First Results on the Star Formation and Dust
Extinction of Local Galaxies from AKARI AllSky Survey
Tsutomu T. TAKEUCHI
Institute for Advanced Research, Nagoya University, JAPANFang-Ting, YUAN, Katsuhiro L. MURATA
Division of Particle and Astrophysical Science, Nagoya University, JAPAN
Véronique BUAT, Élodie GIOVANNOLI, Denis BURGARELLALaboratoire d’Astrophysique de Marseille, OAMP, FRANCE
Jorge Iglesias-Páramo
Instituto de Astrofísica de Andalucía, CSIC, SPAIN
Sébastien HEINIS
Department of Physics and Astronomy, The Johns Hopkins University, USA
Agnieszka POLLO, Piotr RYBKA
Instytut Problemów Jądrowich im. Andrzeja Sołtana, POLAND

27th Grain Formation WS/Dust in Galaxies, Osaka, 10 Oct. 2009

1. The Star Formation History in the Universe
1.1 How to Estimate the SFR from Observations
The SFR of galaxies is estimated based on the measurementof the total ultraviolet (UV) light from massive stars.
UV
Massive stars＋

Theory of stars=Number ofmassive stars

Since the lifetime of massive stars (~ 106 yr) is much shorter than
the age of galaxies, their number can be regarded as the currentSFR.

1.1 How to Estimate the SFR from Observations
By using a mass distribution function of stars at their birth(initial mass function: IMF), we can convert the number ofmassive stars (current massive SFR) to the total number of
newly born stars, i.e., the total SFR.
Some examples of the IMF
estimated from observations.
The IMF is often approximatedby a power-law form withreasonable lower and uppermasses.

(Kroupa 2002)

1.2 Problem in the Estimation of SFR from UV

FIR

FUV
Dust

Short-wavelength photons like UV are scattered andabsorbed by small solid grains, i.e., dust (referred to as“extinction”), and re-emitted from dust at far-infrared (FIR).
Hence, to obtain an unbiased view of the cosmic starformation, it is crucial to treat the information of both
FUV and FIR.

M31 (the Andromeda galaxy)

Optical

FUV

FIR

1.3 The cosmic star formation history at z < 1Hidden SF

Directly observed SF

The local fraction of the hidden SF is 50-60%, while thefraction at z=1 reaches around 80% (Takeuchi et al.
2005a).

2. Multiband Galaxy Sample from AKARI ASS
2.1 Construction of the sample

Red: AKARI
Blue: IRAS matchedFirst, AKARI Bright Source Catalog sample (β-1.1)wasmatched with IRAS PSCz (60μm selected redshift survey:
confirmed galaxies) (by YUAN Fang-Ting).

2.1 Construction of the sample

Parent sample (~ 6000 galaxies).

2.1 Construction of the sample

Red: AKARI-IRAS
Green: galaxies in the SDSS
Yellow: cirrus-contaminatedSelect galaxies in the SDSS DR7 (optical survey) region (~ 8000deg2). This selection automatically excluded galaxies in highcirrus sky regions. 1186 galaxies were selected.

2.1 Construction of the sample
The parent sample was further matched with
1. GALEX: all-sky ultraviolet (UV) survey at 1530Å and 2315Å
2. SDSS: large optical survey at u, g, r, i, z
3. 2MASS: all-sky near-infrared (NIR) survey at J, H, K

Final sample consists of 607 galaxies with good quality flux
measurement at UV-optical-NIR-MIR-FIR.

2.2 Properties of the sample galaxies
Number counts from UV to FIR

Number count slope becomes steeper and steeper from UV to FIR.
The effective detection limit at 90μm is ~ 0.8 Jy.

Redshift and 90μm luminosity distributions

Since the AKARI BSC β-1 is rather shallow, most of the galaxies
in the sample are local (z < 0.05). FIR luminosities range from 106to 1012L☉. In this sample, a few are ULIRGs.

2.3 Basic Results from the Sample
Spectral energy distributions (SEDs) of the sample

Red symbols and lines are SEDs
obtained by AKARI FIS, and black
ones are from GALEX, SDSS,
2MASS, and IRAS.
The sample galaxies have a large
variety of SEDs.

Average SEDs as a function of 90μm luminosity
We find a clear trend of theshape of SEDs as a functionof 90μm luminosity, eventhough we have various SEDs
in each 90μm luminosity bin(see the difference between
the average and medianvalues).
Low L90 galaxies have bluer
SEDs, while high-L90 ones
have redder.

A formula to estimate the total IR luminosity from FIS flux
To calculate star-formation and extinction related quantities
of galaxies, total IR luminosity is necessary.
FIR (λ=44‐122μm: Helou et al. 1988)
Total IR (λ=3‐1100μm: Dale et al. 2001)

Total IR (λ=3‐1100μm: Dale & Helou 2002)
Total IR (λ=8‐1000μm: Sanders & Mirabel 1996)

A formula to estimate the total IR luminosity from FIS flux
Hirashita et al. (2008) proposed a formula to estimate theFIR flux from N60, WIDE-S, and WIDE-L fluxes:
LAKARI = Δν( N60 ) L65μm + Δν(WIDE - S ) L90μm + Δν(WIDE - L) L140μm
Δν( N60 ) = 1.58 × 1012 [Hz]Δν(WIDE - S ) = 1.47 × 1012 [Hz]Δν(WIDE - L) = 0.831×1012 [Hz](N.B. Thanks to the continuous bands of FIS, this formula
was constructed without any interpolation).
Since we have both AKARI FIS and IRAS fluxes, we canconstruct the desirable formula by comparing LAKARI and LTIR.

A formula to estimate the total IR luminosity from FIS flux

LTIR = 8.21LAKARI

0.91

r = 0.987

AKARI IRC ASS will be used to explore this issue further.

Total IR (dust) luminosity vs. FUV luminosity

Total dust luminosity LTIR is much higher than the FUV
luminosity LFUV.

Star-formation luminosity
Since we have both FUV and FIR fluxes, we can obtain thetotal luminosity contribution from newly forming stars. We
refer to it as the star-formation luminosity LSF:
LSF = LFUV + 0.7 LTIR

(0.7: correction for old stars)

Star formation rates (SFRs) estimated from FUV and IR
Assuming the Salpeter IMF, wehave conversion formulae from
FUV/dust luminosities to the SFR.
log SFR FUV = log LFUV − 9.51
log SFR dust = log LTIR − 9.75 − log(1 − η)
SFR = SFR FUV + SFR dust

Star formation rates (SFRs) estimated from FUV and IR
Assuming the Salpeter IMF, wehave conversion formulae from
FUV/dust luminosities to the SFR.
log SFR FUV = log LFUV − 9.51log SFR dust = log LTIR − 9.75 − log(1 − η)
SFR = SFR FUV + SFR dust

No galaxies have SFRFUV fraction > 0.2 if SFR > 2×10 M☉yr-1.

The average extinction trend as a function of LSF: IRAS result
Dust attenuation at FUV, AFUV,
is uniquely determined by the
dust-to-FUV luminosity ratio.
The relation is approximated asi.e., the more the SF is active, the more the galaxy is extinguished.
The extinction of the UV and IR selected samples agree with eachother.

The average extinction trend as a function of LSF: AKARI result

A similar trend was found by AKARI for the dust extinction ofgalaxies.

3. To Go Further: Galaxy Selection by FIR Colors
3.1 Need for Star-Galaxy Separation
As we have seen, a study with all-sky surveys is a very
efficient way of exploring the general properties of galaxies.
However, we had to select confirmed galaxies (in our case, byIRAS PSCz).
In general, when we start a systematic statistical studies ongalaxies, especially when we try to measure their redshifts,
we have to select good galaxy candidates; otherwise we waste
observation time.
Hence, in the case of pure FIR surveys, a systematic method
to extract reliable galaxy candidates is desired.

3.2 Preceding Study from IRAS

(Walker et al. 1989)
With IRAS four bands, a very detailed classification waspossible. However, for AKARI FIS ASS, we must rely only on
FIR bands, and this cannot be a trivial application of IRAS
methodology.

3.3 Star-Galaxy Separation by FIS Color-Color
Diagrams
Data
1. We selected WIDE-S sources in a low-cirrus region(I100 < 10 MJy sr-1) on the sky to avoid contaminationin FIR flux (~ 5000 objects).

2. The sample was matched with SIMBAD and NED(astronomical database for stars, nebulae, and galaxies).

Color-color diagram (an example)

Red: galaxies
Blue: stars
Yellow: other Galacticobjects
Green: unidentified
We found that we can define a separation line on the FIS colorcolor plot to select > 97% of galaxies (Pollo et al. A&A submitted).

4. Summary
1. We have constructed a sample of local galaxies selected byAKARI WIDE-S by matching IRAS PSCz galaxies, andassociated fluxes from UV to FIR (GALEX, SDSS, 2MASS).
2. By this sample, we constructed average SEDs of galaxies asa function of L90.
3. We have established a new formula to estimate total IR(dust) emission and hidden SFR from three AKARI FIS
bands (N60, WIDE-S, and WIDE-L).
4. Based on the formula, we found that hidden star formation
dominates the star formation activity of most of the FIS
selected local galaxies.
5. We also established a method to select galaxy candidates
only from FIS color-color diagrams, with > 97%
completeness.

0. Introduction: the Evolution of the Universe
0.1 The Global History of the Universe

http://map.gsfc.nasa.gov/m_mm.html

0.2 Chemical evolution of galaxies
Star formation
Heavy element production

Mass ejection
ISM

Stellar evolution

Stellar winds
PNe
Heavy element production
Supply of heavy
elements

Mass ejection
SNRs

Stellar death
Heavy element production

0.2 Chemical evolution of galaxies
Dust production

Star formation

Protoplanetary
disk

Heavy element production

Mass ejection
ISM

Dust production
Stellar evolution

Stellar winds
PNe
Heavy element production
Supply of heavyelements

Mass ejection
SNRs

Stellar death
Heavy element production

Cool star atmosphere
PNe

Dust production
SNRs

Blast wave by SNe

Dust destruction

Luminosity with redshifts

FIR luminosity goes up continuously, while optical/NIR saturates(reflection of their luminosity functions). UV has large scatter.

Comparison between observed and estimated IR luminosities(Takeuchi et al. 2005b)
The difference between LFIR and true LIR is important inrelation to cold dust.

Relation between FUV-TIR luminosity ratio and AFUV
It is known that the extinction in galaxies is expressed as anonlinear function of the flux ratio between FIR and FUV:

(Buat et al. 2005)
Hence, we can see how the extinction depends on galaxy
properties through the FIR/FUV luminosity ratio.

Acknowledgement
TTT has been supported by Program for Improvement of Research
Environment for Young Researchers from Special Coordination
Funds for Promoting Science and Technology commissioned by theMinistry of Education, Culture, Sports, Science and Technology(MEXT) of Japan.