S 1 Galaxy formation in the cosmic web Credit: Guzzo & VIPERS - PowerPoint PPT Presentation

08/07/2016 Charlotte Welker Mergers and Gas accretion onto galaxies: the imprint of the cosmic web Collaborators: Chris Power(ICRAR), Pascal Elahi (ICRAR) Christophe Pichon (IAP), Julien Devriendt (Oxford), Yohan Dubois( IAP),Sandrine Codis (CITA), Clotilde Laigle (IAP) S 1

Galaxy formation in the cosmic web Credit: Guzzo & VIPERS team (2013) ☛ Galactic properties correlated to anisotropically distributed density: Implications? ☛ Angular momentum hidden variable?

The Hubble sequence Hubble (1936) Credit: NASA, ESA, M. Kornmesser Spirals Ellipticals Lenticulars (+Irregulars) j Rotation supported Dispersion supported Barred spirals 3

Simulations in this talk: ☛ Cosmological Hydrodynamical runs with Gadget and Ramses. ☛ Hydrodynamical zooms on haloes with Gadget, Ramses, Arepo. ☛ Large scale cosmological “full physics” run with Ramses: Horizon-AGN 100 Mpc.h-1 cubic box UV reheating, cooling, star formation, metal release feedback from SNI, SNII, AGN: quasar and jets 1 kpc maximal resolution 4

Tracing spin swings in the Cosmic web Pick your favourite cosmic web Ø Detecting the ridge lines of the density field extractor…. Ø Fully connected network Ø Topolological extractor, naturally multiscale Gas, 10 Mpc projected map Ø DisPerse: can be applied on real data (particles or grids) Ø No smoothing: persistence level, “S/N ratio threshold” Filament segment θ µ = cos( θ ) L L Horizon-AGN: Skeleton (Sousbie 2009 +DisPerse, Sousbie 2011) 5

[1] Kinematics of the cosmic web: a a brief recap Cosmic Flows in the vicinity of filaments. S 6

Kinematics of the cosmic web DM Particle tracers Void Filament Credit: Laigle et al 2015. 7

Kinematics of the cosmic web DisPerse extracted LSS features particle tracers Wall Filament Void Credit: Laigle et al 2015. 8

Kinematics of the cosmic web Voids towards walls 9

Kinematics of the cosmic web Walls towards filaments 10

Kinematics of the cosmic web Filaments towards nodes 11

Kinematics of the cosmic web High vorticity regions 12

Kinematics of the cosmic web High vorticity regions Galaxies in the vicinity of filaments 13

Vorticity-filament alignment Laigle et al 2015 Vorticity Sz maps (filament cross-sections) PDF of the vorticity-filament angle f lament ω =rot(v) direction walls Credit: Laigle et al 2015. 14

The gaseous cosmic web ☛ DM particles shell-cross but gas shocks and radiatively cools: gas filaments significantly thinner than DM counterpart! Gas (AMR) Dark matter particles Z=3.8 Mh=2 10^12 Msun Rvir=79 kpc Credit: Pichon et al 2011. 15

2.1) Structure of gas inflows Nifty comparison, in prep Large scales: ☛ DM particles shell-cross but gas shocks and radiatively cools: Ø 10^14 -10^15 M sun clusters: connectivity remains around 3-5 gas filaments significantly thinner than DM counterpart! 8 8 GAS 4 4 y (Mpc/h) z (Mpc/h) 0 0 -4 -4 Tilted ring -8 -4 0 4 8 -8 -4 0 4 8 16 x (Mpc/h) y (Mpc/h)

2.1) Structure of gas inflows Nifty comparison, in prep Skeleton (filaments) Highest robustness 0.8 Ø filamentary structure survives shocks at ~1-2 0.6 Rvir Ø Tested with RAMSES, 0.4 GADGET, AREPO (Nifty comparison) 0.2 Tilted ring 0.2 0.4 0.6 0.8 17

2.1) Structure of gas inflows Nifty comparison, in prep Skeleton (filaments) Anti-skeleton (depletion contours) 1 1 Mpc.h-1 0.5 Ø filamentary structure survives shocks at ~1-2 y ( /R 200 ) Rvir 0 Ø Tested with RAMSES, GADGET, AREPO -0.5 (Nifty comparison) Tilted ring -1 1 -1 0 0.5 -0.5 18 x ( /R 200 )

Structure of gas inflows Cold flows at z>1 - torques from misaligned halo/galaxy - Net angular momentum transfer from neighbouring ☛ DM particles shell-cross but gas shocks and radiatively cools: “pushing” voids (cause braided vorticity tubes). gas filaments significantly thinner than DM counterpart! Helix like structure (Pichon 2011, Danovich 2015) Z=1.33 Inner halo 0.35 Rvir 30 kpc Cold gas Z=2.33 Tilted ring streamlines Credit: Danovich 2015. 19

[2a] Impact on the spin of haloes and galaxies 1) Simulated haloes 2) Simulated galaxies 3) Real galaxies S 20

Swings for dark haloes in simulations… Low mass halo Massive halo Aragon-Calvo 2007, Hahn 2007, Paz 2008, Codis 2012 21

It holds true for synthetic galaxies (multiple tracers) Spin orientation distribution for galaxies 1.10 1.10 1.10 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 z=1.83 log M /M o =10.75 g − r = − 0.04 log M /M o =10.25 g − r =0.09 1.05 1.05 1.05 log M /M o =9.75 g − r =0.21 g − r =0.34 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1+ ξ 1.00 1.00 1.00 0.95 0.95 log M /M o =9.25 0.95 log Z/Z o = − 0.66 log M /M o =8.75 log Z/Z o = − 0.87 log Z/Z o = − 1.14 0.90 0.90 0.90 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 cos θ cos θ cos θ cos θ cos θ cos θ cos θ cos θ cos θ cos θ ☛ We recover the alignement/ Log(M trans /M sun )= 10.25-10.75 perpendicular signal. Consistent with dark haloes Low-mass, young, centrifugally supported, metal-poor, bluer galaxies : aligned Massive, high velocity dispersion, red, metal-rich old galaxies: perpendicular Dubois, Pichon, Welker et al 2015 22

… and real galaxies likewise! Tempel & Libeskind 2013 ☛ recent observations in SDSS ! z<0.5 SDSS DR8 Elliptical galaxies : perpendicular to filaments θ µ= cos ( θ ) L Spiral galaxies : aligned with filaments 23

[2b] Mechanisms of spin acquisition 1) Eulerian view: smooth accretion vs mergers 2) Lagrangian theory S 24

Spin swing dynamics Smooth accretion SMOOTH PDF of µ over 4 timesteps δ t ACCRETION 1.06 p=n+4 1.04 p=n+3 p=n+2 p=n+1 1.02 time ☛ Gas inflows (re)-align galaxies with their filament 1+ ξ 1+ ξ 1+ ξ 1.00 0.98 δ t = 250 Myr 0.96 0.0 0.2 0.4 0.6 0.8 1.0 μ µ= cos ( θ ) Spin-filament angle θ L ξ : excess probability 25

Spin swing dynamics Mergers MERGERS PDF of µ for different merging histories δ m>0, n m =1 Lgal 1.2 1 L gal δ m>0, n m =2 v δ m>0, n m >2 Lgal2 n m : number of mergers 1.1 Mergers drive galactic spin 1+ ξ 1+ ξ flips. 1.0 ☛ Mergers flip the spin 0.9 perpendicular to the Δ m=0, 9.4 < Γ < 9.6 filament Δ m=0, 9.6 < Γ < 9.7 0.8 Stronger signal than for 0.0 0.2 0.4 0.6 0.8 1.0 μ galactic properties! Red to pink: µ= cos ( θ ) merged between z=5.2 and z=1.8 θ Blue to yellow: never merged, Γ =log(M/Msun) L 26

A lagrangian theory exits! See Codis et al 2015. Tidal Torque Theory: ☛ In the vicinity of a filament: anisotropic environment ! See Codis et al 2015. 27

Insights from lagrangian theory See Codis et al 2015. ☛ Proto-filament in the initial density field: Ø Line connecting two maxima (proto-nodes) through a saddle point maximum saddle point minimum 2D gaussian random field 28

Insights from lagrangian theory See Codis et al 2015. In the plane of the saddle point orthogonal to filament: 2D density map 2D spin map We recover the quadrants ! T I 29

Insights from lagrangian theory See Codis et al 2015. ☛ Same GRF analysis around a filament-type saddle point constraint in 3D: ☛ Compute expectations for δ and s Sketch of the spin distribution Density map 30

[2c] Impact on the mopholgy of galaxies Statistical study in Horizon-AGN S 31

Morphological variety in Horizon-AGN Rest-frame colour images of synthetic galaxies Colour (g-r) blue red 10.0 11.0 mass 11.7 irregular elliptical disk 32

Galactic Morphologies Inertia tensor: Moments and ellipsoid axis: λ 1 > λ 2 > λ 3 I ij = Σ l m l ( δ ij . ( x l k .x l k ) − x l i .x l j ) c < b < a c ? c a a b b Disks : c/a < 0.45 Spheroids: c/a > 0.7 b/a< 0.55 b/a >0.8 33

� � Galactic morphologies: Smooth accretion Axis ratio: c/a SMOOTH ACCRETION 1.0 disks Gas inflows flatten spheroids spheroids over time along the filament 0.8 direction Cumulative probability Time 0.6 P( ξ i > Ξ ) 1.5 Gyr 0.4 0.2 Dark to light: 1.5 Gyr Cumulative probability of 9.5<log(M/Msun)<10.5 0.0 axis ratios ξ over a time step (250 Myr) 0.2 0.4 0.6 0.8 1.0 34 ξ 1 =c/a

� Galactic morphologies: Smooth accretion log(M/Msun)>10.5 SMOOTH ACCRETION Axis ratio: c/a Gas inflows flatten spheroids 1.0 over time along the filament direction Cumulative probability 0.8 Up to the transition mass! 0.6 P( ξ > Ξ ) 0.4 0.2 Dark to light: 1.5 Gyr Cumulative probability of axis ratios ξ over a time 0.0 step (250 Myr) 0.2 0.4 0.6 0.8 1.0 35 ξ 1 =c/a

� � [2b] Galactic morphologies: Mergers Axis ratio: c/a MERGERS 1.0 Mergers turn disks into 0.8 spheroids Cumulative probability δ m 0.6 Even minor mergers can P(> Ξ ) δ m = 0 create spheroid remnants 5% < δ m < 9% 0.4 9% < δ m < 20% δ m > 20% 0.2 Cumulative probability of axis ratios ξ for mergers 0.0 with different mass ratios over a time step (250 Myr) 0.2 0.4 0.6 0.8 1.0 ξ 1 = c/a 36

j-M scaling relations : variations with gas fraction 0.95 f gas 37