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Multi-wavelength modelling of galaxy evolution: Lecture 1: Computing galaxy SEDs from the UV to the radio. Cedric Lacey. Outline. Stars Stellar evolution Stellar spectra Integrated spectra of stellar populations Dust Extinction Emission Radio Thermal radio emission

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Multi-wavelength modelling of galaxy evolution:Lecture 1: Computing galaxy SEDs from the UV to the radio

Cedric Lacey

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outline
Outline
  • Stars
    • Stellar evolution
    • Stellar spectra
    • Integrated spectra of stellar populations
  • Dust
    • Extinction
    • Emission
  • Radio
    • Thermal radio emission
    • Radio synchrotron emission

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stars
Stars

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modelling the light from stellar populations
Modelling the light from Stellar Populations
  • Stellar evolution tracks
  • Stellar spectra
  • Stellar initial mass function (IMF)
  • Star formation history (SFH)
  • Chemical enrichment history

Ingredients:

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simple stellar population ssp
Simple Stellar population (SSP)
  • Set of stars all with same age  and initial metallicity Z
  • Stellar evolution models give evolution of stars in mass, L, Teff, g as function of  , Z & initial mass m

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stellar evolution tracks
Stellar Evolution Tracks

Low mass High mass

Girardi et al 2000

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simple stellar population ssp1
Simple Stellar population (SSP)
  • Set of stars all with same age  and metallicity Z
  • Stellar evolution models give evolution of stars in mass, L, Teff, g as function of  , Z & initial mass m
  • Assign spectrum to each star as fn of L, Teff, g & Z
  • Sum spectra from all stars in HR diagram to get spectrum of SSP

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stellar spectra
Stellar Spectra
  • Use library of observed stellar spectra
    • more accurate
    • but only includes stars can observe easily, e.g. lack stars with low Z & high m, also v.high Z stars
  • Use theoretical stellar atmosphere models
    • can cover all Teff, g, Z & /Fe
    • but models do not reproduce all features of observed spectra

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stellar initial mass function imf
Stellar Initial Mass Function (IMF)
  • IMF specifies relative number of stars of different initial masses m
  • (m)dm = no of stars in mass range (m,m+dm)
  • Usually assume power law over some range of mass

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what imf
What IMF?
  • Conventional choice is Salpeter (1955) IMF:

x=1.35 for 0.1<m<100 Mo

  • However, in solar neighbourhood, IMF is much flatter than this for m<1Mo, and probably a bit steeper for m>1Mo
  • Better fit is Kennicutt (1983) (or similar):

x=0.4 for 0.1<m<1 Mo

x=1.5 for 1<m<100 Mo

  • But IMF in other environments might be different!

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spectral energy distribution sed of an ssp
Spectral Energy Distribution (SED) of an SSP

Bruzual & Charlot 1993

  • SEDs shown for different ages in Gyr)
  • Salpeter IMF assumed
  • SED dominated by high-m stars at young ages & low-m stars at old ages

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composite stellar population csp
Composite Stellar Population (CSP)
  • In general, have mixture of ages & metallicities Z:

t,Z) dt dZ = mass of stars formed in time (t,t+dt) with metallicities in range (Z,Z+dZ)

  • In single-zone chemical evolution model, there is one-to-one relation Z(t)
  • But in multi-zone model, or where galaxies form by mergers, there is distribution of Z even at fixed t

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sed of composite population
SED of composite population
  • where

is SED of population with single mass m, age metallicity Z

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example seds of csps for different star formation histories
Example SEDs of CSPs for different star formation histories

const SFR exp decaying SFR

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Bruzual & Charlot 1993

galaxy seds along present day hubble sequence
Galaxy SEDs along present-day Hubble sequence
  • average broad-band UV- near-IR SEDs for galaxies of different Hubble types can be quite well fit with simple SFHs, e.g.
    • Single burst long in past
    • Const SFR
    • Exponentially-decaying SFR

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fit of model to observed galaxy seds
Fit of model to observed galaxy SEDs

Elliptical Irregular

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Bruzual & Charlot 1993

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Fit of model to observed SEDs along Hubble sequence

E - Sc galaxies

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Bruzual & Charlot 1993

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However, this does not prove that real galaxies all had such simple star formation histories!
  • Broad-band SEDs given by integral over wide range of stellar mass & age
    • insensitive to details of SFH
  • Small-scale spectral features (absorption features & spectral breaks) more sensitive to particular types of star
  • Analysis of these features implies more complicated SFHs for many galaxies, e.g. recent bursts

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what about effects of ism
What about effects of ISM?
  • Dust
    • Absorbs & scatters light from stars in UV & optical
    • Absorbed energy re-emitted in IR & sub-mm
  • Gas ionized by stars (in HII regions)
    • Emission lines in UV, optical & IR
    • Thermal bremsstrahlung emission in radio
  • Relativistic electrons accelerated in supernova remnants (SNRs)
    • Emit synchrotron radiation in radio when move in galactic magnetic field

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slide20
Dust

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observational constraints on dust properties
Observational constraints on dust properties
  • Extinction & reflection of starlight
  • Infra-red emission
  • Interstellar abundances & depletions
  • X-ray scattering & absorption
  • Polarization of starlight

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extinction curve of local ism
Extinction curve of local ISM

Analytical representations of measured extinction curves along different lines of sight

Average extinction curve for local diffuse ISM

Fitzpatrick 2004

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ir emission from local diffuse ism
IR emission from local diffuse ISM

Dust heated by local diffuse interstellar radiation field

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element depletions in local ism
Element depletions in local ISM

Gas-phase abundances in local ISM more depleted for higher condensation temperature

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what are dust grains made of
What are dust grains made of?

Main clue is spectral features in absorption or emission

  • Graphite:

- bump in extinction curve at 2175 A

- can be explained as electronic transition in carbon in graphite-like structure

- could either be small graphite grains or large polycyclic aromatic hydrocarbon molecules (PAHs)

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what are dust grains made of 2
What are dust grains made of? (2)
  • PAHs (polyclyclic aromatic hydrocarbon molecules)

- strong emission bands at 3-13 m

- explained as vibrational (stretching & bending) modes of PAH molecules

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what are dust grains made of 3
What are dust grains made of? (3)
  • Silicates:

- strong absorption features at 9.7 & 18 mm

- implies silicates, e.g. Mg2 SiO4

- absence of fine structure => amorphous (glassy)

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Optical extinction curve requires range of grain sizes ~ 0.01-0.1 m

- wavelength dependence constrains size distribution

- suggests power-law similar to

  • Mid-IR emission (~ 3-20 m) requires v.small grains ~ 0.001-0.01 m (10-100 A)

- such grains heated to T much higher than equilibrium value by single photons

  • Overall constraint on grain chemical compositions from element depletions in ISM

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scattering absorption cross section for spherical grain
Scattering & Absorption cross-section for spherical grain
  • Scattering/absn efficiency:
  • Q = a^2)
  • Q ~ const for a
  • Q falls rapidly for a
  • absorption dominates at a

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emission from dust grains
Emission from dust grains
  • Large grains
  • Small grains
  • PAH molecules

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Large Grains (>100 Å), don’t cool in the time between absorption of two photons, so reach thermal equilibrium with the interstellar radiation field.

  • Tis determined by solving the energy balance equation:

Angle averaged In

Absorption

Emission

Note that equilibrium grain T depends weakly on radiation field & on grain size

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Indeed, absorption occurs mainly in optical–UV where Q,a»1, while emission is in IR where Q,a ~ - with ~1.5-2. Thus, as an order of magnitude we get

e.g. to double T would require an increase of U by 60!

The SED of optically thin dust emission is relatively stable.

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2. Small grains(<100 Å) fluctuate in temperature between two photons and a probability distribution P(T)dT to find a grain between T and T+dThas to be computed (e.g. Guhathakurta & Draine 1989, Siebenmorgen et al. 1992).

Once this is done:

replacing

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slide35

Effect of temperature fluctuations

Predicted spectrum

PredictedP(T)

With

fluctuations

Neglecting

fluctuations

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PAHs (polyciclyc aromatic hydrocarbons) are a family of very stable planar molecules, based on benzene ring which has an aromatic bond in which a  orbital is shared in the chain.

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slide38

“Unidentified Infrared Bands” commonly interpreted by C-C and C-H vibration modes, due to the absorption of a single uv photon, in large planar Polycyclic Aromatic Hydrocarbons (PAHs) molecules, with size ~ 10 Å and containing ~ 50–100 C atoms.

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slide39

PAH vibrational spectra resembles those of emission bands in many astrophysical objects

Observed mid-IR spectra require mixture of PAHs, but mixture seems to be similar in different objects where PAHs seen

However, there is evidence that in denser environments and stronger UV field intensities the PAHs may be depleted.

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geometrical effects 2
Geometrical effects (2)
  • Dust is in 2-phase medium: dense molecular clouds (MCs) & diffuse ISM
  • Stars also not smoothly distributed: stars form inside MCs & then escape or disperse parent clouds after few Myr

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geometrical effects 3
Geometrical effects (3)

Consequences:

  • Stellar age-dependent dust extinction (since young stars in dustiest regions)
  • Dust column density effectively wavelength dependent (since younger stars emit at shorter wavelengths) - has implications for attenuation law
  • Different radiative heating of dust grains in different environments - large dust grains heated to higher T in star-forming clouds than in diffuse ISM

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computing effects of dust on galaxy sed
Computing effects of dust on galaxy SED
  • Need to compute radiative transfer of starlight through dust distribution, allowing for clumping of stars & gas
  • Need to compute temperatures of dust grains of different types & sizes in different radiative environments
  • A code which does this is GRASIL (Silva, Granato & Bressan & Danese1998)

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example seds computed using grasil fit to observed galaxies
Example SEDs computed using GRASIL fit to observed galaxies

(Silva et al 1998)

M100 (spiral) M82 (starburst)

tesc = 3 Myr tesc = 10 Myr

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important parameters in grasil dust model
Important parameters in GRASIL dust model
  • tesc = timescale for stars to escape from parent clouds
    • net UV attenuation v. sensitive to this in star-forming galaxies
  • cloud = dust optical depth in molecular clouds
    • mid-IR dust emission sensitive to this, since clouds opt thick in mid-IR

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radio
Radio

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contributions to radio emission from normal galaxies
Contributions to radio emission from normal galaxies
  • Thermal emission

- from ionized gas in HII regions

  • Non-thermal emission
    • from relativistic electrons accelerated in supernova remnant (SNR) shock waves
    • emit synchrotron radiation when orbit in magnetic field

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thermal radio emission
Thermal Radio emission

(Condon 92)

Thermal

  • free-free (bresstrahlung) emission from ionized gas in HII regions
  • Mainly sensitive to Q(H) = H-ionizing photon luminosity
  • This is easy to obtain from integrated stellar SED
  • Weak dependence on metallicity through equilibrium Te
  • Thermal radio emission begins promptly when O stars form
  • The radio slope is flat in Lvs 

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non thermal radio emission
Non Thermal Radio emission
  • FIR/Radio correlation for normal (including starburst) galaxies suggests link with SF
  • thought to be Synchrotronradiation from relativistic electrons accelerated in shock waves of SNRs produced by Type II supernovae
  • implies link to SNII rate
  • contributions from both individual SNRs & electrons in general ISM
  • but general ISM dominates
  • slope depends on energy spectrum of relativistic electrons, observationally find:
  • so non-thermal dominates over thermal at low (large )

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slide50

Non Thermal Radio emission (2)

  • total non-thermal energy emitted per SN not known theoretically
    • - in principle depends on both efficiency of shock acceleration of electrons and on strength of B-field
  • but tightness of radio-FIR correlation in galaxies of differerent types (normal & starburst) seems to require that NT energy per SN nearly constant
    • - therefore calibrate relation on values for our Galaxy:

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predictions of grasil sed model including radio emission
Predictions of GRASIL SED model including radio emission

(Bressan et al 2003)

M51 (spiral) M82 (starburst)

- model also reproduces observed radio-FIR correln

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