ay202a galaxies dynamics lecture 23 galaxy evolution n.
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AY202a Galaxies & Dynamics Lecture 23: Galaxy Evolution PowerPoint Presentation
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AY202a Galaxies & Dynamics Lecture 23: Galaxy Evolution

AY202a Galaxies & Dynamics Lecture 23: Galaxy Evolution

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AY202a Galaxies & Dynamics Lecture 23: Galaxy Evolution

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  1. AY202a Galaxies & DynamicsLecture 23:Galaxy Evolution

  2. CMD’s for local dwarfs Tolstoy. Hill & Tosi 2009 LG Dwarfs SFR

  3. Dynamical Evolution Galaxy shapes affected by dynamical interactions with other galaxies (& satellites) Galaxy luminosities will change with accretion & mergers SFR will be affected by interactions Mergers – the simple model Rate P = π R2 <vrel> N t P = probability of a merger in time t R = impact parameter N = density vrel = relative velocities

  4. N h-3 rc h vrel 0.05 Mpc-3 20 kpc 300 km/s Roughly P = 2x10-4()( )2( ) 1/H0 a small number, but we see a lot in clusters N ~ 103 – 104 N field V rel ~ 3-5 V rel field The problem was worked first by Spitzer & Baade in the ’50’s, then Ostriker & Tremaine, Toomre2 and others in the ’70’s

  5. Mergers occur depending on the Energy and Angular Momentum of the interaction

  6. Milky Way Andromeda collision (Dubinski) M31 MW Androway

  7. NGC3923 Shell galaxy D. Malin

  8. Time evolution of an encounter between an exponetial disk and a spheroid of mass 100x in units of the circular period. Bar under 0 is ten scale lengths for the disk

  9. Velocity-Radius Shells Quinn ‘84

  10. Results from n-body simulations: (1) Cross sections for merging are enhanced if angular momenta of the galaxies are aligned (prograde) and reduced of antialigned (retrograde) (2) Merger remnants will have both higher central surface density and larger envelopes --- peaks and puffs (3) Head on collisions  prolate galaxies along the line of centers, off center collisions  oblate galaxies

  11. An additional effect is Dynamical Friction (Chandrasekhar ’60) A satellite galaxy, Ms, moving though a background of stars of density ρ with dispersion σ and of velocity v is dragged by tidal forces wake formed & exerts a negative pull (Schombert)

  12. dv/dt = -4πG2 MSρ v-2 [φ(x) – xφ’(x)] lnΛ where φ = error function x = √2 v/σ Λ = rmax/rmin (maximum & minimum impact parameters) usually rmin = max (rS, GMS/v2) If you apply this to typical galaxy clustering distributions, on average a large E galaxy has eaten about ½ its current mass. Giant E’s in clusters are a special case.

  13. L Ostriker & Hausman ’78 Simulations for 1st ranked galaxies (BCG’s) 1. Galaxies get brighter with time due to cannibalism (L) 2. Galaxies get bigger with time (β) 3. Galaxies get bluer with time by eating lower L, thus lower [Fe/H] galaxies Core radius 5 different simulations of eating 30 neighbors Profile

  14. Chemical Evolution Simplest Model Closed Box Reprocessing = - + MG(t) = MG0 –M*(t) + ME(t) ME complicated  ME(m,t) usually assume for M < 3 M, ME(t) ~0 dMG dM* dME dt dt dt Gas Stars Ejecta from evolving * (winds, SN)

  15. dMz/dt dM*/dt Yield y(t) = dMz/dt = rate at which newly formed metals are ejected from stars To make this work we need the theory of element formation. BBFH 1957 etc. see Arnett ARAA 1995 also work bya variety of other authors.

  16. Neutron Capture

  17. S Process Silver to Antimony Slow neutron capture in stars. Neutron capture slower than beta decay.

  18. R Process Rapid neutron capture relative to beta decay. Primarily in core collapse SN.

  19. Structure of an evolved 25 M Star

  20. Predicted Yields

  21. Where the elements come from

  22. Element Production (Pagel)

  23. SN Ia

  24. Tayler’s Disk Model SFR = dM*/dt = C μn μ = gas surface density and assume the Instantaneous Recycling approximation  some fraction α of gas is not returned to the gas mass and a fraction 1- α is returned instantaneously, metal enriched μ = μ0 – α s , s= stellar density Then dμ/dt = -α ds/dt = -α Cμn = -μn /t0 where t0 = 1/αC is the characteristic time constant for significant changes in the disk gas density

  25. If z is the fraction of heavy elements by mass in the gas, and λ is the fraction of mass in stars which is converted completely to heavy elements and ejected into the ISM. If we define zμ as the fraction of heavy elements per unit mass+ in the disk d(zμ)/dt = -z ds/dt + (1-α –λ) z ds/dt + λ ds/dt then the yield Y = λ/α = the ratio of the mass converted into heavy elements to the mass locked up in stars, and we have d(zμ)/ds = λ (1 – z) - αz loss due to SF return due to winds w no processing return of completely processed material + mass includes both stellar and gas

  26. Substituting for S d(zμ)/ds = μ dz/ds + z dμ/ds = -αμ dz/dμ – α z  -μ dz/dμ = dz/d(ln 1/μ) = λ (1 – z) /α λ/α is usually termed the yield Y, the ratio of the mass completely converted to heavy elements to the mass locked up in stars. (in the limit of small z) dz/d(ln 1/μ) = Y  z = Y ln(1/μ) so the heavy element abundance is simply related to the net fraction of the mass of gas turned into stars For the simple Tayler model the yield is ~ 0.004

  27. Curve of Growth for a typical Voigt line profile – Linear Log Sq Root

  28. However, the Tayler model fails to fit the data. data

  29. Model Cumulative histogram of N vs z N z The G dwarf problem --- most nearby stars are metal rich Data

  30. Possible solutions 1. Prompt Initial Enrichment (PIE) 2. Variable IMF with increased yields in the past 3. Metal enhanced star formation  stars for preferentially in high [Fe/H] regions 4. Infall --- gas not described by a closed box “4” may be best – we expect infall in most formation scenarios, but we need a variable infall rate MG(t) = MG0 + ME(t) - M*(t) + MI(t) all of 1-4 probably operate in the galaxy

  31. Metallicity Gradients Simple model has one important success --- successfully predicts linear metallicity gradients in spirals z(r) = z0 – r (1/rT – 1/rG) rT = scale length of total mass density rG = scale length of total gas density

  32. Zaritsky, Kennicutt & Huchra

  33. Ages from ubvyHphotometry

  34. = 0.00 = 2.35 = 4.00

  35. SN II Production SN Ia Production Element Ratios

  36. Population Box Baade’s simple view

  37. Hodge’s population box SFR [Fe/H] AGE

  38. M31 Population Box

  39. IMF Redux