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Fine tuning (or not) in structure formation simulations
Debora SijackiDebora Sijacki IoA & KICCIoA & KICC CambridgeCambridge
The Physics of Fine Tuning ConferenceThe Physics of Fine Tuning ConferenceJune 20 2017June 20 2017
2 From the CMB to the large scale structure
The initial conditions are directly observable
cosmic time
Millennium simulationSpringel et al. 2005
Planck 2015 results
3 Cosmological simulations of structure formation
Millennium XXL
40 yrs!
4
Large scale distribution of matter (and galaxies)
Boylan-Kolchin et al. (2009)
Hierarchical growth of dark matter halos
Springel et al. 2006
Angulo et al. 2012
Abundance of the rarestobjects in the Universe
Cosmological simulations of structure formation
5
Frenk et al. 1999
Cosmological simulation of a galaxy cluster (DM only)
Cosmological simulations of structure formation
6
Frenk et al. 1999
Cosmological simulation of a galaxy cluster (DM only)
Cosmological simulations of structure formation
7
Sembolini et al. 2016 (Nifty)
Cosmological simulation of a galaxy cluster (DM only)
Cosmological simulations of structure formation
8
Sembolini et al. 2016 (Nifty)
Cosmological simulation of a galaxy cluster (DM only)
Cosmological simulations of structure formation
9 But what about all the relevant physics?
radiative cooling and heating processesstar formationsupernovae feedback and stellar windsblack holes and AGN heatingnon-ideal plasma effectsnon-thermal pressure supportmagnetic fields,...
Perseus cluster, Fabian et al.
For ideal inviscid gasEuler equations: conservation laws for mass, momentum and energy
State vector:
Flux vector:
Hydrodynamical simulations
Equation of state:
Uncertainties in hydro solvers of different codes used to simulate galaxy formation
Much more careful code comparisons are needed!Improvements in basic code solvers
Eulerian mesh-based codes
(+ AMR)
Lagrangian particle-based Codes (SPH)
FLASH
ENZO
RAMSES
ART
ATHENA
GADGET
GASOLINEHYDRA
GODUNOVSPH
Hydrodynamical simulations
Non-radiative Cosmological simulation of a galaxy cluster (DM + GAS)
Frenk et al. 1999
Hydrodynamical simulations
Non-radiative Cosmological simulation of a galaxy cluster (DM + GAS)
Frenk et al. 1999
SPH simulations:power-law entropy profiles
GRID-based simulations:cored entropy profiles
Hydrodynamical simulations
Discrepancy between SPH and grid entropy profiles
Springel et al. 2010
Mitchell et al. 2009
FUNDAMENTAL IMPLICATIONS FOR UNDERSTANDING ASTROPHYSICS
Standard SPH simulations flawed (Sijacki et al. 2012)
nIFTy clusters comparison project; Sembolini et al. 2016
15
The Aquila comparison project Scannapieco et al. 2012
9 different codes, 13 runs with the same ICs but different physics“Despite the common halo assembly history, we find large code-to-code variations in the stellar mass, size, morphology and gas content of the galaxy at z=0, due mainly to the different implementations of star formation and feedback.
Physical (& numerical) modeling uncertainties
16
The Aquila comparison project Scannapieco et al. 2012
Physical (& numerical) modeling uncertainties
17
The Aquila comparison project Scannapieco et al. 2012
Physical (& numerical) modeling uncertainties
NEED FOR LARGE-SCALE COSMOLOGICAL NEED FOR LARGE-SCALE COSMOLOGICAL SIMULATIONS WITH A LARGE, STATISTICAL SIMULATIONS WITH A LARGE, STATISTICAL SAMPLE OF GALAXIESSAMPLE OF GALAXIES
18Current state-of-the-art in cosmological simulationsThe Eagle Project (Schaye et al. 2015) The Horizon AGN project (Dubois et al. 14)
Massive Black II (Khandai et al. 2015)Magneticum (Dolag et al. 2014)
19The Illustris project
Box size = 106.5MpcMin cell size = 48pc3 x 1820^3 dark matter particlesgas cellspassive tracers -> 18 billion8192 cores, 19 MCPUh
Physics:
primordial & metal line cooling+ self-shieldingstellar evolutionstellar feedbackgas recyclingchemical enrichmentblack hole growth & feedback
DM DENSITY with overlaid GAS VELOCITY
20
COSMIC STAR FORMATION RATE DENSITY
Genel, Vogelsberger, Springel, Sijacki, et al., MNRAS, 2014
The Illustris project
21
GALAXY MORPHOLOGIESThe Illustris project
Genel et al., MNRAS, 2014Vogelsberger et al., MNRAS, 2014 see also e.g. EAGLE, HORIZON AGN, MASSIVE BLACK and
MAGNETICUM projects
22
BHs in IllustrisBH MASS – BULGE MASS RELATION
Kormendy & Ho, 2013: best fitcircles: ellipticals; stars: spirals with bulges; squares: pseudo bulges
Sijacki et al, 2015
23
GAS DENSITY MAPS + VORONOI MESHNO REFINEMENT MODERATE AGRESSIVE
Curtis & Sijacki, MNRAS, 2015
How (dramatic) change in resolution affects the physics?
24
VORONOI MESHNO REFINEMENT MODERATE AGRESSIVE
Curtis & Sijacki, MNRAS, 2015
Resolving flows onto BHs
25
SAME BH FEEDBACK AT DIFFERENT RESOLUTIONS LEADS TOVERY DIFFERENT OUTFLOW
hot outflow
cold disk inflow
Curtis & Sijacki, MNRAS, 2015
Resolving flows onto BHs
26Powerful QSO outflow in a massive disk galaxy at z ~ 5
Curtis & Sijacki, MNRAS Letter 2015
Carniani et al. 2013 ALMA data of a QSO/SMG at z = 4.7
SAME BH FEEDBACK AT DIFFERENT RESOLUTIONS LEADS TO VERY DIFFERENT GALAXY MORPHOLOGY
(have we understood morphological evolution of galaxies and quenching?)
27
Smith, Sijacki & Shen, 2017, in prep.
How (dramatic) change in resolution affects the physics?
2000M⊙ 200M⊙
20M⊙
SAME SUPERNOVA FEEDBACK AT DIFFERENTRESOLUTIONS LEADS TO COMPLETELYDIFFERENT GALAXY MORPHOLOGIES
28
ConclusionsLessons learned:
1. Accuracy of hydro solvers still needs to be improved No “fine tuning” of baryonic physics to “cover up” for errors in hydro →
solvers
2. Sub-grid physics uncertainties still very large! Free parameters of sub-grid models “fine tuned” for specific observables→ Other results are in principle predictions, but….→
a) Different set of baryonic physics can lead to similar z = 0 results(redshift evolution is different) DEGENERACIES→
b) Same baryonic physics at different resolutions may lead to different results WHAT DO WE LEARN ABOUT PHYSICS?→
3. Next generation sub-grid models for SF and BH physics needed in large cosmological simulations
spatial resolution requirements daunting→ more cross-talk with “small-scale” community →
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