extragalactic astronomy and cosmology at ifa edinburgh
TRANSCRIPT
Extragalactic Astronomyand Cosmology at IfA Edinburgh
Timetable for the day
11:00 Closed Panel session
11:30 Presentations Part-1
12:50 Lunch
13:40 Presentations Part-2
14:50 Q & A session
15:50 Closed Panel Session
17:00 End
Schedule of Talks
11:30 Andy Lawrence Introduction11:40 Jim Dunlop Overview talk-111:50 Philip Best High-z galaxy evolution12:05 Marek Kukula Host galaxies of quasars12:20 Omar Almaini Deep X-ray surveys and AGN12:35 Will Percival Modelling AGN evolution new bid
LUNCH
13:40 John Peacock Overview talk-213:50 Alan Heavens Statistical methods for cosmology vacant14:05 Eelco van Kampen Simulating galaxy formation14:20 Avery Meiksin Simulating evolution of the IGM new bid
14:35 Arjun Berera Observational tests of inflation new bid
Key Points
Grant supports 9 academic-equivalent staff
– main activity of 6, partial activity of 3
– Peacock, Taylor, Jimenez and Berera added as PIs
Talented and aggressive team of PDRAs
Case presented as clear projects
– science a continuum but deliverables distinct
PDRAs nurtured but do cycle through
– Hughes, Taylor, Jimenez all moved through
Edinburgh context
Institute for Astronomy– 7 ac. staff; 4.5 senior research fellows (half of Berera)
– Temporary Lecturer being recruited
– 5 PDRAs on rolling grant support + 1 on Gemini grant
– WFAU : 6.5 research staff, 4.5 tech/admin (2.2 research FTEs)
Astronomy Technology Centre– approx 11 active astronomers; 3.5 research FTEs
Astronomy elsewhere in University– 3 academic staff in Maths/Physics (Heggie/Ruffert/Shotter)
– 0.5 senior research fellows in Physics (Berera)
Current bid
Merges existing roller and Peacock PDRA
Focused on extragalactic and cosmology
– star formation and low mass stars excluded
– supported to some extent in ATC and WFAU
Baseline 5 PDRAs : bid for +3
PDRA bid summary
Hi-z funded Y1-2 bid+2yr Best in place (Hughes left)
Hosts funded Y1-2 bid+2yr Kukula in place
X-AGN funded Y1 bid+3yr Almaini in place
AGN evoln new line bid+4yr Percival in place (1 yr contract)
Stat.cos. funded Y1-2 bid+2yr vacant (Taylor got AF)
Sim.cos. funded Y1 bid+3yr Van Kampen in place
IGM new line bid+4yr
Inflationnew line bid+4yr
Notes : Hughes left early + Kukula spell at STScI
unspent funds 1 year contract to Percival
Part 1
4 named PDRAs (3 existing grant lines + 1 new one)
Linking themes:
• Major multi-frequency surveys
• Cosmological evolution of AGN, galaxies & clusters
• Physical connections history of AGN activity history of star-formation activity
black hole formation host spheroid formation
History of black hole activity History of star-formation activity(Radio & X-ray) (Visible & Dust-enshrouded)
Key issues
Black-hole formation Host spheroid formation
Radio Galaxies
Sub-mm evolution contrasts withradio evolution especially at z > 2.5(Archibald, Dunlop et al. 2000)
Stars
Dust
Gas
But perhaps this makes sense….
Big black holes are needed by z= 3and hence perhaps also big bulges
Friaca/Jimenez models predictgrowth of stars and decline of dustfor formation redshift z = 5
Philip Best • z distribution of the field sub-mm population• sub-mm - optical studies of radio galaxies and high z clusters
Omar Almaini • Major X-ray surveys: - resolving the X-ray background, new hard X-ray populations, AGN to z = 8, X-ray/sub-mm link
Marek Kukula• HST/Gemini/VLT studies of the hosts of quasars, z = 0 - 5• VLA/Merlin studies probing the origin of radio loudness
Will Percival • Analytical theory - evolution of compact activity in a cosmological context• The black-hole galaxy-formation link
Philip Best High z Galaxy Evolution
Omar Almaini Deep X-ray Surveys
Marek Kukula Quasar Host Galaxies
Will Percival Modelling Evolution
High Redshift Galaxy Evolution
Observational and theoretical study of the evolution of massive galaxies.
Main themes:
• Dust enshrouded starbursts at high redshift– SCUBA surveys & follow-up
– HDF, 8mJy, cluster surveys
• Galaxy evolution in clusters
• Deep spectroscopic studies of HzRG’s
• Age dating of stellar populations
My previous workRadio, optical, IR & spectroscopic studies of HzRG’s
The SCUBA 850-m HDF map
Deepest SCUBA map
50 hours integration
100 arcsec radius
Beam: 14.5’’ FWHM
Noise: rms 0.45 mJy
5 strong sources
HDF 850.1
IRAM 1.3-mm & VLA data needed to provide an accurate position.
No consistent optical id.
Downes et al. astro-ph/9907139
100SFR visible
SFRhidden
cf. such ULIRGswith optical SFgals (ratio ~ 5)
Background structure: “normal” star-forming galaxies
Subtract 5 brightest point sources (Peacock et al. 2000)
Residual structure correlates with optical-UV selected star-forming galaxies
8 mJy survey
Collaboration with Imperial College,
Cambridge and UCL
• Shallow wide-field survey to complement HDF
• 400 sq. arcmins to S850m= 8mJy (3-)
• 8 SCUBA shifts allocated; 24 more long-term
• z and T constraints from deep 175m ISO data
• New PhD student (Suzie Scott) working on data reduction & source extraction
Multi-wavelength follow-up
• Deep radio imaging
(VLA time already awarded):
– identify sources with z < 2.5
– z estimate from radio vs
sub-mm spectral index
– isolates extreme z objects
Essential for reliable identifications & redshifts of SCUBA sources. Will take several years.
from Carilli & Yun, 2000
• mm interferometry, IRAM PdB– time awarded (collaboration, Dieter Lutz)– reliable positions for radio empty fields– brightest SCUBA source in Lockman hole region has
been detected - but no optical/IR id
• Deep optical - IR imaging– UKIRT time allocated– some sources will need Gemini
• Spectroscopy– obtaining redshifts clearly requires 8m class
telescopes
High redshift cluster studies
Why carry out deep radio / sub-mm studies of
high redshift clusters?
• SCUBA observes different population of star-forming
objects than those from optical studies
• Clusters at high z:– are young, possibly still forming– have high galaxy merger rates– are ideal testbeds of galaxy evolution
• Good complement to field surveys / low-z clusters
2 projects:
• Deep SCUBA and VLA studies of z~1 clusters– 8 shifts start-up SCUBA time allocated– 30 hrs VLA data on MS1054 taken in April– Initially targeting clusters with much optical-IR data
• Imaging around z>3 radio galaxies– known regions of high overdensity (protoclusters?)– positive results from pilot study (4C41.17)– long-term status awarded for an extended study
Both projects will require considerable follow-up.
CL1604+43 (z=0.9), 850m
Preliminary results
(March 2000 data)
1 shift
(2 more to come)
- 3 clear detections
- 2-3 marginal
- much richer than
blank field pointings
MS1054-03 (z=0.8), 5GHz
30 hrs, 5 GHz, C-array
(taken April 2000)
- rms 5.7Jy
- numerous detections
- overlay with deep HST
mosaic: most detections
have secure id’s
- Keck MOS data: many
id’s at redshift of cluster.
Galaxy evolution in clusters
In addition to studies of cluster star formation, aim to push back cluster studies to earlier epochs• very deep optical / IR imaging around z>1.5 RGs
– cross-correlation statistics
– colour-magnitude diagrams
– photometric redshifts
• follow-up multi-object spectroscopy (Gemini)– evolution of cluster environments
– age-dating of evolved elliptical galaxies (Jimenez)
Just one massive cluster at this redshift has severe consequences for LSS and cosmological models.
Conclusions
Studies of SCUBA sources are rapidly advancing
and provide key information about SF history of
the Universe. Much follow-up work is required.
Long-term goal is to couple this work with that on• Galaxy evolution in clusters
• Deep spectroscopic studies of HzRGs
• Age dating of stellar populations
to obtain a consistent view of the evolution of
“activity” in the Universe
Philip Best High z Galaxy Evolution
Omar Almaini Deep X-ray Surveys
Marek Kukula Quasar Host Galaxies
Will Percival Modelling Evolution
Quasar Host Galaxies PDRA: Marek Kukula PI: James Dunlop
Ground-based & HST observationsof carefully constructed quasar samples
Line-free imaging and off-nuclearspectroscopy of host galaxies
Comprehensive study of local (z=0.2)quasar hosts now complete
Recently extended out to z=2 with NICMOS
Next phase: follow host galaxyevolution to z>4 with HST, VLT& Gemini
Why study quasar hosts?
HST studies of local (z < 0.3) quasars show that their hoststend to be dominated by a massive spheroidal component.
At z = 2.5 a significant fraction of all massive black holes were active.
Very likely all large elliptical galaxies contain massive black holesand are potential quasar hosts.
Quasar evolution and the starformation history of the universeshare similar properties growth & fuelling of blackholes is closely linked to the evolution of large-scale structure.
Low-redshift quasar hosts
R-band imaging with HST/WFPC20.1 < z < 0.25
Awarded 34 orbits in Cycle 6 (completed 1999)
Image Model
Galaxy Residual
2-D modelling
Surface brightnessprofile
Carefully matched samples: Radio-Quiet Quasars,Radio-Loud Quasars & Radio GalaxiesR-band filter avoids contamination by quasaremission lines
Analysis of HST images
The hosts of all but the least luminous RQQs are massive elliptical galaxies
2-D modelling of HST data:
Black Hole MassesFor local inactive galaxies: (Magorrian et al. 1998)M (bh) = 0.006 M (bulge)
Can now do the same for our quasar samples:
Black hole mass
RLQ
RQQ
M (bh) ~ 10 - 109 10 M0
Can estimate Eddington luminosities:quasars are radiating at ~10% Eddington
100%
10%1%
Bulge luminosity
Off-nuclear spectroscopyOptical spectroscopy with the WHT
Spectrophotometric modelling
Galaxy spectrum
Hosts dominated by an old (~12 Gyr) stellar population.Little on-going starformation (< 0.5 % by mass).
Main result : at z = 0.2 all luminous quasars are in massive elllipticalgalaxies - regardless of radio luminosity of the quasar
Use image to selectoptimum slit position5 arcsec off-nucleus
Out to z=2 with NICMOS Define 3 new quasar samples at z = 0.4, 1 & 2
Choose quasars of the same intrinsic luminosity at each z
60 orbits with WFPC2 & NICMOS in Cycle 7 (to complete Nov. 2000)
Redshift/filter combinationalways samples the sameregion of the restframe spectrum
Results from NICMOSA first look at host galaxy evolution out to z=2
2-D modelling
z=0.2 : massiveelliptical galaxies
z=1 : large, luminous elliptical galaxiesz=2 : no large, luminous galaxies present
large galaxies are still assembling?
smaller galaxies, quasar fuellingmore efficient?
same as hosts at z=0.2
hosts fully-assembled by z=1
Image Surface brightnessprofile
Next phase: 2000 - 2004
Work to date
HST Cycle 9(commencing 2000)
VLT near-infrared imaging(commencing 2000)
Follow host galaxy evolution out to z > 4
Same highly successful strategy:
carefully controlled samples
line-free imaging
Initial observations underway:
Starting point for major study withnew-generation instruments
New observationsNew instruments will make detailed studies of high-z quasar hosts possible
Gemini : NIR imaging(proposal submitted)
HST Advanced Camera for Surveys :multi-colour optical imaging
Ground-based 8-m spectroscopy
Edinburgh team extremely well-placed to exploit these new capabilities :
Philip Best High z Galaxy Evolution
Omar Almaini Deep X-ray Surveys
Marek Kukula Quasar Host Galaxies
Will Percival Modelling Evolution
Deep X-ray SurveysDeep X-ray Surveys
XMM XMM
Omar AlmainiAndy Lawrence, Jim Dunlop
Progress 1998-2000Progress 1998-2000
• ROSAT/ASCA Surveys ROSAT/ASCA Surveys
• X-ray/sub-mm linkX-ray/sub-mm link
• QSO X-ray VariabilityQSO X-ray Variability
• Studies of dwarf AGNStudies of dwarf AGN
Boyle et al 1998
Georgantopoulos et al 1998
Fabian et al 1998
Almaini et al 1998
Blair et al 1999
Almaini, Gunn & Shanks 2000
Almaini, Lawrence & Boyle 1999Almaini et al. 2000
• ROSAT/ASCA Surveys ROSAT/ASCA Surveys • Studies of dwarf AGNStudies of dwarf AGN• X-ray/sub-mm linkX-ray/sub-mm link• X-rays from starburstsX-rays from starbursts• X-rays from starburstsX-rays from starbursts• QSO X-ray VariabilityQSO X-ray Variability
Manners et al. (in preparation)
Natarajan & Almaini 2000
Lira et al. (1999)Iwasawa et al. (2000)
The ELAIS/SCUBA X-ray The ELAIS/SCUBA X-ray SurveySurvey
• UK 8mJy SCUBA surveyUK 8mJy SCUBA survey
• ELAIS 7.5, 15, 90, 175µmELAIS 7.5, 15, 90, 175µm
• VLA radio (0.1mJy)VLA radio (0.1mJy)
ChandraChandra (150ks (150ks))XMMXMM (150ks) (150ks)
• Imaging to R=26, K=22Imaging to R=26, K=22
PI: AlmainiPI: Almaini
The Puzzle Of The X-ray Background
Deep ROSAT SurveysDeep ROSAT Surveys
12 day exposure!12 day exposure!
Broad-line Broad-line QSOsQSOs
‘‘NELGs’NELGs’
Emission-line galaxies?Emission-line galaxies?
Almaini et al. (1996)Almaini et al. (1996)
July 23, July 23, 19991999
The ELAIS/SCUBA X-ray The ELAIS/SCUBA X-ray SurveySurvey
• UK 8mJy SCUBA surveyUK 8mJy SCUBA survey
• ELAIS 7.5, 15, 90, 175µmELAIS 7.5, 15, 90, 175µm
• VLA radio (0.1mJy)VLA radio (0.1mJy)
ChandraChandra (150ks (150ks))XMMXMM (150ks) (150ks)
• Imaging to R=26, K=22Imaging to R=26, K=22
PI: AlmainiPI: Almaini
Chandra Soft X-ray Source CountsChandra Soft X-ray Source Counts
Chandra Hard X-ray Source CountsChandra Hard X-ray Source Counts
XMM
The XMM Mirror Assembly The XMM Mirror Assembly
Scientific ObjectivesScientific Objectives
•Resolve X-ray backgroundResolve X-ray background•Study new, hard X-ray populationsStudy new, hard X-ray populations•Detect very high redshift AGN (z~8)Detect very high redshift AGN (z~8)
AGN/galaxy connection AGN/galaxy connection
Variability of high z QSOs Variability of high z QSOs
Multi-wavelength studies Multi-wavelength studies
Detailed AstrophysicsDetailed Astrophysics
•Measure AGN fraction in submm surveysMeasure AGN fraction in submm surveysRedshift
The X-ray Survey The X-ray Survey
•Analysis of X-ray dataAnalysis of X-ray data
• Source IdentificationSource Identification
• AstrophysicsAstrophysics- reveal ‘new’ hard X-ray populations - reveal ‘new’ hard X-ray populations
- QSO X-ray at high z - QSO X-ray at high z
- multi-wavelength studies - multi-wavelength studies
- source detection, X-ray spectra, variability
- deep imaging (R=26, K=22)- spectroscopy (Gemini, Keck, CGS4)- iron lines? (XMM)
- evolution of high z AGN (z>3) - evolution of high z AGN (z>3)
- AGN fraction in sub-mm surveys- AGN fraction in sub-mm surveys
ChandraChandraXMMXMMSCUBASCUBA
UFTI K=22UFTI K=22
Scientific ObjectivesScientific Objectives
• Resolve X-ray backgroundResolve X-ray background• Study new, hard X-ray populationsStudy new, hard X-ray populations• Detect very high redshift AGN (z~8)Detect very high redshift AGN (z~8)
Astrophysics of source populationsAstrophysics of source populations
• Determine AGN fraction in sub-mm surveysDetermine AGN fraction in sub-mm surveys
X-ray spectra X-ray spectra X-ray variability of high z QSOs X-ray variability of high z QSOs
Multi-wavelength studies Multi-wavelength studies
AGN/galaxy connection AGN/galaxy connection
Philip Best High z Galaxy Evolution
Omar Almaini Deep X-ray Surveys
Marek Kukula Quasar Host Galaxies
Will Percival Modelling Evolution
Modelling cosmologicalAGN evolution
PDRA: Will Percival
Investigators: J.A.Peacock, J.S. Dunlop,
A.Lawrence & A.F. Heavens
The problem: Understanding AGN evolution
The ROSAT soft X-ray quasar luminosity function of Miyaji et al. 2000
A compilation of the measured co-moving number density of luminous quasars selected in X-ray, optical and radio wavebands
The link with the star formation rate
Qualitative evolution of SFR and luminous AGN emission similar
However, 0<z<2 factor ~10 decrease for SFR, compared to factor ~100 for number density of luminous QSOs
Both phenomena thought to be linked with the build-up of structure with mergers between galaxies implicated in both
Merger-induced starbursts alone can explain the observed evolution in the SFR
Why do we need analytic models?
The scale of AGN engines lies far below any feasible numerical resolution
Output from numerical simulation has to occur sequentially at fixed times
Analytic models are usually more versatile than numerical techniques
Analytic models often provide more insight into the physics behind modelled phenomena
Percival & Miller 1999 MNRAS 309 823
Used Press-Schechter (PS) theory to predict the distribution of times at which halos form
Percival, Miller & Peacock 2000 MNRAS accepted, astro-ph/0002328
Provided a (Bayesian) framework from which any mass function can be converted to give the distribution of halo formation times
We can now use this model to predict the formation of structure within more general cosmological scenarios including non-Gaussian models
The build-up of halos (in detail)
The mass function and halo creation rate do not uniquely specify the build-up of individual halos
PS theory provides more information: it ascribes a merger tree for every halo
This is important in order to follow the growth of halos as well as their global properties
Mergers vs Slow accretion
Only violent mergers are thought to give rise to starbursts and quasar activation
Red circle - merger
Blue circle - slow accretion
PS theory predicts that the relative frequency of these events is independent of time
Future directions of analytic work
Analysis of the detailed way in which halos are predicted to form within PS theory
new algorithm for predicting halo merger trees
determine relative importance of mergers vs slow accretion
Importance of PS parameters: particularly filter
Comparison with numerical simulations
Use previous results to link non-Gaussian contributions to the density field with the epoch of structure formation
The tie-in with AGN models
Can activation caused by galaxy mergers explain observed AGN number density evolution?
If the lifetime is short (~108 Gyr), we need extra evolution to explain the factor ~100 decrease 1>z>0 (dashed line)
However, if the lifetime over which quasars are active is longer (~109 Gyr), then a decreasing birth rate and the time-redshift relation provide the correct evolution (solid line)
The tie-in with host galaxy studies
Correlations between host galaxy and quasar emission set important constraints on AGN models
Relations between black hole mass and spheroidal luminosity suggest we should see a correlation between host and nuclear luminosity
However, recent studies find that the hosts of all quasars have similar luminosities (Percival et al 2000)
Kauffmann & Haehnelt 2000 predict a nuclear/host limit using relations between black hole and spheroid mass. The new data suggest a different explanation is required for luminous AGN emission
Summary Over the next four years, studies of AGN based in
Edinburgh will provide important clues for understanding the evolution of AGN
Our current understanding of the build-up of structure is insufficient to fully exploit the results of these observational studies
The aims of this line of the grant are therefore:
1. To provide the required theoretical background in structure formation leading to galaxy and AGN formation
2. To combine this theoretical work with the results of observational studies to produce and constrain plausible models of AGN
Structure formation overview
Aims:• Understanding the sequence of structure formation
• Connecting ab initio theories to observations
V
0)(3 VH
Major programmes: observation
• 2dFGRS (Peacock, Sutherland)
• SDSS (Meiksin)
• Planck (Heavens)
- Plus high-z galaxy work
The 2dF Galaxy Redshift Survey
May 2000: 100,000 redshifts to B=19.45 (target 250k by 2002)
First precision data on spatial distribution of different classes of galaxy - analysis is manpower limited
Major programmes: theory• Galaxy stellar content
(Jimenez, Brand, Dunlop, Heavens)
• LSS statistics
(Heavens, Taylor)
• N-body studies
(Peacock, Meiksin)
• Numerical galaxy formation
(van Kampen, Jimenez, Peacock)
• Warm inflation
(Berera, Taylor)
V
0)(3 VH
KL
Galaxy stellar population models
Jimenez dust models (astro-ph/9910279):
All star formation is ‘hidden’: ‘visible’ fraction depends on lifetime of high-mass stars and dust burnoff time. Predicts 6:1 for Salpeter IMF - matches SCUBA / HDF
Jimenez stellar models:
•Improved stellar evolution
•New Cray atmospheres
•Star formation / Chemical evolution
Major programmes: theory• Galaxy stellar content
(Jimenez, Brand, Dunlop, Heavens)
• LSS statistics
(Heavens, Taylor)
• N-body studies
(Peacock, Meiksin)
• Numerical galaxy formation
(van Kampen, Jimenez, Peacock)
• Warm inflation
(Berera, Taylor)
V
0)(3 VH
KL
Haloes, occupation numbers, and bias
High-mass haloes
Galaxies from empirical occupation numbers
Realisticpowerspectrum
2563 VIRGO simulation
Major programmes: theory• Galaxy stellar content
(Jimenez, Brand, Dunlop, Heavens)
• LSS statistics
(Heavens, Taylor)
• N-body studies
(Peacock, Meiksin)
• Numerical galaxy formation
(van Kampen, Jimenez, Peacock)
• Warm inflation
(Berera, Taylor)
V
0)(3 VH
KL
Summary of PDRA bids• LSS statistics
(Taylor replacement; P.I. Heavens)
• IGM simulations
(New position; P.I. Meiksin)
• Semi-numerical galaxy formation
(van Kampen; P.I. Peacock)
• Warm inflation
(New position: P.I. Berera)
V
0)(3 VH
KL
Statistical Methods for Cosmology
Previous PDRA: Andy Taylor (now PPARC AF - gravitational lensing)
Post funded for 2 years
Request: 4 year funding
PSCz (Branchini)
Goals
Scientific goals: cosmological parameter estimation, understanding galaxy formation, star formation history…
Rationale: complement large observational investment
To develop and apply new theoretical tools for analysis of cosmological data sets
2dfPlanck
Past workGalaxy Redshift Surveys: First power spectrum analysis in spherical coordinates (including mask, selection function, redshift distortions) Heavens & Taylor 1995
‘Heavens-Taylor pixelization’ (Padmanabhan et al. 2000;
CfA2/SSRS) now standard analysis method (also planned for 2dF, Sloan)
Data Compression
Datasets are large, noisy and correlated. Data compression is necessary for analysis.
Why? Can’t compare theory with 106 galaxy positions
e.g. correlation function, power spectrum
Aim: To perform data compression whilst preserving as much information as possible about what we want to know Tegmark, Taylor & Heavens 1997
PSCz survey
PSCz: Spherical Harmonic analysis (4600 modes) + optimised data compression ( 2300 modes), with 1% loss of information Hierarchical data compression, parameter eigenvector methods (Ballinger, Taylor, Heavens & Tadros 2000)
Without data compression With data compression
Tadros et al 1999 Taylor et
al. 2000
Power spectrum = 0.4 0.1
Galaxy Spectra
Physical parameters (e.g. age, metallicity, star formation history….)
Find b1 which captures most information about age.
Find b2 (orthogonal to b1) which captures most information about stellar mass… etc. Solve generalised eigenvalue problem; Gram-Schmidt orthogonalisation in 1000-dimensional (curved!) space.
Data x
y=b.x
(Heavens, Jimenez, Lahav 2000)
MASSIVE (99%), LOSSLESS data compression.
• Two numbers y1 and y2 tell you as much about age and number of stars as the entire spectrum
• Spectral classification based on physical parameters
From 352 pixels From 2 numbers
Very large data compression possible:
Likelihood of age, number of stars:
Theory Developments (with applications):-
Future Programme
• Optimal mode construction for non-gaussian likelihood functions
Applications (with some theory development):-
• CMB power spectrum estimation
• non-gaussian signatures to estimate foreground contamination
• physical parameters from galaxy spectra
New: CMB parameter estimation
Power Spectrum
Multipole
Data compression reduces 2000 correlated numbers to ~17 uncorrelated numbers.
CMB data compression: Clcosmological parameters (0, , b…)
Unsolved problem: Full parameter estimation is not practical (max. likelihood in ~17 dimensions)
Can speed up parameter estimation by up to 108 (almost losslessly)
Theory Developments (with applications):-
• Optimal mode construction for non-gaussian likelihood functions
Applications (with some theory development):-
• CMB power spectrum estimation
• non-gaussian signatures to estimate foreground contamination
• physical parameters from galaxy spectra
• Cl parameters
SimulatingGalaxy Formation
and Evolution
PPARC rolling grant review, May 2000
Eelco van Kampen
Semi-numerical models of galaxy formation
Cosmological model Halo formation and
merger history Gas dynamics and
radiative cooling Star formation and
feedback Stellar population
synthesis
Ingredients:
sCDM model of van Kampen, Jimenez & Peacock (1999)
Research goals 2000-2004
Understanding all ingredients for a model of galaxy formation and evolution
Assessing the robustness and uniqueness of such a model
Applying the model to solve specific problems:
– galaxy occupation number
– the abundance of dwarf satellites
– structures of local galaxies
– interpreting high-redshift galaxy data
The modelling so far Differences with previous, semi-analytical models:
– Inclusion of a bursting star formation mode
– Chemical evolution in stellar populations and gas
– Halo merger history from a special N-body technique to treat halo substructure
Retaining substructure in semi-numerical models (using N-body simulations)
Erasure of all substructure in semi-analytical models
van Kampen (2000)
Results of the existing code
Simultaneous match of the luminosity function and the Tully-Fisher relation, with a realistic mass-to-light ratio
van Kampen, Jimenez & Peacock (1999)
Halo substructureThe abundance of subhaloes in N-body simulations
A problem for N-body simulation codes or for cosmology ?
Issues:
• numerical limitations
• nature of dark matter
• galaxies vs. clusters
• mass-to-light ratios
Virgo Consortium simulation
UndermergingDynamical friction is not properly modelled in N-body simulations
- possibly allowing too many subhaloes to survive
van Kampen (2000)
Exploiting the existing code
Extend van Kampen, Jimenez & Peacock (1999) to aCDM Universe and a WDM Universe
Interpreting data from the 2dF survey: surface brightness function and limit, angular and redshift space correlation functions
Statistics of the galaxy ‘occupation number’, the number of galaxies within a dark matter halo
Structures of local galaxies
Needed: modelling disks and bulges galaxy cluster physics: ram-pressure stripping
and tidal processes transforms galaxies
Specific goals: morphological fractions surface brightness function and limits morphology-density relation
Prediction of morphology and surface brightness
Modelling disks A new way of modelling galactic disks and disk
star formation, using the Schmidt law and a form of the Kennicutt surface-density threshold
Rimes & van Kampen (in preparation)
High-redshift galaxies
Needed: dust model (Jimenez et al. 1999) higher numerical resolution
Specific goals: sub-mm maps galaxy clustering at high redshift high redshift starburst activity
Constraints on galaxy formation models and uniqueness tests for models that work for local galaxies.
The SCUBA HDF map
50 hours integration
100 arcsec radius
Beam: 14.5’’ FWHM
Noise: 8’’ FWHM
Issues :
• optical counterparts
• starburst emission
• clustering properties
Hughes et al. (1998) 5 brightest point sources subtracted
Emission at extreme zNICMOS GTO data found eight z > 5 candidates (with 4-473.0 at z=5.6):
2 close pairs match well with 1-mJy level peaks:
Starburst activity triggered by interaction?
Combine numerical SFR with Jimenez dust models
Simulating galaxy formation and evolution:
research goals 2000-2004 Understanding all model
ingredients
Assessing the robustness and uniqueness of the model
Applications:
– galaxy occupation number
– dwarf satellite abundance
– structures of local galaxies
– high-redshift galaxies
Hydrodynamical simulations of the intergalactic medium
Avery Meiksin (bid for new position)
Purpose: to simulate the formation and evolution of the intergalactic medium
Cold Dark Matter models
(sCDM, CDM, OCDM, CDM, CHDM)
Key questions:• What is the origin of structure in the IGM?• What is the physical nature of the Lyman-alpha forest?• What is the metal content of the IGM, and how has it evolved?
PM (gravity) + Eulerian finite difference (hydro)
In collaboration with M. Norman (NCSA)
The cosmic web
in the
intergalactic
medium
Projects
(1) Tests of cosmological models
(2) Multiple line-of-sight statistics
(3) Metal ions in the Lyman-alpha forest
SYNTHETIC SPECTRUM
wavelet transform
flux distribution
Wavelet
coefficients
Comparisonbetween Keckspectrum and6 cosmologicalmodels
Absorptionline parameterdistributions:
NHI, b
(1) Tests of cosmological models
Goal: Testing cosmologies by comparing real and synthetic quasar spectra.
(2) Multiple line-of-sight statistics
Goal: Shape and amplitude of P(k)
HI column density correlates with gas morphology
Expect different line-of-sight statistics for different morphological structures, corresponding to different HI column densities
1016 cm-2 < NHI : spheroidal (minihaloes) (3D)
1014.5 cm-2 < NHI < 1016 cm-2 : filamentary
(cosmic web) (1D)
1013.5 cm-2 < NHI < 1014.5 cm-2 : sheet-like (2D)
NHI < 1013.5 cm-2 : fluctuations in minivoids
Column density correlateswith morphology
(3) Metal ion predictionsGoals: B
Sources of photoionization Evolution of IGM metallicity (star formation) Tests of cosmological models [, , P(k)]
HI fixes: NHI = nHIL = RnB2L / HI or B
2 h3/2 / HI
HeII fixes: HeII / HI
Metals (e.g. CII:CIV, SiIV:CIV) fix: n / nB or HI / B
Hence separate constraints on B, HI, HeI
X-ray absorption lines (e.g. OVIII:Ly) to be included by incorporating time-dependent metal ionization in simulations
Observational tests of inflation
A. Berera, A. Taylor, J. Peacock, A. Heavens
Warm Inflation
The puzzle of cosmological initial conditions:
T/T < 10-5 in CMB without causal contact
The inflation solution (1981 + ):
CausallyDisconnected
COBE
R(t)
t
Accelerated expansion
implies + 3p < 0
How to get this from high-energy physics?
Acceleratedexpansion
Inflation
standard big bang
Scalar field (‘inflaton’) dynamics
22.2 2/)()(2/ RV
22.2 6/)()(2/ RVp
V
0)(3 VH Supercooled inflation: Just choose V()
Potential energy dominated (‘slow roll’):
H3
But what about particle creation? 0)(3 VH
Warm inflation: dominates
Slow-roll now means thermal overdamping: ,3H
The warm inflation differenceWarm inflationSupercooled inflation
V()
t t
v
r
r
v
Inflation Reheating
V()
Developing Warm Inflation
Observations Theory
– Thermal perturbations, amplitude & slope
– Tensor modes– Super-Hubble
suppression– Isothermal perturbations– Primary & secondary
acoustic peaks.– Non-Gaussian signatures.
– Dissipative QFT at low temp, and out of equilibrium.
– Particle physics models.– Implications for magnetic
fields / baryogensis.– Robustness of solutions.
MAP, Planck polarization will supply vast data in coming years.
General physics developed from this study:- first principles Landau-Ginzburg dynamics.- New tests of CMBR.
Supercooled inflation: inflaton field is isolated
- But interactions are more plausible: Warm Inflation
Implies we need to calculate:
Relevant quantum mechanical processes (dissipation)Already studied in Condensed Matter Physics:Caldeira-Leggett model, Fermi-Ulam-Pasta model.
In Quantum Field Theory (QFT) generic couplingsof fields yield dissipation.
In restricted cases, QFT wam inflation solutions have been obtained - confirms that warm inflation works!
Considerable exploration remains.
Signatures of Warm Inflation
(Taylor & Berera, 2000, Phys Rev D)
- Standard inflation has no interactions - so universe is supercooled.
-Warm inflation includes interactions.
- Warm inflation predicts different tensor/scalar ratio.- No Consistency Relation in warm inflation.- Mechanism for isocurvature modes - may be detectable by Planck.
- Predicted amplitude of perturbations for warm and supercooled inflation.
Detection Limits for Super-Hubble SuppressionA. Berera & A.F. Heavens Submitted PRD, 2000
Inflation/Defect models Largest (Causal) Fluctuation Scale. Potentially useful constraint.
Detectable in CMB, even if larger than visible horizon
COBE data prefers small LCFS (Berera, Fang, Hinshaw, 1996, PRD)
MAP/Planck will improve detection (through better foreground subtraction/parameter determination)
Detectability for sub-visible Horizon LCFS
Future Work: Basic Theory
Derive Linearized General Relativistic Perturbation Equationsfor Warm Inflation Conditions:
- Effects of homogeneous radiation component
- change in background evolution- themally induced density fluctuations
- Isocurvature fluctuations
- suppression scale- comprehensive identification of mechanisms
- General evolution of adiabatic and isocurvature fluctuations
- feedback effects of entropic pressure.
The Goal: Tests to Distinguish Between Warm and Supercooled Inflation
Cosmic Microwave Background:
- Generalise CMBFast for Warm Inflation:- remove conditions specific to supercooled inflation (T/S, account for dissipation term, etc).- account for super-Hubble suppression scale.
- Include isocurvature modes.
- NonGaussian signatures.
- Simulate MAP & Planck maps.
Optimal tests for temperature and polarization data:
- Primary: tensor-scalar ratio,
- Secondary: include isocurvature.