Download The Deep Structure of Dark Matter

The role of large-scale
structure on galaxy
properties
Joss Bland-Hawthorn
University of Sydney
Galaxy studies are an environmental science:
but are there observed environmental dependencies?
They struggle
to find a
strong
environmental
dependence
beyond
cluster vs.
field.
Why ?
This may reflect (i) difficulty of defining environment; (ii) influence is
washed out – evolution, projection, complexity; (iii) inadequacy of
existing data;
What is
environment?
Muldrew+ 2012
Statistical
environment –
a measure of "crowding"
Physical environment – I
How do we define physical structures?
Ideally these would be defined in terms of
EUV/x-ray emissivity, CMB SZ or weak
lensing signal.
Dietrich+ 12
But while useful for dense groups & cluster mass scales, these are much
less sensitive to large-scale structure at lower densities.
For the foreseeable future, we are limited to galaxy redshift surveys.
Physical environment – II
"A collection of connected points having
the same environmental attributes."
1. Double pass friends of friends (Murphy+ 2011)
2. Multiscale mapping (Barrow+ 1985; Aragon-Calvo+ 2007; Smith+
2012)
3. Geometric classifiers (Lemson & Kauffman 1999; Sousbie+ 2008)
4. Dynamic classifiers (Hahn+ 2007; Hoffman+ 2012)
Dynamic classifiers – Gravitational tidal tensor,
Velocity shear tensor – are the most physical
but have not been demonstrated on data yet.
V
G
Projection effects
in a multi-component galaxy
Cappellari 2016
Effects of dust ?
I can't find any discussion
on this point in measuring,
say, kinematic parameters.
Integral field spectroscopy is giving us a new
angle on environmental effects.
But we need “cosmological” samples across
large-scale structure at high density, cf. Stripe 82.
STRIPE 82:
16000 galaxies to rp ~ 17.7 (3o thick)
The technological evolution continues… Near field – ATLAS3D, CALIFA,
SAMI, MaNGA, MUSE, Hector…
By 2025, we may have 100,000+ galaxies with spatially resolved
optical and HI kinematics. We need virtual IFS observations for
~105 galaxies from ~10 x 1003 Mpc3 simulations that reach to
z~0.
improved
sampling
where Φ(r)
varies rapidly
SAMI survey @ AAT
(2017)
2016
SAMI has so far obtained masses, low & high order
kinematics, specific angular momenta on ~1200
galaxies, ~2000 by mid 2017, ~3600 by end 2018.
Hector: “cosmologically motivated IFS survey” across
large-scale structure (all galaxies, M ≥ 109 M)
SAMI: 3600 gals
in 0.6 x 1003 Mpc3
(1dF: 2015-18)
Hector-1: 12000 gals
in 2 x 1003 Mpc3
(2dF: 2018-23)
Hector-2: 60000 gals
in 6 x 1003 Mpc3
(3dF: unfunded)
our first “true” hexabundle (88% fill)
N ~ 60,000 galaxies to
detect spin alignment with
LSS at z=0
Dark matter only: see also
Bailin & Steinmetz; Hahn;
1003 Mpc3 includes gas, AGN etc. (RAMSES: Teyssier et al)
Critical mass where it switches over
decreases with redshift (~1012 M today)
Most of the action at high z but signature
frozen in down to z ~ 0.
Codis+12,15; Dubois+14; Laigle+15; Chisari+16
LSS connection goes back to: Katz+03;
Birnboim & Dekel 03; Keres+05; Ocvirk+08
ω=
Δ
Vorticit
y
xv
ω ~ 100 km s-1 Mpc-1
Codis+12: helical motion down filament in
co-moving frame generates spin. Local
| to filament.
vorticity sets up in plane __
Galactic accretion with vorticity (Codis+12, 15;
Laigle+15)
Spinning up haloes
Spin-aligned
galaxies
Early onset of vorticity due to shear
flows
This is not the same as TTT which
was long thought to dominate spin.
Vorticity may dominate over TTT
in the final analysis (Libeskind+13).
New work from Sadrine Codis
A
(see also Codis+15)
Signatures at z~1, want to extend to z~0.
A: galaxy spin aligns with tidal tensor (e1 points
down filament) for low mass galaxies, opposite for
high mass.
B: blue galaxies align, red galaxies not so much.
C: tensor contribution mostly < 3 Mpc but
detectable to 10 Mpc.
Same volume as
SAMI but 20x more
galaxies;
some cosmic
variance.
If true, some galaxy
properties are
affected by largest
scales.
B
C
Australia’s major investment:
important element of the Hector survey
Gas supply – missing ingredient in all surveys:
Deep 21cm (≤1019 cm-2) maps of nearby
galaxies & groups only exist for small
samples.
Deepest to date: M31-M33
map
reaches ~1017 cm-2 (Wolfe+16).
ASKAP 36 dishes
Wallaby, Dingo surveys
Milky Way “analogue” – M83
Koribalski 2016
Huge HI disks appear to be normal for
Galaxy, M31, M33, LMC, SMC...
Summary
A case is proposed for physical environment over statistical environment.
We must distinguish between filaments in voids ( .v > 0) and filaments in
dense regions ( .v < 0)…
We need to reach down to void galaxies while retaining enough filaments,
groups and clusters for intercomparisons. A full treatment takes us to a
Hector survey of ~105 galaxies ultimately down to mass limit ≥ 109 M .
2-4m class telescopes, supported by all-sky HI and photometric surveys,
are
needed into the next decade to tackle these issues.
Simulations must extract “Hector IFS observations” of ~105 galaxies and
measure key parameters (e.g. slow/fast fraction, high order kinematics).
Dubois+ 14