent treatment of Milky Way: mutual response of both Clouds and MW halo non-spherical, non-stationary MW halo self-consistent dynamical friction live gaseous halo What do we really know about the parameter space?

29 Great circles and the Local Group satellite system (Sawa & Fujimoto 2005)

30 The Great Disk of the Milky Way Satellites around the Milky Way CDM halo distribution: (Kroupa, Theis & Boily 2005) Distribution highly anisotropic (Diemand et al. 2004)

31 Formation scenarios The satellite system is a remnant of cosmological structure formation (formed by infall along a cosmic web substructure) The satellite system is a remnant of a disrupted (Searle&Zinn) fragment (Lynden-Bell 1976, Majewski 1994) The satellite system is the result of an individual interaction event (e.g. Kroupa et al. 2005, Sawa&Fujimoto 2005)

32 The satellite system of the Milky Way-II II: the dsph system Questions: How important are tides for dsph? How much DM do dsph contain? How are the dsph formed? Is the dsph system a tracer of the MW DM halo? Is there an evolutionary link between the dsphs and the Magellanic System?

33 Collaborators Stefan Harfst (Rochester) Simone Recchi,, Gerhard Hensler (Vienna), Pavel Kroupa (Bonn) Christian Boily (Strasbourg), Thorsten Naab (Munich( Munich) Lia Athanassoula,, Albert Bosma (Marseille) Christian Brüns ns,, Nikolaus Neininger,, Uli Klein, Sven Kohle (Bonn) Adam Ruzicka, Jan Palous (Praha) Helmut Meusinger (Tautenburg) Jay Gallagher,, Linda Sparke (Madison) Werner Zeilinger (Vienna), Giovanna Temporin (Innsbruck)