future modelling efforts eelco van kampen eso [email protected]
TRANSCRIPT
Modelling galaxy formation & evolution
• large-scale environment
• halo, galaxy & black hole merger histories
• gas physics
• star formation
• stellar population synthesis
• interstellar radiation field
• dust
• feedback processes (linking the above)
large-scale environment
anything left to do ?
Horizon project:thin redshift slice through a full sky cone(Pichon & Teyssier 2008)
Millennium-II run:a 100 Mpc/h box(Boylan-Kolchin 2009)
Mare Nostrum universe:area around the most massive galaxy cluster(Khalatyan 2005)
large-scale environment
• everything with gas, star formation, feedback, etc.
• constrained simulations to model specific objects
• multiple resolutions
Dark matter map of the A901/A902 supercluster
(Heymans et al. 2008)
halo, galaxy & BH merger history
• extracted from large simulations oranalytical formalisms
• issues:
- merger timescales
- subhalo heating, stripping, quenching, etc. etc.
- environmental effects
- multiple mergers (especially at high-z)
- black hole mergers and merger history
star formation & ISMmolecular cooling, interstellar radiation field (ISRF), star formation thresholds, ...
Differing models for the ISM and star formation, for three different galaxy masses(Robertson & Kravtsov 2008)New atomic & molecular cooling +
molecular density SF scaling with ISRF
New atomic & molecular cooling + molecular density SF scaling without ISRF
“Standard” atomic cooling + total gas density SF scaling + SF threshold model
stellar population synthesis models
long history, but outstanding issues
important for high-z galaxies is the modelling of the Thermally-Pulsing AGB phase of stellar evolution, most important for ages of around a Gyr
M05 models compared to others and to data(Maraston 2007)
)/exp()/exp( ddod zzRR −−=ρρ
Galaxy geometry used in GRASIL (Silva et al. 1998)
Disk: double exponential Bulge: King profile
γ=3/2
dust emission for normal galaxies
dust emission for other galaxies
How to model more complex geometries like merging galaxies, tidal interactions, or multiple mergers ?
UDF 2012(Elmegreen et al. 2009)
NGC 6240 (Spitzer image)(Bush et al. 2009)
Zw II 96(Evans et al. 2008)
feedback processes
Wind recycling appears to be a common phenomenon where galactic superwind feedback is re-accreted on a timescale usually much shorter than a Hubble time.
(Oppenheimer & Davé, 2008)
An example ...
Modelling galaxy populations
Phenomenological models or numerical simulations ?
Phenomenological :
- partly numerical, partly analytical, partly heuristic
- many assumptions and simplified scaling relations
- fast, so parameter space can be explored
Numerical:
- fully numerical down to resolution scale, below that analytical (‘subgrid physics’)
- expensive, limited to a few parameter sets and/or physical assumptions
Simulating star formation in disk galaxies:the future - 2015
•The ISM is fully resolved
•This means that the scale height of all ISM components are resolved using at least 10 resolution elements (Romeo 1994). This translates into at least ∆x∼1 pc. If this is not satisfied the true disk stability will not be modelled accurately. At such a resolution, star formation occurs in their natural sites i.e. massive clouds such as GMCs. This treatment is the goal of most simulations but is due to their computational load beyond the capabilities of modern simulations attempting to study the assembly and evolution of large spiral galaxies to z = 0. In addition, as the star formation sites become resolved the codes need to incorporate the radiative feedback in order to accurately treat the life-times of the GMC structures (Murray et al. 2009).
Pandora’s box (new small scale physics must be treated)!
Computationally impossible in a cosmological context today
From Ben Moore’s talk:
summarysummary observed mass assembly history and SFR
history reproduced (w/in observational errors) for massive galaxies (M*>few 1010 Msun)
low mass galaxies form too early, are too passive at all redshifts (z<2), and have stellar pops that are too old at z~0
may indicate that modelling of SN FB in current models needs to be modified
possible dearth of both very rapidly SF galaxies and quenched galaxies at z~2
latest models still fail to reproduce enough bright SMGs
observed mass assembly history and SFR history reproduced (w/in observational errors) for massive galaxies (M*>few 1010 Msun)
low mass galaxies form too early, are too passive at all redshifts (z<2), and have stellar pops that are too old at z~0
may indicate that modelling of SN FB in current models needs to be modified
possible dearth of both very rapidly SF galaxies and quenched galaxies at z~2
latest models still fail to reproduce enough bright SMGs
From Rachel Somerville’s talk:
Dec 15th 2009 Desika Narayanan Obergurgl
Ways Forward: Velocity Fields with ALMA
Davé et al 2009: Harassment
Narayanan et al 2009b: Major Mergers
From Desika Narayanan’s talk:
SED and SPH galaxy models: GRASIL3D A.Schurer 09 PhD theses
Aim: exploit the spatial information for stars and gas in hydro simulations of galaxy formation and of observed images – requires no symmetries
GRASIL->3D: •generalised to an arbitrary geometry through a cube grid in which stars and gas particles output by the SPH are distributed• Gas in each cell divided in SF molecular clouds and cirrus (if young stars are present and gas density > threshold)• Intrinsic stellar SED in each cell, with young stars within MCs• Radiation field in each cell due to all other cells
1° Application : P-DEVA (Serna & Dominguez-Tenreiro) + GRASIL3D
From Laura Silva’s talk:
Modelling galaxies here and there ...
My current modelling efforts:
•STAGES: modelling a multi-wavelength dataset for the A901/A902 supercluster
•SHADES: modelling the sub-mm galaxy population
•GAMA and Herschel-ATLAS: clusters and clustering
My future modelling efforts:
•SERVS: galaxy evolution vs. environment
•SCUBA-2 cosmology legacy survey: clustering and proto-clusters
•proto-cluster galaxies with ALMA, LMT, ...
SHADES: SCUBA half-degree survey
Lockman & SXDF @ 850 micron
SHADES: flux vs. photo-z
Schael et al. (2010)
SHADES vs. phenomenological models
model 1: fiducial model 6: more quiescent star formation (in disks)model 7: more bursting star formation (merger-driven)
Black lines: total SFR density (blue: bursting, red: quiescent)
Flux versus photo-z
Flux versus stellar mass
Stellar mass components
Simulations and simulators
science simulations (sky images)
telescope simulators (simulates corruption of sky images by the telescope, detectors, etc.)
For ground-based telescopes (JCMT, ALMA, etc.) one needs to simulate the atmosphere as well.
Most useful for the more complex observing modes.
Interferometer simulatorsThe simdata interferometer simulator (part of the CASA package) produces
•synthetic visibilities•a synthesized deconvolved image•some analysis tools (image fidelity etc.)
The simdata simulator models:•thermal noise•cross-polarization leakage, gain drift•atmospheric phase delay (using a mock phase screen)
ALMA, last week
An example: M51
A continuum subtracted H alpha image of the nearby galaxy M51 (NGC 5194 -- provided by D. Thilker at NRAO).
This H alpha image should be a reasonable representation of the atomic FIR lines and other tracers of massive star formation.
M51 ‘observed’ with ALMA
M51 at lower redshift(and using a larger mosaic)
Sub-mm map-making
from model galaxies to a mock sub-mm map ...
A blank field (850 micron at the JCMT)
With a proto-cluster at z=3.8
TAMASISTAMASIS is an ASTRONET funded project aiming at enhancing the science that can be produced from submillimeter surveys
The aim is to:
provide reliable, easy-to-use, and optimal map-making tools for Herschel and future generation of sub-mm instruments, so that the ambitious science objectives that are set for these facilities can be met.
aid the interpretation of future sub-mm datasets by generating observation-like mock maps from the theoretical models, and improving the models themselves
develop along the way specific data analysis tools requested for map-making performance assessments. Deconvolution and source detection are two areas where the ability to take in multi-wavelength data will make a significant difference.
TAMASISSpecifically, TAMASIS aims to achieve the following goals:
1. Produce simulations of the sub-mm flux distribution on the sky, in cosmology, star formation and Galactic structure. These models will be "observed" with the instrument simulators to provide controlled input samples to aid in algorithmic development and evaluation. In a further stage, these simulations will produce mock maps that can be directly compared to observed maps.
2. Improve and develop techniques to produce sub-mm maps, focusing on scan maps because they represent the observing mode of choice.
3. Improve and develop techniques to analyze scan maps, from source detection to fluctuation analysis methods.
4. Produce realistic mock maps for those legacy surveys which are of particular interest to the ASTRONET partner countries, for example Herschel ATLAS and HI-GAL
5. Deliver over the course of the project to the astronomical community tools and test maps that will have been thoroughly validated to allow others to benefit from our efforts.
TAMASIS
Saclay: Marc Savage, Pierre ChanialOrsay: Alain Abergel + post-docLeiden: Paul van der Werf, Rowan MeijerinkESO: Eelco van Kampen, Juan Gonzalez
ASTROSIM network
This programme aims to bring together European computational astrophysicists working on a broad range of topics from the stability of the solar system to the formation of stars and galaxies.
AstroSim provides funding for conferences, workshops, training schools, exchange visits and collaborative travel. It’s easy to apply, decisions are made quickly with little bureaucracy.
For more information talk to Ben Moore, or goto http://www.astrosim.net/
Summary
• modelling of galaxies is getting more and more sophisticated in all parts
• galaxy populations still need to be simulated using phenomenological models of galaxy formation
• such models have variable success still
• instrument simulators should be used to predict data for more complex observing modes, eg. mapping
• collaborative networks exist to assist the community, eg. TAMASIS and ASTROSIM