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Journal ArticleDOI

Infrared luminosity functions based on 18 mid-infrared bands: revealing cosmic star formation history with AKARI and Hyper Suprime-Cam

TL;DR: In this paper, the authors performed a census of dust-obscured CSFH in the entire AKARI NEP field in 5 broad bands and estimated total infrared LFs at 0.35$ <$z$<$2.2.
Abstract: Much of the star formation is obscured by dust. For the complete understanding of the cosmic star formation history (CSFH), infrared (IR) census is indispensable. AKARI carried out deep mid-infrared observations using its continuous 9-band filters in the North Ecliptic Pole (NEP) field (5.4 deg$^2$). This took significant amount of satellite's lifetime, $\sim$10\% of the entire pointed observations. By combining archival Spitzer (5 bands) and WISE (4 bands) mid-IR photometry, we have, in total, 18 band mid-IR photometry, which is the most comprehensive photometric coverage in mid-IR for thousands of galaxies. However previously, we only had shallow optical imaging ($\sim$25.9ABmag) in a small area of 1.0 deg$^2$. As a result, there remained thousands of AKARI's infrared sources undetected in optical. Using the new Hyper Suprime-Cam on Subaru telescope, we obtained deep enough optical images of the entire AKARI NEP field in 5 broad bands ($g\sim$27.5mag). These provided photometric redshift, and thereby IR luminosity for the previously undetected faint AKARI IR sources. Combined with the accurate mid-IR luminosity measurement, we constructed mid-IR LFs, and thereby performed a census of dust-obscured CSFH in the entire AKARI NEP field. We have measured restframe 8$\mu$m, 12$\mu$m luminosity functions (LFs), and estimated total infrared LFs at 0.35$<$z$<$2.2. Our results are consistent with our previous work, but with much reduced statistical errors thanks to the large area coverage of the new data. We have possibly witnessed the turnover of CSFH at $z\sim$2.

Summary (3 min read)

1 Introduction

  • Mid-infrared (mid-IR) is one of the less explored wavelengths due to the earth's atmosphere, and difficulties in developing sensitive detectors.
  • To overcome these problems, the authors have newly obtained deeper optical data over the entire AKARI NEP wide field, using the Hyper-Suprime Cam on the Subaru telescope.
  • Using the deeper optical data, in this paper, the authors measure mid-infrared galaxy LFs, and estimate total IR LFs (based on the mid-IR SED fitting) from the entire AKARI NEP field.

2 Data

  • To rectify the situation and to fully exploit the AKARI's spacebased data, the authors carried out an optical survey of the AKARI NEP wide field (PI:Goto) using Subaru's new Hyper Suprime-Cam (HSC; Miyazaki et al. 2018) in five optical bands (g, r, i, z, and y, Oi et al. 2018 submitted) .
  • The HSC has a field-of-view (FoV) of 1.5 deg in diameter, covered with 104 red-sensitive CCDs.
  • It has the largest FoV among optical cameras on 8m-class telescopes, and can cover the AKARI NEP wide field (5.4 deg 2 ) with only 4 FoV (Fig. 1 ).
  • See Oi et al. (2018, submitted) for more details of the observation and data reduction.
  • Subaru telescope does not have u * -band capability, while it is critically important to accurately estimate photometric redshifts (photo-z) of low-z galaxies.

3 Analysis

  • Uncertainties of the LF values include fluctuations in the number of sources in each luminosity bin, the photometric redshift uncertainties, the k-correction uncertainties, and the flux errors.
  • To estimate errors, the authors used Monte Carlo simulations from 1000 simulated catalogs.
  • A new flux is also assigned following a Gaussian distribution with the width of flux error.
  • The smaller data points at the faint ends are adopted from the NEP deep field, where AKARI data are deeper (Goto et al. 2015) , and are included in the fit.
  • Vertical arrows show the 8µm luminosity corresponding to the flux limit at the central redshift in each redshift bin.

4.1 The 8µm LF

  • The authors first present monochromatic 8µm LFs, because the 8µm luminosity (L8µm) has been known as a good indicator of the TIR luminosity (Babbedge et al.
  • Often in previous work, SED based extrapolation was needed to estimate the 8µm luminosity.
  • This is not the case for the analysis present in this paper.
  • The smaller data points at the faint ends are adopted from the NEP deep field, where AKARI data are deeper (Goto et al. 2015) , and are included in the fit.
  • Vertical arrows show the 12µm luminosity corresponding to the flux limit at the central redshift in each redshift bin.

templates (2% from the sample).

  • The authors corrected for the completeness using Kim et al. (2012) (25% correction at maximum, with their selection to the 80% completeness limits).
  • Then, the 1/Vmax method was used to compensate for the flux limit.
  • Various previous studies are shown with dashed lines for comparison.
  • Interestingly, the 8µm LFs peaks in the 3rd bin (z∼1), then declines toward z∼2.

4.2 12µm LF

  • The 12µm luminosity L12µm) is also known to correlate well with the TIR luminosity (Spinoglio et al.
  • AKARI's advantage still holds in not needing extrapolation based on SED models.
  • Various previous studies are shown in dash-dotted lines.
  • Similar to the 8µm LF, the evolution becomes less evident between the two higher redshift bins.

4.3 Total IR LFs estimated from mid-IR SED fit

  • The authors caution readers that estimation of the LTIR involves extrapolation to the far-IR wavelength range based on the SED models, and thus invites associated uncertainty, as they further discuss in Section 5.
  • The L18W flux (Matsuhara et al. 2006 ) are used to apply the 1/Vmax method, because it is a wide, sensitive filter (but using the L15 flux limit does not change their main results).
  • For clarity, the authors separated LFs in four different panels at each redshift bin.
  • The TIR LFs show a strong evolution compared to local LFs, but again turns over at z > 1.2.

4.4.1 Total IR Luminosity Density from L8µm

  • LFs First, the authors estimate Total IR Luminosity Density from L8µm LFs.
  • Possible SED evolution, and the presence of AGN will induce further uncertainty.
  • Murata et al. (2014) also reported that L8µm/LTIR is constant at below the main sequence, while it decreases with starburstiness at above the main sequence, concluding that starburst galaxies have deficient PAH emission compared with main-sequence galaxies.
  • Overplotted previous studies are taken from Le Floc'h et al. ( 2005) in the dark-green, dash-dotted line, Magnelli et al. (2013) in the dark-red, dash-dotted line, Huynh et al. (2007) in the dark-yellow, dash-dotted line, Gruppioni et al. (2013) in the pink, dash-dotted line at several redshifts as marked in the figure.

4.4.2 Total IR Luminosity Density from L12µm LFs

  • Due to the same reasons as L8µm (improved statistics, and availability of 140 and 160µm), the authors use the following conversion (Goto et al. 2011b) .
  • The authors caution readers again here for the use of a single conversion for varieties of galaxies with different SFR at different redshifts.
  • Results should be interpreted with this uncertainty in mind.

4.4.3 Integration to TIR density

  • The derived total LFs are multiplied by LTIR and integrated to measure the TIR density ( ΩTIR).
  • Following their previous work, the authors use a double-power law.
  • With the lowest redshift LF, the authors first fit the normalization (Φ * ) and slopes (α, β).
  • The authors also note that ΩIR from 12µm is sensitive to the faint-end slope of 12µm LFs.
  • Much deeper observations are awaited to clarify the issue.

5 Discussion

  • The conversions are based on local star-forming galaxies.
  • The pink dashed line shows the total estimate of IR (TIR LF) and UV (Schiminovich et al. 2005) .
  • Following the results in the literature discussed in Section 4.3, in this section, the authors compare LT IR estimated from L8µm and L12µm from equations 1 and 2 in three overlapping redshift ranges in Fig. 6 using their data.
  • One can immediately notice that the relation deviates at logLTIR >12 (or equivalently at z > 1).
  • 4 and 5 between midand far-IR measurements could be the result of the change in the SED, rather than incorrect measurements on either.

6 Summary

  • Previously AKARI NEP wide field lacked deep optical photometry, and thereby, accurate photo-z, despite the presence of space-based 9-band mid-IR photometry from AKARI.
  • To rectify the situation, the authors have obtained deep optical 5-band imaging covering the entire 5.4 deg 2 of the NEP wide field, using the new Hyper Suprime-Cam mounted on the Subaru 8m telescope.
  • Thanks to the large area coverage, the brightends are better-determined.

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Infrared luminosity functions based on 18 mid-infrared
bands: revealing cosmic star formation history with
AKARI and Hyper Suprime-Cam*
Journal Item
How to cite:
Goto, Tomotsugu; Oi, Nagisa; Utsumi, Yousuke; Momose, Rieko; Matsuhara, Hideo; Hashimoto, Tetsuya;
Toba, Yoshiki; Ohyama, Youichi; Takagi, Toshinobu; Chiang, Chia-Ying; Kim, Seong Jin; Kilerci Eser, Ece; Malkan,
Matthew; Kim, Helen; Miyaji, Takamitsu; Im, Myungshin; Nakagawa, Takao; Jeong, Woong-Seob; Pearson, Chris;
Barrufet, Laia; Sedgwick, Chris; Burgarella, Denis; Buat, Veronique and Ikeda, Hiroyuki (2019). Infrared luminosity
functions based on 18 mid-infrared bands: revealing cosmic star formation history with AKARI and Hyper Suprime-
Cam*. Publications of the Astronomical Society of Japan, 71(2), article no. 30.
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2019 The Authors
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arXiv:1902.02801v1 [astro-ph.GA] 7 Feb 2019
Publ. Astron. Soc. Japan (2014) 00(0), 1–10
doi: 10.1093/pasj/xxx000
1
Infrared luminosity functions based on 18
mid-infrared bands: revealing cosmic star
formation history with AKARI and Hyper
Suprime-Cam
Tomotsugu GOTO
1
, Nagisa OI
2
, Yousuke UTSUMI
3
, Rieko MOMOSE
1,4
,
Hideo MATSUHARA
5
, Tetsuya HASHIMOTO
1
, Yoshiki TOBA
6
, Youichi
OHYAMA
6
, Toshinobu TAKAGI
7
, Chia Ying CHIANG
1
, Seong Jin KIM
1
, Ece
KILERCI ESER
1
, Matthew MALKAN
8
, Helen KIM
8
, Takamitsu MIYAJI
9
,
Myungshin IM
10
, Takao NAKAGAWA
5
, Woong-Seob JEONG
11,12
, Chris
PEARSON
13,14
, Laia BARRUFET
15
, Chris SEDGWICK
14
, Denis BURGARELLA
16
,
Veronique BUAT
16
and Hiroyuki IKEDA
17
1
National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan 30013
2
Tokyo University of Science, 1-3 Kagurazaka, Shinjuku-ku, Tokyo 162-8601, Japan
3
Kavli Institute for Particle Astrophysics and Cosmology (KIPAC), SLAC National Accelerator
Laboratory, Stanford University, SLAC, 2575 Sand Hill Road, Menlo Park, CA 94025, USA
4
Department of Astronomy, School of Science, The University of Tokyo 7-3-1 Hongo,
Bunkyo-ku, Tokyo 113-0033, JAPAN
5
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 3-1-1
Yoshinodai, Chuo, Sagamihara, Kanagawa 252-5210, Japan
6
Academia Sinica Institute of Astronomy and Astrophysics, P.O. Box 23-141, Taipei 10617,
Taiwan
7
Japan Space Forum, 3-2-1, Kandasurugadai, Chiyoda-k u, Tokyo 101-0062 Japan
8
Department of Physics and Astronomy, UCLA, Los Angeles, CA, 90095-1547, USA
9
Insitituto de Astronom´ıa, U niversidad Nacional Aut
´
onoma de M
´
exico
10
Astronomy Program, Department of Physics & Astr onomy, FPRD, Seoul National University,
Shillim-Dong, Kwanak-Gu, Seoul 151-742, Korea
11
Korea Astronomy and Space Science Institute (KASI), 776 Daedeok-daero, Yuseong-gu,
Daejeon 34055, Korea
12
Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113,
Korea
13
RAL Space, STFC Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0QX, UK
14
The Open University, Milton Keynes, MK7 6AA, UK
15
European Space Astronomy Centre, 28691 Villanueva de la Canada, Spain
16
Aix-Marseille Universit, CNRS LAM (Laboratoire dAstrophysique de Marseille) UMR 7326,
13388 Mars eille, France
c
2014. Astronomical Society of Japan.

2 Publications of the Astronomical Society of Japan, (2014), Vol. 00, No. 0
17
National Astronomical Observatory, 2-21-1 Osawa, Mitaka, Tokyo, Japan
E-mail: tomo@gapp.nthu.edu.tw
Received 2018 June 30; Accepted 2019 January 21
Abstract
Much of the star formation is obscured by dust. For the complete understanding of the cosmic
star formation history (CSFH), infrared (IR) census is indispensable. AKARI carried out deep
mid-infrared observations using its continuous 9-band filters in the North Ecliptic Pole (NEP)
field (5.4 deg
2
). This took significant amount of satellite’s lifetime, 10% of the entire pointed
observations. By combining archival Spitzer (5 bands) and WISE (4 bands) mid-IR photometry,
we have, in total, 18 band mid-IR photometry, which is the most comprehensive photometric
coverage in mid-IR for thousands of galaxies. However previously, we only had shallow optical
imaging (25.9ABmag) in a small area of 1.0 deg
2
. As a result, there remained thousands of
AKARI’s infrared sources undetected in optical. Using the new Hyper Suprime-Cam on Subaru
telescope, we obtained deep enough optical images of the entire AKARI NEP eld in 5 broad
bands (g 27.5mag). These provided photometric redshift, and thereby IR luminosity for the
previously undetected faint AKARI IR sour ces. Combined with the accurate mid-IR luminosity
measurement, we constr ucted mid-IR LFs, and thereby performed a census of dust-obs cured
CSFH in the entire AKARI NEP eld. We have measured restframe 8µm, 12µm luminosity
functions (LFs), and estimated total infrared LFs at 0.35<z<2.2. Our results are consistent with
our previous work, but with much reduced statistical err ors thanks to the large area coverage
of the new data. We have possibly witnessed the turnover of CSFH at z 2.
Key words: AKARI, infrared galaxies, cosmic star formation history
1 Introduction
Mid-infrared ( mid-IR) is one of the less explored wavelengths
due to the earth’s atmosphere, and difficulties in developing sen-
sitive detectors. NASA’s S pitzer and WISE space telescopes
only had four filters in the mid-IR wavelength range, hamper-
ing studies of distant galaxies.
AKARI space telescope has a potential to revolutionize the
field. Using its 9 continuous mid-IR filters (2-24µm), AKARI
performed a deep imaging survey in the North Ecliptic Pole
(NEP) field over 5.4 deg
2
. Using AKARI’s 9 mid-IR band pho-
tometry, mid-IR SED diagnosis can be performed for thousands
of galaxies, for the first time, over the large enough area to over-
come cosmic variance. Environmental effects on galaxy evolu-
tion can be also investigated with the large volume coverage
(Koyama et al. 2008; Goto et al. 2010a).
However, previously, we were limited by a poor optical cov-
erage both in area and depths. Over this wide area, only shal-
low optical/NIR imaging data have been available (Hwang et al.
2007; Jeon et al. 2010, 2014). Deep optical images are limited
to the central 0.25 deg
2
.
To overcome these problems, we have newly obtained
deeper optical data over the entire AKARI NEP wide field, us-
ing the Hyper-Suprime Cam on the Subaru telescope. Using
the deeper optical data, in this paper, we measure mid-infrared
galaxy LFs, and estimate total IR LFs (based on the mid-IR
SED fitting) from the entire AKARI NEP field. Unless oth-
erwise stated, we assume a cosmology with (h,
m
,
Λ
) =
(0.7,0.3,0.7).
2 Data
To rectify the situation and to fully exploit the AKARI’s space-
based data, we carr ied out an optical survey of the AKARI NEP
wide field (PI:Goto) using Subaru’s new Hyper Suprime-Cam
(HSC; Miyazaki et al. 2018) in five optical bands (g, r,i, z, and
y, Oi et al. 2018 submitted). The HSC has a field-of-view (FoV)
of 1.5 deg in diameter, covered with 104 red-sensitive CCDs. It
has the largest FoV among optical cameras on 8m-class tele-
scopes, and can cover the AKARI NEP wide field (5.4 deg
2
)
with only 4 FoV (Fig.1). The 5 sigma limiting magnitudes are
27.18, 26.71, 26.10, 25.26, and 24.78 mag [AB] in g,r,i,z, and
y-bands, respectively. See Oi et al. (2018, submitted) for more
details of the observation and data reduction.
Subaru telescope does not have u
-band capability, while it
is critically important to accurately estimate photometric red-
shifts (photo-z) of low-z galaxies. Therefore, we obtained u
-
band image of the AKARI NEP wide eld using the Megaprime
camera of Canada France Hawaii Telescope (PI :Goto, Goto

Publications of the Astronomical Society of Japan, (2014), Vol. 00, No. 0 3
45:00.0
17:50:00.0
55:00.0
18:00:00.0
05:00.0
10:00.0
15:00.0
65:00:00.0
30:00.0
66:00:00.0
30:00.0
67:00:00.0
30:00.0
Right ascension
Declination
Fig. 1. HSC three color (g, r, i) composite image of the NEP wide field (5.4 deg
2
). The AKARI NEP wide data exist within the white circle.
et al. 2017). Combining the optical six bands, we have obtained
accurate photo-z in the AKARI NEP field (Oi et al. 2018, sub-
mitted). To the detection limit in L18W filter (18.3 ABmag,
Kim et al. 2012), we have 5078 infrared sources.
In addition to the AKARI’s 9 mid-IR bands, in the AKARI
NEP field, there exit archival deep Spitzer (IRAC1,2,3,4 and
MIPS24, Nayyeri et al. 2018) and WISE (W 1, W 2, W 3, and
W 4) images as well. By combining all available mid-IR bands,
in total we used 18 mid-IR bands, which are one of the most
comprehensive mid-IR data sets for thousands of galaxies.
3 Analysis
To compute LFs, we use the 1/V
max
method, following Goto
et al. (2010b, 2015). Uncertainties of the LF values include
fluctuations in the number of sources in each luminosity bin,
the photometric redshift uncertainties, the k-correction uncer-
tainties, and the flux errors. To estimate errors, we used Monte
Carlo simulations from 1000 simulated catalogs. Each sim-
ulated catalog contains the same number of sources. These
sources are assigned with a new redshift, to follow a Gaussian
distribution centered at the photo-z with the width of z/(1 +
z) ( 0.060, Oi et al. in preparation). A new flux is also as-
signed following a Gaussian distribution with the width of flux
error. For total infrared (TIR) LF errors, we re-performed the
SED fit for the 1000 simulated catalogs. Note that total in-
frared luminosity is estimated based on mid-IR SED tting al-
though we have intensive 18-band filter coverage in mid-IR, as
explained in Section 4.3. We ignored the cosmic variance due
to our much improved volume coverage. All the other err ors

4 Publications of the Astronomical Society of Japan, (2014), Vol. 00, No. 0
Fig. 2. Restframe 8µm LFs based on the AKARI NEP wide field. The blue
diamonds, the purple triangles, the red squares, and the orange crosses
show the 8µm LFs at 0.28 < z < 0.47, 0.65 < z < 0.90, 1.09 < z < 1.41,
and 1.78 < z < 2.22, respectively. AKARI’s MIR filters can observe rest-
frame 8µm at these redshifts in a corresponding filter. Error bars are esti-
mated from the Monte Carlo simulations (§3). The dotted l ines show analytic
fits with a double-power law. The smaller data points at the faint ends are
adopted from the NEP deep field, where AKARI data are deeper (Goto et al.
2015), and are included in the fit. Vertical arrows show the 8µm luminos-
ity corresponding to the flux limit at the central redshift in each redshift bin.
Overplotted LFs are B abbedge et al. (2006) in the pink dash-dotted lines,
Caputi et al. (2007) in the cyan dash-dotted lines, Huang et al. (2007) in
the dark-yellow dash-dotted lines, F u et al. (2010), in the dark green dash-
dotted line, and Kim et al. (2015) in the bright green dash-dotted line. Best-fit
parameters are presented in Table 1.
described above are added to the Poisson errors for each LF bin
in quadrature.
4 Results
4.1 The 8µm LF
We firs t present monochromatic 8µm LFs, because the 8µm lu-
minosity (L
8µm
) has been known as a good indicator of the TIR
luminosity (Babbedge et al. 2006; Huang et al. 2007; Goto et al.
2011a).
An advantage of AKARI is that we do not need k-correction
because one of the continuous filters always convert the rest-
frame 8µm at our redshift range of 0.28 < z < 2.22. Often in
previous work, SED based extrapolation was needed to estimate
the 8µm luminosity. This was often the largest uncertainty. This
is not the case for the analysis present in this paper.
To estimate the restframe 8µm LFs, we followed our previ-
ous method in Goto et al. (2015) as we briefly summarize below.
We used sources down to 80% completeness limits ( Kim et al.
2012). Galaxies are excluded when SEDs were better fit to QSO
Fig. 3. Restframe 12µm LFs based on the AKARI NEP wide field.
Luminosity unit is logarithmic solar luminosity (L
). The blue diamonds,
the purple triangles, and the red squares show the 12µm LFs at 0.15 < z <
0.35, 0.38 < z < 0.62, and 0.84 < z < 1.16, respectively. The smaller data
points at the faint ends are adopted from the NEP deep field, where AKARI
data are deeper (Goto et al. 2015), and are included in the fit. Vertical arrows
show the 12µm luminosity corresponding to the flux limit at the central red-
shift in each redshift bin. Overplotted LFs are P
´
erez-Gonz
´
alez et al. (2005)
at z=0.3, 0.5 and 0.9 in the dark-cyan dash-dotted l ines, Toba et al. (2014)
at 0< z <0.05 based on WISE in the dark green dash-dotted lines, Rush
et al. (1993) at 0< z <0.3 in the light green dash-dotted lines, and Kim et al.
(2015) at 0< z <0.3 in the pink dash-dotted line. Note Rush et al. (1993) is
at higher redshifts than Toba et al. (2014). Best-fit parameters are presented
in Table 1.
templates (2% from the sample).
We corrected for the completeness using Kim et al. (2012)
(25% correction at maximum, with our selection to the 80%
completeness limits). Four redshift bins of 0.28< z <0.47,
0.65< z <0.90, 1.09< z <1.41, and 1.78< z <2.22, were used,
following our previous work. Then, the 1/V
max
method was
used to compensate for the flux limit.
The resulting restframe 8µm LFs are shown in Fig. 2. The
arrows show the flux limit at the m edian redshift in bin. We
performed the Monte Carlo simulation to obtain errors. They
are smaller than in our previous work (Goto et al. 2010b, 2015)
thanks to the improved area coverage. The faint end marked
with smaller data points are adopted from the NEP deep field,
where AKARI data are deeper (Goto et al. 2015).
Various previous studies are shown with dashed lines for
comparison. Compared to the local LF, our 8µm LFs show
strong evolution in luminosity up to z 0.9. Interestingly, the
8µm LFs peaks in the 3rd bin ( z1), then declines toward z2.

Citations
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50 citations

Journal ArticleDOI
TL;DR: In this article, the authors constrain the rest-frame FUV, NUV and U-band luminosity functions with unprecedented precision from z ∼ 0.2 to z ∼ 3.
Abstract: We constrain the rest-frame FUV (1546 A), NUV (2345 A), and U-band (3690 A) luminosity functions (LFs) and luminosity densities (LDs) with unprecedented precision from z ∼ 0.2 to z ∼ 3 (FUV, NUV) and z ∼ 2 (U band). Our sample of over 4.3 million galaxies, selected from the CFHT Large Area U-band Deep Survey (CLAUDS) and HyperSuprime-Cam Subaru Strategic Program (HSC-SSP) data lets us probe the very faint regime (down to MFUV, MNUV, MU ≃ −15 at low redshift), while simultaneously detecting very rare galaxies at the bright end down to comoving densities 1 it is due to the evolution of both $M^\star _{\rm UV}$ and the characteristic number density $\phi ^\star _{\rm UV}$. In contrast, the U-band LF has an excess of faint galaxies and is fitted with a double-Schechter form; $M^\star _{U}$, both $\phi ^\star _{U}$ components, and the bright-end slope evolve throughout 0.2 < z < 2, while the faint-end slope is constant over at least the measurable 0.05 < z < 0.6. We present tables of our Schechter parameters and LD measurements that can be used for testing theoretical galaxy evolution models and forecasting future observations.

34 citations


Cites background from "Infrared luminosity functions based..."

  • ...…have been possible for some time for high-z galaxies (e.g., Hughes et al. 1998; Chapman et al. 2005; Magnelli et al. 2013; Gruppioni et al. 2013; Goto et al. 2019), they do not yet provide significant insights at very high redshifts (z>∼ 6), nor for low-mass galaxies which have low SFRs and low…...

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Journal ArticleDOI
TL;DR: In this article, the authors estimate the detections of non-repeating and repeating fast radio bursts separately, based on latest observational constraints on their physical properties including the spectral indices, FRB luminosity functions, and their redshift evolutions.
Abstract: Fast radio bursts (FRBs) are mysterious extragalactic radio signals. Revealing their origin is one of the central foci in modern astronomy. Previous studies suggest that occurrence rates of non-repeating and repeating FRBs could be controlled by the cosmic stellar-mass density (CSMD) and star formation-rate density (CSFRD), respectively. The Square Kilometre Array (SKA) is one of the best future instruments to address this subject due to its high sensitivity and high-angular resolution. Here, we predict the number of FRBs to be detected with the SKA. In contrast to previous predictions, we estimate the detections of non-repeating and repeating FRBs separately, based on latest observational constraints on their physical properties including the spectral indices, FRB luminosity functions, and their redshift evolutions. We consider two cases of redshift evolution of FRB luminosity functions following either the CSMD or CSFRD. At $z\gtrsim2$, $z\gtrsim6$ and $z\gtrsim10$, non-repeating FRBs will be detected with the SKA at a rate of $\sim10^{4}$, $\sim10^{2}$, and $\sim10$ (sky$^{-1}$ day$^{-1}$), respectively, if their luminosity function follows the CSMD evolution. At $z\gtrsim1$, $z\gtrsim2$, and $z\gtrsim4$, sources of repeating FRBs will be detected at a rate of $\sim10^{3}$, $\sim10^{2}$, and $\lesssim10$ (sky$^{-1}$ day$^{-1}$), respectively, assuming that the redshift evolution of their luminosity function is scaled with the CSFRD. These numbers could change by about one order of magnitude depending on the assumptions on the CSMD and CSFRD. In all cases, abundant FRBs will be detected by the SKA, which will further constrain the luminosity functions and number density evolutions.

30 citations

Journal ArticleDOI
TL;DR: In this article, a star formation change parameter, SFRF$(5Myr/SFR$(800Myr), is defined, which is the ratio of the SFR averaged within the last 5 Myr to the Sfr averaged within 800 Myr.
Abstract: To investigate the variability of the star formation rate (SFR) of galaxies, we define a star formation change parameter, SFR$_{\rm 5Myr}$/SFR$_{\rm 800Myr}$ which is the ratio of the SFR averaged within the last 5 Myr to the SFR averaged within the last 800 Myr. We show that this parameter can be determined from a combination of H$\alpha$ emission and H$\delta$ absorption, plus the 4000 A break, with an uncertainty of $\sim$0.07 dex for star-forming galaxies. We then apply this estimator to MaNGA galaxies, both globally within Re and within radial annuli. We find that galaxies with higher global SFR$_{\rm 5Myr}$/SFR$_{\rm 800Myr}$ appear to have higher SFR$_{\rm 5Myr}$/SFR$_{\rm 800Myr}$ at all galactic radii, i.e. that galaxies with a recent temporal enhancement in overall SFR have enhanced star formation at all galactic radii. The dispersion of the SFR$_{\rm 5Myr}$/SFR$_{\rm 800Myr}$ at a given relative galactic radius and a given stellar mass decreases with the (indirectly inferred) gas depletion time: locations with short gas depletion time appear to undergo bigger variations in their star-formation rates on Gyr or less timescales. In Wang et al. (2019) we showed that the dispersion in star-formation rate surface densities $\Sigma_{\rm SFR}$ in the galaxy population appears to be inversely correlated with the inferred gas depletion timescale and interpreted this in terms of the dynamical response of a gas-regulator system to changes in the gas inflow rate. In this paper, we can now prove directly with SFR$_{\rm 5Myr}$/SFR$_{\rm 800Myr}$ that these effects are indeed due to genuine temporal variations in the SFR of individual galaxies on timescales between $10^7$ and $10^9$ years rather than possibly reflecting intrinsic, non-temporal, differences between different galaxies.

17 citations


Cites background from "Infrared luminosity functions based..."

  • ...…galaxy population also known as the cosmic evolution of the star formation rate density (SFRD), is well established up to redshift of ∼9 (e.g. Lilly et al. 1996; Schiminovich et al. 2005; Bouwens et al. 2011, 2014; Madau & Dickinson 2014; Hagen et al. 2015; Alavi et al. 2016; Goto et al. 2019)....

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References
More filters
Journal ArticleDOI
TL;DR: In this paper, a review is presented on the broad patterns in the star formation properties of galaxies along the Hubble sequence, and their implications for understanding galaxy evolution and the physical processes that drive the evolution.
Abstract: Observations of star formation rates (SFRs) in galaxies provide vital clues to the physical nature of the Hubble sequence, and are key probes of the evolutionary properties of galaxies. The focus of this review is on the broad patterns in the star formation properties of galaxies along the Hubble sequence, and their implications for understanding galaxy evolution and the physical processes that drive the evolution. Star formation in the disks and nuclear regions of galaxies are reviewed separately, then discussed within a common interpretive framework. The diagnostic methods used to measure SFRs are also reviewed, and a self-consistent set of SFR calibrations is presented as an aid to workers in the field.

553 citations


"Infrared luminosity functions based..." refers methods in this paper

  • ...4.4 Total IR Luminosity density, ΩIR Using LFs in previous sections, we next compute the IR luminosity density, to estimate the cosmic star formation density (Kennicutt 1998)....

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Journal ArticleDOI
TL;DR: In this paper, the authors used a 24?m-selected sample containing more than 8000 sources to study the evolution of star-forming galaxies in the redshift range from z = 0 to z ~ 3.
Abstract: We use a 24 ?m-selected sample containing more than 8000 sources to study the evolution of star-forming galaxies in the redshift range from z = 0 to z ~ 3. We obtain photometric redshifts for most of the sources in our survey using a method based on empirically built templates spanning from ultraviolet to mid-infrared wavelengths. The accuracy of these redshifts is better than 10% for 80% of the sample. The derived redshift distribution of the sources detected by our survey peaks at around z = 0.6-1.0 (the location of the peak being affected by cosmic variance) and decays monotonically from z ~ 1 to z ~ 3. We have fitted infrared luminosity functions in several redshift bins in the range 0 1011 L?) to the total SFR density increases steadily from z ~ 0 up to z ~ 2.5, forming at least half of the newly born stars by z ~ 1.5. Ultraluminous infrared galaxies (LTIR > 1012 L?) play a rapidly increasing role for z 1.3.

504 citations


"Infrared luminosity functions based..." refers background in this paper

  • ...The 12µm luminosity L12µm) is also known to correlate well with the TIR luminosity (Spinoglio et al. 1995; Pérez-González et al. 2005)....

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  • ...Previous work also found a stronger evolution in luminosity than in density (Pérez-González et al. 2005; Le Floc’h et al. 2005)....

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  • ...L12µm is also reported to correlate with LTIR (Chary & Elbaz 2001; Pérez-González et al. 2005)....

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Journal ArticleDOI
TL;DR: In this article, the authors present results from the deep Herschel-Photodetector Array Camera and Spectrometer (PACS) far-infrared blank field extragalactic survey, obtained by combining observations of the Great Observatories Origins Deep Survey (GOODS) fields from the PACS Evolutionary Probe (PEP) and GOODS-Herschel key programmes.
Abstract: We present results from the deepest Herschel-Photodetector Array Camera and Spectrometer (PACS) far-infrared blank field extragalactic survey, obtained by combining observations of the Great Observatories Origins Deep Survey (GOODS) fields from the PACS Evolutionary Probe (PEP) and GOODS-Herschel key programmes. We describe data reduction and theconstruction of images and catalogues. In the deepest parts of the GOODS-S field, the catalogues reach 3σ depths of 0.9, 0.6 and 1.3 mJy at 70, 100 and 160 μm, respectively, and resolve ~75% of the cosmic infrared background at 100 μm and 160 μm into individually detected sources. We use these data to estimate the PACS confusion noise, to derive the PACS number counts down to unprecedented depths, and to determine the infrared luminosity function of galaxies down to L_(IR) = 10^(11) L⊙ at z ~ 1 and L_(IR) = 10^(12) L⊙ at z ~ 2, respectively. For the infrared luminosity function of galaxies, our deep Herschel far-infrared observations are fundamental because they provide more accurate infrared luminosity estimates than those previously obtained from mid-infrared observations. Maps and source catalogues (>3σ) are now publicly released. Combined with the large wealth of multi-wavelength data available for the GOODS fields, these data provide a powerful new tool for studying galaxy evolution over a broad range of redshifts.

483 citations

Journal ArticleDOI
Carlotta Gruppioni1, Francesca Pozzi2, Giulia Rodighiero3, Ivan Delvecchio2, S. Berta4, Lucia Pozzetti1, G. Zamorani1, P. Andreani, Alessandro Cimatti2, O. Ilbert5, E. Le Floc'h, Dieter Lutz4, Benjamin Magnelli4, Lucia Marchetti6, Lucia Marchetti3, Pierluigi Monaco7, Raanan Nordon4, Seb Oliver8, P. Popesso4, L. Riguccini, Isaac Roseboom8, Isaac Roseboom9, David J. Rosario4, Mark Sargent, Mattia Vaccari3, Mattia Vaccari10, Bruno Altieri, H. Aussel, Ángel Bongiovanni11, J. Cepa11, Emanuele Daddi, H. Dominguez-Sanchez11, H. Dominguez-Sanchez1, D. Elbaz, N. M. Foerster Schreiber4, R. Genzel4, Alvaro Iribarrem12, M. Magliocchetti1, Roberto Maiolino13, Albrecht Poglitsch4, A. M. Pérez García, M. Sánchez-Portal, Eckhard Sturm4, Linda J. Tacconi4, Ivan Valtchanov, Alexandre Amblard14, V. Arumugam9, M. Bethermin, James J. Bock15, James J. Bock16, A. Boselli5, V. Buat5, Denis Burgarella5, N. Castro-Rodríguez11, N. Castro-Rodríguez17, Antonio Cava18, P. Chanial, David L. Clements19, A. Conley20, Asantha Cooray15, Asantha Cooray21, C. D. Dowell15, C. D. Dowell16, Eli Dwek22, Stephen Anthony Eales23, Alberto Franceschini3, Jason Glenn20, Matthew Joseph Griffin23, Evanthia Hatziminaoglou, Edo Ibar24, K. G. Isaak25, Rob Ivison24, Rob Ivison9, Guilaine Lagache26, Louis Levenson15, Louis Levenson16, Nanyao Y. Lu15, S. C. Madden, Bruno Maffei27, G. Mainetti3, H. T. Nguyen15, H. T. Nguyen16, B. O'Halloran19, M. J. Page28, P. Panuzzo, Andreas Papageorgiou23, Chris Pearson29, Chris Pearson30, Ismael Perez-Fournon17, Ismael Perez-Fournon11, Michael Pohlen23, Dimitra Rigopoulou30, Dimitra Rigopoulou31, Michael Rowan-Robinson19, Benjamin L. Schulz15, Douglas Scott32, Nick Seymour33, Nick Seymour28, D. L. Shupe15, Anthony J. Smith8, Jamie Stevens34, M. Symeonidis28, Markos Trichas35, K. E. Tugwell28, L. Vigroux36, Lian-Tao Wang8, G. Wright24, C. K. Xu15, Michael Zemcov15, Michael Zemcov16, S. Bardelli1, M. Carollo37, Thierry Contini38, O. Le Fevre5, Simon J. Lilly37, Vincenzo Mainieri, Alvio Renzini1, Marco Scodeggio1, E. Zucca1 
TL;DR: In this article, the authors exploit the deep and extended far-IR data sets (at 70, 100 and 160 μm) of the GPS PACS Evolutionary Probe (PEP) Survey, in combination with the Herschel Multi-tiered Extragalactic Survey data at 250, 350 and 500 μm, to derive the evolution of the rest-frame 35-, 60-, 90- and total infrared luminosity functions (LFs) up to z ∼ 4.
Abstract: We exploit the deep and extended far-IR data sets (at 70, 100 and 160 μm) of the Herschel Guaranteed Time Observation (GTO) PACS Evolutionary Probe (PEP) Survey, in combination with the Herschel Multi-tiered Extragalactic Survey data at 250, 350 and 500 μm, to derive the evolution of the rest-frame 35-, 60-, 90- and total infrared (IR) luminosity functions (LFs) up to z ∼ 4. We detect very strong luminosity evolution for the total IR LF (LIR ∝ (1 + z)3.55 ± 0.10 up to z ∼ 2, and ∝ (1 + z)1.62 ± 0.51 at 2 < z ≲ 4) combined with a density evolution (∝(1 + z)−0.57 ± 0.22 up to z ∼ 1 and ∝ (1 + z)−3.92 ± 0.34 at 1 < z ≲ 4). In agreement with previous findings, the IR luminosity density (ρIR) increases steeply to z ∼ 1, then flattens between z ∼ 1 and z ∼ 3 to decrease at z ≳ 3. Galaxies with different spectral energy distributions, masses and specific star formation rates (SFRs) evolve in very different ways and this large and deep statistical sample is the first one allowing us to separately study the different evolutionary behaviours of the individual IR populations contributing to ρIR. Galaxies occupying the well-established SFR–stellar mass main sequence (MS) are found to dominate both the total IR LF and ρIR at all redshifts, with the contribution from off-MS sources (≥0.6 dex above MS) being nearly constant (∼20 per cent of the total ρIR) and showing no significant signs of increase with increasing z over the whole 0.8 < z < 2.2 range. Sources with mass in the range 10 ≤ log(M/M⊙) ≤ 11 are found to dominate the total IR LF, with more massive galaxies prevailing at the bright end of the high-z (≳2) LF. A two-fold evolutionary scheme for IR galaxies is envisaged: on the one hand, a starburst-dominated phase in which the Super Massive Black Holes (SMBH) grows and is obscured by dust (possibly triggered by a major merging event), is followed by an AGN-dominated phase, then evolving towards a local elliptical. On the other hand, moderately star-forming galaxies containing a low-luminosity AGN have various properties suggesting they are good candidates for systems in a transition phase preceding the formation of steady spiral galaxies.

461 citations


"Infrared luminosity functions based..." refers result in this paper

  • ...This may be qualitatively consistent with previous reports by Herschel that the dust attenuation peaks and declines at z>1.2 (Gruppioni et al. 2013; Burgarella et al. 2013)....

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Journal ArticleDOI
TL;DR: In this paper, the authors measured mid-IR spectroscopic redshifts and place constraints on the contribution from star formation and AGN activity to the mid IR emission, finding that the hot dust continuum from an AGN contributes at most 30% of the midIR luminosity.
Abstract: We present deep mid-IR spectroscopy with Spitzer of 13 SMGs in the GOODS-N field. We find strong PAH emission in all of our targets, which allows us to measure mid-IR spectroscopic redshifts and place constraints on the contribution from star formation and AGN activity to the mid-IR emission. In the high-S/N composite spectrum, we find that the hot dust continuum from an AGN contributes at most 30% of the mid-IR luminosity. Individually, only 2/13 SMGs have continuum emission dominating the mid-IR luminosity; one of these SMGs, C1, remains undetected in the deep X-ray images but shows a steeply rising continuum in the mid-IR indicative of a Compton-thick AGN. We find that the mid-IR properties of SMGs are distinct from those of 24 μm-selected ULIRGs at z ~ 2; the former are predominantly dominated by star formation, while the latter are a more heterogeneous sample with many showing significant AGN activity. We fit the IRS spectrum and the mid-IR to radio photometry of SMGs with template SEDs to determine the best estimate of the total IR luminosity from star formation. While many SMGs contain an AGN as evinced by their X-ray properties, our multiwavelength analysis shows that the total IR luminosity, LIR, in SMGs is dominated by star formation. We find that high-redshift SMGs lie on the relation between LIR and LPAH ,6.2 (or LPAH ,7.7 or LPAH ,11.3) that has been established for local starburst galaxies. This suggests that PAH luminosity can be used as a proxy for the SFR in SMGs. SMGs are consistent with being a short-lived cool phase in a massive merger where the AGN does not appear to have become strong enough to heat the dust and dominate the mid- or far-IR emission.

440 citations


"Infrared luminosity functions based..." refers background in this paper

  • ...Pope et al. (2008) showed that z ∼2 sub-millimeter galaxies lie on the relation between LTIR and LPAH,7.7 that has been established for local starburst galaxies....

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Related Papers (5)
Frequently Asked Questions (6)
Q1. What are the contributions mentioned in the paper "Infrared luminosity functions based on 18 mid-infrared bands: revealing cosmic star formation history with akari and hyper suprime-cam*" ?

Combined with the accurate mid-IR luminosity measurement, the authors constructed mid-IR LFs, and thereby performed a census of dust-obscured CSFH in the entire AKARI NEP field. 

The L18W flux (Matsuhara et al. 2006) are used to apply the 1/Vmax method, because it is a wide, sensitive filter (but using the L15 flux limit does not change their main results). 

Mid-infrared (mid-IR) is one of the less explored wavelengths due to the earth’s atmosphere, and difficulties in developing sensitive detectors. 

Uncertainties of the LF values includefluctuations in the number of sources in each luminosity bin, the photometric redshift uncertainties, the k-correction uncertainties, and the flux errors. 

It has the largest FoV among optical cameras on 8m-class telescopes, and can cover the AKARI NEP wide field (5.4 deg2) with only 4 FoV (Fig.1). 

even with AKARI’s sensitivity, the observation might not be deep enough to reliably measure the faint-end slope of 12µm LFs, possibly because 12µm does not contain as luminous emission lines as in the case of 8µm.