Dynamical Modelling in the Cosmic Web

Dynamical Modelling in the Cosmic Web

IllustrisTNG Science Conference, MPA Garching.

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Chris Duckworth

October 15, 2018
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Transcript

  1. None
  2. • Halo assembly bias: • the dependence of the clustering

    of dark matter halos on physical parameters outside of halo mass. (e.g. halo age, shape, spin) • E.g. Sheth & Tormen04, Gao+05, Wechsler+06, Dalal+08 • Linked to the large scale tidal environment which is a direct effect of the anisotropy of the cosmic web! • (e.g. Hahn+09,Tojeiro+17,Kraljic+18) • Found in various flavors of simulation but yet to converge in observations
  3. Discrete Persistent Structures Extractor Sousbie 2011, MNRAS 414, 350 Sousbie+

    2011, MNRAS, 414, 384 Discrete points (e.g. galaxy positions) Density field estimation (Delaunay tessellation) Structure identification (Morse-Smale complex)
  4. TNG300-1: Identified up-skeleton (filaments connecting nodes and saddle points)

  5. (Borzyszkowski+16) In rest-frame of the halo: Blue = in-falling material

    Red = material moving away z = 0 z = 0
  6. (Faltenbacher & White 10) (Garaldi+17) How can we trace anisotropy?

    Substructure… Particles… β = 1 – σ2 tan / 2σ2 rad
  7. • Actual observation: • Duckworth+ (submitted): No correlation between accretion

    rate seen by rotation offset between stars and gas with vicinity to filaments (or nodes!) • Theory: • Low mass halos can have their accretion ’stalled’ due to proximity of filaments of width larger than the halo (e.g. Borzyszkowski+16) • Possible observation: • Accretion rate on to the central galaxy is also `stalled’, reflected in an alignment in the rotation of stellar and gas components (wrt. to control `field’ sample).
  8. • Actual observation: • Duckworth+ (submitted): No correlation between accretion

    rate seen by rotation offset between stars and gas with vicinity to filaments (or nodes!) • Possible observation: • Accretion rate on to the central galaxy is also `stalled’, reflected in an alignment in the rotation of stellar and gas components (wrt. to control `field’ sample).
  9. • Theory: • Low mass halos can have their accretion

    ’stalled’ due to proximity of filaments of width larger than the halo (e.g. Borzyszkowski+16) • Possible observation: • Intrinsic difference in the orbits of satellites around the central subhalo? • Difference in velocity anisotropy?
  10. Stacking TNG300 haloes: 1011.8-1012.5 M☉ PRELIMINARY

  11. CJAM : Jeans Anisotropic MGE modelling code written in C

    Watkins+13, https://github.com/lauralwatkins/cjam Adaptation to include chemical properties: Zhu+16 1) Construct MGEs of tracer population + gravitational potential (or functional form) 2) Solve Jeans’ equations taking each tracer position as a prior and compare model velocity to the observed (line-of-sight) 3) Use maximum likelihoods to find best fit free parameters + prediction for 3D velocities for all tracers! sub-divide tracer populations with different chemical & dynamical properties!
  12. (Watkins+13)

  13. None
  14. To be released: • Cosmic web identification in TNG300 using

    DisPerSE • Velocity anisotropy for stacked halos in different environments In progress/To do: • JAM for satellites stacked in different cosmic web environments • Is this ‘stalled’ accretion visible on the central galaxy kinematics in TNG? • Comparison of DisPerSE with tidal tensor. Do particle movements between snapshots match identification of these environments? cd201@st-andrews.ac.uk