Various Mostly Lagrangian Things Mark Neyrinck Johns Hopkins
University Collaborators: Bridget Falck, Miguel Aragn-Calvo, Xin
Wang, Donghui Jeong, Alex Szalay Tracing the Cosmic Web, Leiden,
Feb 2014 Slide 2 Mark Neyrinck, JHU Outline Comparison in
Lagrangian space Comparison in Lagrangian space Halo spins in an
origami model Halo spins in an origami model Lagrangian
substructures Lagrangian substructures Incorporating rotation into
a velocity-field classification Incorporating rotation into a
velocity-field classification Halo bias deeply into voids with the
MIP Halo bias deeply into voids with the MIP Slide 3 Mark Neyrinck,
JHU Information, printed on the spatial sheet, tells it where to
fold and form structures. 200 Mpc/h Slide 4 Why folding? In phase
space... (e.g. analytical result in Bertschinger 1985) Mark
Neyrinck, JHU Slide 5 N-body cosmological simulation in phase
space: a 2D slice Mark Neyrinck, JHU x vxvx y x z y Slide 6 Eric
Gjerde, origamitessellations.com Rough analogy to origami:
initially flat (vanishing bulk velocity) 3D sheet folds in 6D phase
space. - The powerful Lagrangian picture of structure formation:
follow mass elements. Particles are vertices on a moving mesh. -
Eulerian morphologies classified by Arnold, Shandarin &
Zeldovich (1982) - See also Shandarin et al (2012), Abel et al.
(2012) Slide 7 (Neyrinck 2012; Falck, Neyrinck & Szalay 2012)
The Universes crease pattern Crease pattern before folding After
folding Slide 8 Mark Neyrinck, JHU Web comparison in Lagrangian
coordinates Warming up: Lagrangian Eulerian Lagrangian for ORIGAMI
Slide 9 Mark Neyrinck, JHU Web comparison in Lagrangian coordinates
ORIGAMI Slide 10 Mark Neyrinck, JHU Web comparison in Lagrangian
coordinates Forero & Romero Slide 11 Mark Neyrinck, JHU Web
comparison in Lagrangian coordinates Nuza, Khalatyan & Kitaura
Slide 12 Mark Neyrinck, JHU Web comparison in Lagrangian
coordinates NEXUS+ Slide 13 Flat-origami approximation
implications: - # of filaments per halo in 2D: generically 3,
unless very special initial conditions are present. - # of
filaments per halo in 3D: generically 4. Unless halo formation
generally happens in a wall Assumptions: no stretching, minimal
#folds to form structures Slide 14 Flat-origami approximation
implications: Galaxy spins? To minimize # streams, haloes connected
by filaments have alternating spins Are streams minimized in
Nature? Probably not, but interesting to test. A void surrounded by
haloes will therefore have an even # haloes before mergers Slide 15
Chirality correlations Connect to TTT (tidal torque theory): haloes
spun up by misaligned tidal tensor, inertia tensor. Expect local
correlations between tidal field, but what about the inertia tensor
of a collapsing object? - Observational evidence for chiral
correlations at small separation ( Pen, Lee & Seljak 2000,
Slosar et al. 2009, Jiminez et al. 2010) Slide 16 ORIGAMI halo
spins in a 2D simulation Galaxy spins? To minimize # streams,
haloes connected by filaments have alternating spins A void
surrounded by haloes will therefore have an even # haloes Slide 17
Mark Neyrinck, JHU Lagrangian slice: initial densities Slide 18
Mark Neyrinck, JHU Lagrangian slice: VTFE* log-densities *Voronoi
Tesselation Field Estimator (Schaap & van de Weygaert 2000)
Slide 19 Mark Neyrinck, JHU Lagrangian slice: LTFE* log-densities
Halo cores fairly good-looking! *Lagrangian Tesselation Field
Estimator (Abel, Hahn & Kahler 2012, Shandarin, Habib &
Heitmann 2012) Slide 20 Mark Neyrinck, JHU Lagrangian slice:
ORIGAMI morphology node filament sheet void Slide 21 LTFE in
Lagrangian Space evolution with time Slide 22 Mark Neyrinck, JHU
Time spent as a filament/structure map Slide 23 Morphologies with
rotational invariants of velocity gradient tensor Slides from Xin
Wang Slide 24 SN-SN-SN (halo)UN-UN-UN (void)SN-S-S (filament)UN-S-S
(wall) 1Mpc/h Gaussian filter, using CMPC 512 data SFSSFCUFSUFC
both potential & rotational flow Slides from Xin Wang Slide 25
Stacked rotational flow from MIP simulation Slides from Xin Wang
Slide 26 Halo bias deeply into voids without
stochasticity/discreteness with Miguels MIP simulations Mark
Neyrinck, JHU MN, Aragon-Calvo, Jeong & Wang 2013,
arXiv:1309.6641 Slide 27 Comparison of: Halo-density field with
Halo-density field predicted from the matter field Mark Neyrinck,
JHU Not much environmental dependence beyond the density by eye!
Slide 28 Conclusion Visualization of the displacement field Mark
Neyrinck, JHU
