Lisa Kewley Australian National University Thank you to the LOC and SOC Jeff Rich ITing Ho Rebecca Davies Anne Medling Credit goes to Elise Hampton David Nicholls Results in this talk are from ID: 785800
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Slide1
Physical Conditions in the ISM
Lisa Kewley
Australian National University
Slide2Thank you to the LOC and SOC
Jeff Rich
I-Ting Ho
Rebecca Davies
Anne
Medling
Credit
goes to
Elise Hampton
David Nicholls
Slide3Results in this talk are from:
SAMI: Australian Astronomical Observatory
2016: 3000 galaxies 2025: 100,000 galaxies (HECTOR)
S7: Australian 2.3m
WiFeS
~140 AGN
WIGS: Australian 2.3m
WiFeS
~40 U/LIRGS
Slide4ISM Spectral
Diagnostics
[OII]
Slide5ISM Spectral
diagnostics
Metallicity
(amount of metals)
[OII]
Slide6Metallicity
Star Formation Rate
[OII]
ISM Spectral
Diagnostics
Slide7ISM Spectral
Diagnostics
Metallicity
Star Formation Rate
Electron Density
[OII]
Slide8ISM Spectral
Diagnostics
Metallicity
Star Formation Rate
Electron Density
Ionizing Source
[OII]
Slide9ISM Spectral
Diagnostics
Metallicity
Star Formation Rate
Electron Density
Ionizing Source
Ionization Parameter
[OII]
Slide10ISM Spectral
Diagnostics
Metallicity
Star Formation Rate
Electron Density
Ionizing Source
Ionization Parameter
Shock properties
[OII]
Slide11What can we learn from the ISM
?
Star formation
AGN
Gas inflow
Slide12What can we learn from the ISM?
Star formation
Outflows
AGN
Gas inflow
Slide13What can we learn from the ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
Slide14What can we learn from the
ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
Slide15What can we learn from the ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
Slide16What can we learn from the ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
When? How much?
Mechanism?
Slide17What can we learn from the ISM
?
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
When? How much?
Mechanism?
?
How common?
How much mass loss?
How common?
How much mass loss?
?
Slide18What can we learn from the ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
When? How much?
What mechanism?
?
How common?
How much mass loss?
How common?
How much mass loss?
?
How do metals
Build up in disks?
?
Slide19What can we learn from the ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
When? How much?
What mechanism?
?
How common?
How much mass loss?
How common?
How much mass loss?
?
How do metals
Build up in disks?
?
?
How much
Metals/mass
lost? Effect on
Host?
Slide20What can we learn from the ISM?
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
?
How common?
How much mass loss?
How common?
How much mass loss?
?
How do metals
Build up in disks?
?
?
Connection?
How much
Metals/mass
lost? Effect on
Host?
Slide21Gas Inflows through IFU data
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
?
?
?
?
Connection?
Slide22Spiral Galaxy
Metallicities
HST view of M101
Image credit: Kunz et al. 2009
Bresolin
(2007)
Slide23Inflows flatten
gas-phase gradients
HST view of M101
Image credit: Kunz et al. 2009
Bresolin
(2007)
Nuclear
metallicity
diluted with pristine gas
Gas flows down spiral arms
Slide24Kewley et al. (2010,
ApJL
, 131, 2004
)
Metallicity
Gradients:
A
Smoking
Gun for
m
ajor gas inflows
Isolated
Dotted, dashed
= mergers
Slide25Gas Inflows flatten gradients in U/LIRGs
Rich et al. 2012,
ApJ
, 753, 5
Using the ANU
WiFeS
IFU
Also: Kewley+06,+10, Rosa+14,
Husemann+14, Ho+15
Isolated
Wide
Pair
Close
Pair
Late
Merger
Slide26Metallicity
gradients in QSOs
Husemann+14
Sanchez+12
Normal spiral gradient
Slide27Side note on
m
etallicity
diagnostic
d
iscrepancies...
Kewley & Ellison (2008)
Slide28Metallicity
Diagnostic Discrepancies...
it is a bit like US politics
Slide29Metallicity
Diagnostic Discrepancies...
it is a bit like US politics
Slide30Metallicity
Diagnostic Discrepancies...
it is a bit like US politics
Slide31Metallicity
Diagnostic Discrepancies...
it is a bit like US politics
Slide32Metallicity
Diagnostic Discrepancies...
it is a bit like US politics
Slide33Metallicity
Diagnostic Discrepancies...
it is a bit like US politics
Slide34Resolution
of discrepancies
Strong Line Methods- atomic data- relative abundances- depletion factors- e
-
temperature distribution
Empirical Methods
e
-
temperature fluctuations / gradients
-
e-
temperature distribution
Nicholls et al.
(
2012,
2013, 2016 in prep)
Slide35ISM conditions
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
?
?
?
?
Connection?
Slide36Optical Diagnostic Diagram
36
log([NII]/H
a
)
log(
[OIII
]/
H
b
)
Slide37Star-forming
A
bundance SequenceMetallicity (Z)Ionization parameter (q)Electron density (n
e
)
Hardness of EUV
radiation field
37
Sensitive to:
Slide38Star-Forming Abundance Sequence
Kewley et al.
2013a,
ApJ
, 774, 110
Slide39AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
39
Shape and position from:
Slide40Photoionization Models
AGN position
& metallicity
40
Low
Metallicity
High
Metallicity
AGN locus
depends
on
metallicity
Kewley et al.
2013a,
ApJ
, 774, 110
Slide41AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
41
Shape and position from:
Metallicity
Slide42AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
42
Shape and position from:
Metallicity
Slide43AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
43
Shape and position from:
Ionization
parameter
Slide44AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
44
Shape and position from:
Ionization
parameter
Slide45AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
45
Shape and position from:
Ionization
parameter
Slide46AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
46
Shape and position from:
EUV
Hardness
Slide47AGN Mixing Sequence
Metallicity
(Z)Ionization parameter (q)Power-law index (a) (EUV hardness)
47
Shape and position from:
EUV
Hardness
Slide48Nuclear spectra of 45,000 galaxies
48
Each data
Point is one
galaxy
Slide49Integral field spectra of one galaxy
Each data
Point is oneSpaxel
(spatial
p
ixel)
Slide50Integral field spectra of one galaxy
Each data
Point is oneSpaxel
(spatial
p
ixel)
Slide51Star formation
vs AGN
Composite
spaxels
form
a clean ring of mixed
Starburst-AGN activity
Davies, Rich, Kewley &
Dopita
(2014,
MNRAS, 439, 3835)
Slide52NLR radius
AGN contribution to each line
Subtraction of AGN (SFR, metallicities)
Subtraction of starburst (AGN luminosity,
E
ddington
rate)
Measurement of AGN NLR properties (
metallicity
, U,
a)
IFU + Photoionization models
Slide53Composite Galaxies
Kewley et al. 2006
Slide54Kewley et al. 2006
Composite Galaxies
Slide55Composites are not Starburst+Sy2
They are mostly
Starburst + shocks Hampton et al. (2016)
Slide56Gas Inflows through IFU data
Star formation
Metals
Outflows
AGN
Gas inflow
?
?
?
?
?
?
Connection?
Slide57Tracing Outflows with Shocks in SAMI
Three velocity
dispersion peaks
Shocks
HII
??
Ho et al. (2014); see also Ho et al. (2016)
Slide58SAMI Shocks: an isolated SF galaxy
log([NII]/H
a
)
HII
??
Shocks
Ho et al. (2014); see also Ho et al. (2016)
Slide59SAMI Shocks: an isolated SF galaxy
log([NII]/H
a)
HII
??
Shocks
Ho et al. (2014); see also Ho et al. (2016)
Slide60SAMI Shocks: an isolated SF galaxy
HII
Shocks
??
Shock Mechanical luminosity = 10
42
ergs/s
Starburst mechanical luminosity = 10
42
– 10
43
ergs/s
Ho et al. (2014); see also Ho et al. (2016)
Slide61Shocks in mergers
Star
Formation
Shocks
Rich, Kewley
&
Dopita
,
(2014,
ApJL
,
781, 12)
These shocks
are from
star formation only
AGN contain <30%
shock contribution
Isolated
Wide
Close
Late
Merger
Slide62Cause of shocks?
“Zoom-in” IFU
ObservationsWide field + narrow high res.e.g.,
Medling
et al.
2015, MNRAS, 448, 2301
Slide63Causes of shocks?
This galaxy:
Disk collision(small scale)+ starburst driven winds (large-scale)Medling
et al.
2015, MNRAS, 448, 2301
Slide64Inflows & Metals:
Metallicity gradient flattening
Dramatic signpost for galactic-scale gas
inflows
Outflows:
Shocks dominant
at late merger stages
Outflows are starburst-driven or caused by gas
collisions.
Starburst-AGN:
clean
mixing sequences
Separation of starburst &
Sy2 contribution
but composites are
starburst+shocks
Summary: Science
Slide65Summary: Techniques
IFU multiplexing: galaxy dissection
Large IFU Surveys with AGN (SAMI, MANGA, S7)Physical Process Diagnostic ToolsFuelling (Inflows) metallicity
gradients, kinematics
Feedback (Outflows) shocks, kinematics
Starburst
vs
AGN line ratio mixing sequences
AGN properties line ratios, AGN models
Slide66Future: Next Generation Telescopes
e.g., GMTIFS
z=2
Separation of SF, shocks
& AGN with
rest-frame
o
ptical diagnostics
z>3
SF, shocks, AGN
Using lensing and UV
diagnostics
Slide67Background:
Metallicity
- Auroral Lines
[OIII]
l
4363, [NII]
l
5755, [SIII]
l
6312, [OII]
l
7325
Advantages:
Strong function of Te
Direct
Disadvantages:
Weak
Saturation
T
e
fluctuations
Slide68Empirical
Metallicity Diagnostics
e.g.,
Pettini
&
Pagel
(2004)
Pilyugin
et al. (2001)
Assumes ISM conditions are
same as local HII regions
Slide69Metallicity
- Strong Lines
[OII]
l
3727, [OIII]
l
5007, [NII]
l
6584, ...
Advantages:
Strong lines
No saturation
Disadvantages:
Model
dependant
(Geometry
, dust parameters,
abundance set,
ionizing radiation
field)
Slide70Kewley & Ellison (2008)
Metallicity
Diagnostic
Discrepancies
SDSS mass-metallicity
relation
Tremonti et al. (2004)
Slide71The current solution to
metallicity
calibration problems
Kewley & Ellison (2008)
Slide72Resolution of discrepancies?
Strong Line
Methods- atomic data- relative abundances- depletion factors- Kappa e-
temperature distribution
Empirical Methods
e
-
temperature fluctuations / gradients
-
Kappa e
-
temperature distribution
Nicholls et al. (2012, 2013)