The Astrophysical Journal Supplement Series, 197:35 (39pp), 2011 December doi:10.1088/0067-0049/197/2/35
C
2011. The American Astronomical Society. All rights reserved. Printed in the U.S.A.
CANDELS: THE COSMIC ASSEMBLY NEAR-INFRARED DEEP EXTRAGALACTIC LEGACY SURVEY
Norman A. Grogin
1
, Dale D. Kocevski
2
, S. M. Faber
2
, Henry C. Ferguson
1
, Anton M. Koekemoer
1
, Adam G. Riess
3
,
Viviana Acquaviva
4
, David M. Alexander
5
, Omar Almaini
6
, Matthew L. N. Ashby
7
, Marco Barden
8
, Eric F. Bell
9
,
Fr
´
ed
´
eric Bournaud
10
, Thomas M. Brown
1
, Karina I. Caputi
11
, Stefano Casertano
1
, Paolo Cassata
12
,
Marco Castellano
13
, Peter Challis
14
, Ranga-Ram Chary
15
, Edmond Cheung
2
, Michele Cirasuolo
16
,
Christopher J. Conselice
6
, Asantha Roshan Cooray
17
, Darren J. Croton
18
, Emanuele Daddi
10
, Tomas Dahlen
1
,
Romeel Dav
´
e
19
,Du
´
ılia F. de Mello
20,21
, Avishai Dekel
22
, Mark Dickinson
23
, Timothy Dolch
3
, Jennifer L. Donley
1
,
James S. Dunlop
11
, Aaron A. Dutton
24
, David Elbaz
10
, Giovanni G. Fazio
7
, Alexei V. Filippenko
25
,
Steven L. Finkelstein
26
, Adriano Fontana
13
, Jonathan P. Gardner
20
, Peter M. Garnavich
27
, Eric Gawiser
4
,
Mauro Giavalisco
12
, Andrea Grazian
13
, Yicheng Guo
12
, Nimish P. Hathi
28
, Boris H
¨
aussler
6
, Philip F. Hopkins
25
,
Jia-Sheng Huang
29
, Kuang-Han Huang
1,3
, Saurabh W. Jha
4
, Jeyhan S. Kartaltepe
23
, Robert P. Kirshner
7
,
David C. Koo
2
, Kamson Lai
2
, Kyoung-Soo Lee
30
, Weidong Li
25
, Jennifer M. Lotz
1
, Ray A. Lucas
1
, Piero Madau
2
,
Patrick J. McCarthy
28
, Elizabeth J. McGrath
2
, Daniel H. McIntosh
31
,RossJ.McLure
11
, Bahram Mobasher
32
,
Leonidas A. Moustakas
33
, Mark Mozena
2
, Kirpal Nandra
34
, Jeffrey A. Newman
35
, Sami-Matias Niemi
1
,
Kai G. Noeske
1
, Casey J. Papovich
26
, Laura Pentericci
13
, Alexandra Pope
12
, Joel R. Primack
36
, Abhijith Rajan
1
,
Swara Ravindranath
37
, Naveen A. Reddy
32
, Alvio Renzini
38
, Hans-Walter Rix
39
, Aday R. Robaina
40
, Steven
A. Rodney
3
, David J. Rosario
34
, Piero Rosati
41
, Sara Salimbeni
12
, Claudia Scarlata
42
, Brian Siana
32
, Luc Simard
43
,
Joseph Smidt
17
, Rachel S. Somerville
4
, Hyron Spinrad
25
, Amber N. Straughn
20
, Louis-Gregory Strolger
44
,
Olivia Telford
35
, Harry I. Teplitz
45
, Jonathan R. Trump
2
, Arjen van der Wel
39
, Carolin Villforth
1
,
Risa H. Wechsler
46
,BenjaminJ.Weiner
19
, Tommy Wiklind
47
, Vivienne Wild
11
, Grant Wilson
12
, Stijn Wuyts
34
,
Hao-Jing Yan
48
,andMinS.Yun
12
1
Space Telescope Science Institute, Baltimore, MD, USA
2
UCO/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA, USA
3
Department of Physics and Astronomy, The Johns Hopkins University, Baltimore, MD, USA
4
Department of Physics and Astronomy, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
5
Department of Physics, Durham University, Durham, UK
6
The School of Physics and Astronomy, University of Nottingham, Nottingham, UK
7
Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
8
Institute of Astro- and Particle Physics, University of Innsbruck, Innsbruck, Austria
9
Department of Astronomy, University of Michigan, Ann Arbor, MI, USA
10
CEA-Saclay/DSM/DAPNIA/Service d’Astrophysique, Gif-sur-Yvette, France
11
Institute for Astronomy, University of Edinburgh, Edinburgh, UK
12
Department of Astronomy, University of Massachusetts, Amherst, MA, USA
13
INAF, Osservatorio Astronomico di Roma, Rome, Italy
14
Harvard College Observatory, Cambridge, MA, USA
15
U.S. Planck Data Center, California Institute of Technology, Pasadena, CA, USA
16
UK Astronomy Technology Centre, Edinburgh, UK
17
Department of Physics and Astronomy, University of California, Irvine, CA, USA
18
Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, Australia
19
Department of Astronomy, University of Arizona, Tucson, AZ, USA
20
Astrophysics Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
21
Physics Department, The Catholic University of America, Washington, DC, USA
22
Racah Institute of Physics, The Hebrew University, Jerusalem, Israel
23
National Optical Astronomy Observatories, Tucson, AZ, USA
24
Department of Physics and Astronomy, University of Victoria, Victoria, BC, Canada
25
Department of Astronomy, University of California, Berkeley, CA, USA
26
Department of Physics and Astronomy, Texas A&M University, College Station, TX, USA
27
Department of Physics, University of Notre Dame, Notre Dame, IN, USA
28
Carnegie Observatories, Pasadena, CA, USA
29
Smithsonian Institution Astrophysical Observatory, Cambridge, MA, USA
30
Yale Center for Astronomy and Astrophysics, New Haven, CT, USA
31
Department of Physics, University of Missouri, Kansas City, MO, USA
32
Department of Physics and Astronomy, University of California, Riverside, CA, USA
33
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
34
Max Planck Institute for Extraterrestrial Physics, Garching, Germany
35
Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA
36
Department of Physics, University of California, Santa Cruz, CA, USA
37
Inter-University Centre for Astronomy and Astrophysics, Pune, India
38
Osservatorio Astronomico di Padova, Padua, Italy
39
Max-Planck-Institut f
¨
ur Astronomie, Heidelberg, Germany
40
Institut de Ciencies del Cosmos, University of Barcelona, Barcelona, Spain
41
European Southern Observatory, Garching, Germany
42
Minnesota Institute of Astrophysics and School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, USA
43
National Research Council of Canada, Herzberg Institute of Astrophysics, Victoria, BC, Canada
44
Department of Physics and Astronomy, Western Kentucky University, Bowling Green, KY, USA
45
Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA, USA
46
Department of Physics, Stanford University, Stanford, CA, USA
1
The Astrophysical Journal Supplement Series, 197:35 (39pp), 2011 December Grogin et al.
47
ALMA/ESO, Santiago, Chile
48
Department of Physics and Astronomy, University of Missouri, Columbia, MO, USA
Received 2011 May 18; accepted 2011 November 5; published 2011 December 6
ABSTRACT
The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) is designed to document
the first third of galactic evolution, over the approximate redshift (z) range 8–1.5. It will image >250,000
distant galaxies using three separate cameras on the Hubble Space Telescope, from the mid-ultraviolet to the
near-infrared, and will find and measure Type Ia supernovae at z>1.5 to test their accuracy as standardizable
candles for cosmology. Five premier multi-wavelength sky regions are selected, each with extensive ancillary data.
The use of five widely separated fields mitigates cosmic variance and yields statistically robust and complete
samples of galaxies down to a stellar mass of 10
9
M
to z ≈ 2, reaching the knee of the ultraviolet luminosity
function of galaxies to z ≈ 8. The survey covers approximately 800 arcmin
2
and is divided into two parts. The
CANDELS/Deep survey (5σ point-source limit H = 27.7 mag) covers ∼125 arcmin
2
within Great Observatories
Origins Deep Survey (GOODS)-N and GOODS-S. The CANDELS/Wide survey includes GOODS and three
additional fields (Extended Groth Strip, COSMOS, and Ultra-deep Survey) and covers the full area to a 5σ point-
source limit of H 27.0 mag. Together with the Hubble Ultra Deep Fields, the strategy creates a three-tiered
“wedding-cake” approach that has proven efficientfor extragalacticsurveys. Data from thesurvey are nonproprietary
and are useful for a wide variety of science investigations. In this paper, we describe the basic motivations for the
survey, the CANDELS team science goals and the resulting observational requirements, the field selection and
geometry, and the observing design. The Hubble data processing and products are described in a companion paper.
Key words: cosmology: observations – galaxies: high-redshift
Online-only material: color figures
1. INTRODUCTION
During the past decade, the Hubble Space Telescope (HST)
and other telescopes have fueled a series of remarkable discov-
eries in cosmology that would have seemed impossible only a
few short years ago. Galaxies are now routinely found when
the universe was only 5% of its current age and before 99%
of present-day stars had formed. Distant Type Ia supernovae
(SNe Ia) showed that the expansion of the universe was decel-
erating for the first ∼9 Gyr, followed by acceleration due to
a mysterious “dark energy” whose nature remains completely
unknown. The troika of Hubble, Spitzer, and Chandra revealed
a complex interplay between galaxy mergers, star formation,
and black holes (BHs) over cosmic time that spawned the new
concept of galaxy/BH “co-evolution.”
This rapid progress can be attributed in part to an unprece-
dented degree of coordination between observatories across the
electromagnetic spectrum in which a few small regions of sky
were observed as deeply as possible at all accessible wave-
lengths. Such regions have become “magnet” regions whose
total scientific value now far exceeds that of their individual
surveys.
The Great Observatories Origins Deep Survey (GOODS;
Giavalisco et al. 2004) possesses the deepest dataonthesky from
virtually every telescope: Hubble, Spitzer, Chandra, Herschel,
the Very Large Array (VLA), and many other observatories
both in space and on the ground. However, the GOODS-
North and GOODS-South fields together subtend only about
300 arcmin
2
, which makes them too small for science goals
involving rare and/or massive objects. Samples are limited, and
count fluctuations tend to be large owing to the high intrinsic
bias and cosmic variance (CV) of massive halos. GOODS HST
images furthermore probe only optical wavelengths, which are
strongly biased toward ongoing star-forming regions and miss
the older stars beyond redshift z ≈ 1.3.
With a survey speed gain of a factor of ∼30 over NICMOS
for galaxy imaging, the new Wide Field Camera 3 (WFC3)/IR
(infrared) camera enables much more ambitious near-IR surveys
than were previously possible with Hubble. For example, the
single-filter GOODS NICMOS Survey (GNS; Conselice et al.
2011a) required 180 HST orbits to survey 45 arcmin
2
to a
limiting magnitude of H
AB
≈ 26.5. By comparison, WFC3/IR
enables a two-filter survey of five times the GNS area to
limiting magnitudes of H
AB
27.1 and J
AB
27.0—using
half the orbits required for the GNS. The capacity for longer-
wavelength and larger-area surveys now allows Hubble to follow
galaxies well into the reionization era; measure spectra and
light curves for SNe Ia in the deceleration era; and measure
rest-frame optical shapes and sizes of galaxies at a time
(z ≈ 2) when cosmic luminosity peaked for both star formation
and active galactic nuclei (AGNs), and when the Hubble
sequence was starting to take shape. The power of WFC3/IR
imaging for distant galaxies is demonstrated in Figure 1, which
compares GOODS-depth four-orbit F775W images from the
Hubble Advanced Camera for Surveys (ACS) with two-orbit
images from WFC3/IR. Regions with red colors due to heavy
dust or old stars leap out with the WFC3/IR, in many cases
leading to a new interpretation of the object.
Given the power of this gain, there is strong motiva-
tion to extend deep-field WFC3/IR imaging beyond the
GOODS regions to larger areas. Three well-studied regions in
the sky are natural candidates for this extension: COSMOS
(Scoville et al. 2007), the Extended Groth Strip (EGS; Davis
et al. 2007), and the UKIRT Infrared Deep Sky Survey
(UKIDSS) Ultra-deep Survey field (UDS; Lawrence et al. 2007;
Cirasuolo et al. 2007). These fields are larger than GOODS
and already have high-quality (though generally shallower)
multi-wavelength data. Establishing multiple, statistically in-
dependent WFC3/IR regions over the sky would also minimize
CV and facilitate follow-up observations by ground-based tele-
scopes.
Several teams responded to the Hubble Multi-Cycle Treasury
(MCT) Program Call for Proposals with programs targeting
high-latitude fields using WFC3/IR to study galaxy evolution.
2
The Astrophysical Journal Supplement Series, 197:35 (39pp), 2011 December Grogin et al.
sregreM neddiHsdiorehpS tnegremE Emergent Disks
F775W (i) F160W (H)
Figure 1. Four-orbit images of HUDF galaxies from ACS vs. two-orbit images from WFC3/IR illustrate the importance of WFC3/IR for studying distant galaxy
structure. WFC3/IR unveils the true stellar mass distributions of these galaxies unbiased by young stars and obscuring dust. The new structures that emerge in many
cases inspire revised interpretations of these objects, as indicated.
Two teams targeted the above five fields and also proposed
to find high-redshift SNe Ia to improve constraints on cosmic
deceleration and acceleration. The program led by Ferguson
proposed to observe the full 300 arcmin
2
of the GOODS fields
to uniform depth in YJH. This proposal contained time for both
spectroscopic and photometric SN Ia follow-up observations
and took advantage of GOODS-N in the Hubble continuous
viewing zone (CVZ) to obtain far-ultraviolet (UV) images on
the day side of the orbit when the sky is too bright for broadband
IR imaging. The second program, led by Faber, proposed
imaging half the area of the two GOODS fields to about twice
the depth of the Ferguson program and also added shallower
imaging over ∼1000 arcmin
2
in EGS, COSMOS, UDS, and
the Extended Chandra Deep Field South. ACS parallels were
included to broaden total wavelength coverage, deepen existing
ACS mosaics, and add a new ACS mosaic in UDS, where none
existed. SN Ia searches were also included, but the proposal
did not contain time for SN follow-up observations, nor did it
feature UV imaging.
The Hubble time-allocation committee (TAC) saw merit in
both proposals and charged the two teams to craft a joint
program to retain the best features of bothprograms yet fit within
902 orbits. This was challenging, owing to four requirements
mandated by the TAC: (1) visit all WFC3/IR tiles at least twice
with the proper cadence for finding SNe Ia (∼60 days; this
severely restricts the range of allowable dates and ORIENTs
in each field), (2) discriminate SNe Ia candidates from other
interlopers (requires very specific multi-wavelength data at
each visit), (3) put as many ACS parallels as possible on top
of each WFC3/IR tile (further restricting Hubble observation
dates and ORIENTs), and (4) maximize the overlap of Hubble
data on top of existing ancillary data (compatible dates and
ORIENTs become vanishingly small). Further complicating
matters, the Hubble TAC also approved the CLASH program
on clusters of galaxies by Postman et al. (GO-12065), including
SN discovery and follow-up observations, with the mandate
that it be coordinated with the SN Ia program here. The SN
portions of both proposals were consolidated under a separate
program by Riess et al. (GO-12099), and the SN Ia follow-
up orbits from both programs were pooled. Our program takes
prime responsibility for the highest-redshift SNe (z>1.3),
while CLASH addresses SNe at lower redshifts.
The resulting observing program, now entitled the Cosmic
Assembly Near-infrared Deep Extragalactic Legacy Survey
(CANDELS), targets five distinct fields (GOODS-N, GOODS-
S, EGS, UDS, and COSMOS) at two distinct depths. Hence-
forth, we will refer to the deep portion of the survey as
“CANDELS/Deep” and the shallow portion as
“CANDELS/Wide.” Adding in the Hubble Ultra Deep Fields
(HUDF) makes a three-tiered “wedding-cake” approach, which
has proven to be very effective with extragalactic surveys.
CANDELS/Wide has exposures in all five CANDELS fields,
while CANDELS/Deep is only in GOODS-S and GOODS-N.
The outline of this paper is as follows. We first provide a
brief synopsis of the survey in Section 2. We follow in Section 3
with a detailed description of the major science goals along with
their corresponding observational requirements that CANDELS
addresses. We synthesize the combined observing requirements
in Section 4 with regard to facets of our survey. A description
of the particular survey fields and an overview of existing
ancillary data are provided in Section 5. Section 6 describes the
detailed observing plan, including the schedule of observations.
Section 7 summarizes the paper, along with a brief description
of the CANDELS data reduction and data products; a much
more complete description is given by Koekemoer et al. (2011),
which is intended to be read as a companion paper to this one.
Where needed, we adopt the following cosmological param-
eters: H
0
= 70 km s
−1
Mpc
−1
; Ω
tot
, Ω
Λ
, Ω
m
= 1, 0.3, 0.7 (re-
spectively), though numbers used in individual calculations may
differ slightly from these values. All magnitudes are expressed
in the AB system (Oke & Gunn 1983).
2. CANDELS SYNOPSIS
Table 1 provides a convenient summary of the survey, listing
the various filters and corresponding total exposure within each
field, along with each field’s coordinates and dimensions. The
Hubble data are of several different types, including images
from WFC3/IR and WFC3/UVIS (both UV and optical) plus
extensive ACS parallel exposures. Extra grism and direct images
will also be included for SN Ia follow-up observations (see
Section 3.5), but their exposure lengths and locations are not
pre-planned. They are not included in Table 1. In perusing the
table, it may be useful to look ahead at Figures 12–16, which
illustrate the layout of exposures on the sky.
The three purely Wide fields (UDS, COSMOS, and EGS,
Figures 14–16) consist of a contiguous mosaic of overlapping
WFC3/IR tiles (shown in blue) along with a contemporaneous
mosaic of ACS parallel exposures (shown in magenta). The
two cameras are offset by ∼6
, but overlap between them is
maximized by choosing the appropriate telescope roll angle.
The Wide exposures are taken over the course of two HST orbits,
with exposure time allocated roughly 2:1 between F160W and
F125W. The observations are scheduled in two visits separated
by ∼52 days in order to find SNe Ia. The stacked exposure time
is effectively twice as long in ACS (i.e., four orbits) on account
of its larger field of view, and its time is divided roughly 2:1
between F814W and F606W. In the small region where the
WFC3/IR lacks ACS parallel overlap, we sacrifice WFC3/IR
3
The Astrophysical Journal Supplement Series, 197:35 (39pp), 2011 December Grogin et al.
Tab le 1
CANDELS at a Glance
Field Coordinates Tier WFC3/IR Tiling HST Orbits/Tile IR Filters
a
UV/Optical Filters
b
GOODS-N 189.228621, + 62.238572 Deep ∼3 × 5 ∼13 YJH UV,UI(WVz)
GOODS-N 189.228621, + 62.238572 Wide 2 @ ∼2 × 4 ∼3 YJH Iz(W)
GOODS-S 53.122751, −27.805089 Deep ∼3 × 5 ∼13 YJH I(WVz)
GOODS-S 53.122751, −27.805089 Wide ∼2 × 4 ∼3 YJH Iz(W)
COSMOS 150.116321, + 2.2009731 Wide 4 × 11 ∼2 JH VI(W)
EGS 214.825000, + 52.825000 Wide 3 × 15 ∼2 JH VI(W)
UDS 34.406250, −5.2000000 Wide 4 × 11 ∼2 JH VI(W)
Notes.
a
WFC3/IR filters Y ≡ F105W, J ≡ F125W, and H ≡ F160W.
b
WFC3/UVIS filters UV ≡ F275W, W ≡ F350LP; ACS filters V ≡ F606W, I ≡ F814W, z ≡ F850LP. Parenthesized filters indicate incomplete and/or relatively
shallow coverage of the indicated field.
depth to obtain a short exposure in the WFC3/UVIS “white-
light” filter F350LP for SN-type discrimination.
The GOODS fields contain both Deep and Wide exposure
regions. In addition, GOODS-S also contains the Early Release
Science (ERS) data (Windhorst et al. 2011), which we have
taken into account in our planning and include in the CANDELS
quoted areas because its filters and exposure times match well
to ours (see Section 6.2). The two GOODS layouts are shown
in Figures 12 and 13. The Deep portion of each one is a central
region of approximately 3×5WFC3/IR tiles, which is observed
to an effective depth of three orbits in F105W and four orbits
in F125W and F160W. To the north and south lie roughly
rectangular “flanking fields” each covered by 8–9 WFC3/IR
tiles, which are observed using the Wide strategy of two orbits in
J+H. The flanking fields additionally receive an orbit of F105W.
The net result is coverage over most of the GOODS fields to at
least ∼1-orbit depth in YJH, plus deeper coverage in all three
filters within the Deep areas.
Executing the GOODS exposures requires ∼15 visits to each
field, and virtually all J+H orbits are employed in SN Ia search-
ing. The filter layouts at each visit are shown for GOODS-S
in Figures 22 and 23 (detailed visits for GOODS-N have not
yet been finalized). Because the telescope roll angle cannot be
held constant across so many visits, the matching ACS paral-
lel exposures (which are always taken) are distributed around
the region in a complicated way. These parallels are taken in
F606W, F814W, and F850LP according to a complex scheme
explained in Section 6.2. For now, it is sufficient to note that
most of the ACS parallels use F814W, for the purpose of iden-
tifying high-z Lyman break “drop-out” galaxies. Because there
is poor overlap between WFC3/IR exposures and their ACS
parallels during any given epoch, all GOODS J+H orbits in-
clude a short WFC3/UVIS F350LP exposure as noted above for
CANDELS/Wide. Finally, Table 1 also lists special
WFC3/UVIS exposures taken during GOODS-N CVZ opportu-
nities of total duration ∼13 ks in F275W and ∼7 ks in F336W.
Exposure maps of the expected final data in GOODS-S are
shown in Figures 24 and 25, including all previous legacy
exposures in HST broadband filters (the GOODS-N maps in
Figures 27 and 28
are preliminary).
Realizing the full science potential of this extensive but
complex data set will require closely interfacing with many
other ground-based and space-based surveys. Among these we
particularly mention Spitzer Extended Deep Survey (SEDS),
49
the Spitzer Warm Mission Extended Deep Survey, whose deep
49
http://www.cfa.harvard.edu/SEDS
3.6 μm and 4.8 μm data points provide vital stellar masses
(the CANDELS fields are completely embedded within the
SEDS regions). The total database is rich, far richer than our
team can exploit. Because of this, and the Treasury nature of
the CANDELS program, we are moving speedily to process
and make the Hubble data public (for details, see Koekemoer
et al. 2011). The first CANDELS data release occurred on
2011 January 12, 60 days after the first epoch was acquired
in GOODS-S. As a further service to the community, we are
constructing separate Web sites for each CANDELS field to
collect and serve the ancillary data. For further information,
please visit the CANDELS Web site.
50
3. SCIENCE GOALS
The MCT Program was established to address high-impact
science questions that require Hubble observations on a
scale that cannot be accommodated within the standard time-
allocation process. MCT programs are also intended to seed
a wide variety of compelling scientific investigations. Deep
WFC3/IR observations of well-studied fields at high Galactic
latitudes naturally meet these two criteria.
In this section, we outline the CANDELS science goals,
prefixed by a brief discussion in Section 3.1 of the theoretical
tools that are being developed for the CANDELS program. Most
of our investigations of galaxies and AGNs divide naturally into
two epochs. In Section 3.2 (“cosmic dawn”), we discuss studies
of very early galaxies during the reionization era. In Section 3.3
(“cosmic high noon”), we discuss the growth and transformation
of galaxies during the era of peak star formation and AGN
activity. Section 3.4 describes science goals enabled by UV
observations that exploit the GOODS-N CVZ. Section 3.5
describes the use of high-z SNe to constrain the dynamics of
dark energy, measure the evolution of SN rates, and test whether
SNe Ia remain viable as standardizable candles at early epochs.
Finally, Section 3.6 describes science goals enabled by the grism
portion of the program. The complete list of goals is collected
for reference in Table 2. Work is proceeding within the team on
all of these topics.
3.1. Theory Support
Theoretical predictions have been an integral part of the
project’s development since its inception. We have extracted
merger trees from the new Bolshoi N-body simulation (Klypin
et al. 2011), which also track the evolution of sub-halos. We then
50
http://candels.ucolick.org
4
The Astrophysical Journal Supplement Series, 197:35 (39pp), 2011 December Grogin et al.
Tab le 2
CANDELS Primary Scientific Goals
No. Goal
Cosmic Dawn (CD): Formation and early evolution of
galaxies and AGNs
CD1 Improve constraints on the bright end of the galaxy LF at
z ≈ 7and8andmakez ≈ 6 measurements more robust.
Combine with WFC3/IR data on fainter magnitudes to
constrain the UV luminosity density of the universe at the
end of the reionization era
CD2 Constrain star formation rates, ages, metallicities, stellar
masses, and dust contents of galaxies at the end of the
reionization era, z ≈ 6–10. Tighten estimates of the
evolution of stellar mass, dust, and metallicity at z = 4–8 by
combining WFC3 data with very deep Spitzer IRAC
photometry
CD3 Measure fluctuations in the near-IR background light, at
sensitivities sufficiently faint and angular scales sufficiently
large to constrain reionization models
CD4 Use clustering statistics to estimate the dark-halo masses of
high-redshift galaxies with double the area of prior Hubble
surveys
CD5 Search deep WFC3/IR images for AGN dropout candidates
at z>6–7 and constrain the AGN LF
Cosmic High Noon (CN): The peak of star formation and
AGN activity
CN1 Conduct a mass-limited census of galaxies down to
M
∗
= 2 × 10
9
M
at z ≈ 2 and determine redshifts, star
formation rates, and stellar masses from broadband spectral
energy distributions (SEDs). Quantify patterns of star
formation versus stellar mass and other variables and
measure the cosmic-integrated stellar mass and star
formation rates to high accuracy
CN2 Obtain rest-frame optical morphologies and structural
parameters of z ≈ 2 galaxies, including morphological
types, radii, stellar mass surface densities, and quantitative
disk, spheroid, and interaction measures. Use these to
address the relationship between galactic structure, star
formation history, and mass assembly
CN3 Detect galaxy sub-structures and measure their stellar
masses. Use these data to assess disk instabilities, quantify
internal patterns of star formation, and test bulge formation
by clump migration to the centers of galaxies
CN4 Conduct the deepest and most unbiased census yet of active
galaxies at z 2 selected by X-ray, IR, optical spectra, and
optical/NIR variability. Test models for the co-evolution of
black holes and galaxies and triggering mechanisms using
demographic data on host properties, including morphology
and interaction fraction
Ultraviolet Observations (UV): Hot stars at 1 <z<3.5
UV1 Constrain the Lyman continuum escape fraction for
galaxies at z ≈ 2.5
UV2 Identify Lyman break galaxies at z ≈ 2.5 and compare their
properties to higher-z Lyman break galaxy samples
UV3 Estimate the star formation rate in dwarf galaxies to z>1
to test whether dwarf galaxies are “turning on” as the UV
background declines at low redshift
Supernovae (SN): Standardizable candles beyond z ≈ 1
SN1 Test for the evolution of SNe Ia as distance indicators by
observing them at z>1.5, where the effects of dark energy
are expected to be insignificant but the effects of the
evolution of the SN Ia white dwarf progenitor masses ought
to be significant
SN2 Refine constraints on the time variation of the cosmic
equation-of-state parameter, on a path to more than
Tab le 2
(Continued)
No. Goal
doubling the strength of this crucial test of a cosmological
constant by the end of HST’s life
SN3 Measure the SN Ia rate at z ≈ 2 to constrain progenitor
models by detecting the offset between the peak of the
cosmic star formation rate and the peak of the cosmic rate
of SNe Ia
extract light cones that mimic the geometry of the CANDELS
fields, with many realizations of each field in order to study
CV. These light cones are populated with galaxies using several
methods: (1) sub-halo abundance matching, a variant of halo
occupation distribution modeling, in which stellar masses or
luminosities are assigned to (sub-)halos such that the observed
galaxy abundance is reproduced (Behroozi et al. 2010); (2) semi-
analytic models (SAMs), which use simplified recipes to track
the main physical processes of galaxy formation. We are using
three different, independently developed SAM codes, based on
updated versions of the models developed by Somerville et al.
(2008b), Croton et al. (2006), and Lu et al. (2011), that are being
run in the same Bolshoi-based merger trees. This will allow us
to explore the impact of different model assumptions on galaxy
observables.
All three SAM models include treatments of radiative cooling
of gas, star formation, stellar feedback, and stellar population
synthesis. The Somerville and Croton SAMs also include
modeling of BH formation and growth, and so can track AGN
activity. We are developing more detailed and accurate modeling
of the radial sizes of disks and spheroids in the SAMs, using
an approach based on the work of Dutton & van den Bosch
(2009) in the case of the former, and using the recipe based
on mass ratio, orbit parameters, and gas content taken from
merger simulations by Covington et al. (2011) for the latter.
Using simple analytic prescriptions for dust extinction, we will
use the SAMs to create synthetic images based on these mock
catalogs, assuming smooth parameterized light profiles for the
galaxies. A set of mock catalogs, containing physical properties
such as stellar mass and star formation rate (SFR), as well as
observables such as luminosities in all CANDELS bands, will
be released to the public through a queryable database.
51
The
synthetic images will also be made publicly available.
In addition, several team members are pursuing N-body
and hydrodynamic simulations using a variety of approaches.
To complement Bolshoi, Piero Madau is computing Silver
River, a higher-resolution version of his previous N-body
Via Lactea Milky Way simulation. Romeel Dav
´
eisusing
a proprietary version of Gadget-2 to track gas infall, star
formation, and stellar feedback in very high redshift galaxies
(Finlator et al. 2011). Working with multiple teams, Avishai
Dekel is guiding the computation of early disky galaxies at
z ≈ 2 with particular reference to clump formation; early
results were presented in Ceverino et al. (2010). The simulation
efforts make use of a wide range of codes and numerical
techniques, including ART, ENZO, RAMSES, GADGET, and
GASOLINE. Finally, the theory effort includes post-processing
of hydrodynamic simulations with the SUNRISE radiative
transfer code to produce realistic images and spectra, including
the effects of absorption and scattering by dust (Jonsson et al.
51
See, for example, Darren Croton’s Web site at
http://web.me.com/darrencroton/Homepage/Downloads.html.
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