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Subaru/WFIRST Synergies for Cosmology and Galaxy Evolution Collaborators: Peter Capak, Olivier Doré, Jason Rhodes, Shoubaneh Hemmati, Daniel Stern, Judy Cohen, WFIRST Cosmology SIT (http://www.wfirst-hls-cosmology.org) Dan Masters (JPL/California Institute of Technology) Artist’s concept 2017 California Institute of Technology. Government sponsorship acknowledged.

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Page 1: Artist’s concept Subaru/WFIRST Synergies for Cosmology and ... · Subaru/WFIRST Synergies for Cosmology and Galaxy Evolution ... • HSC/PFS could conduct observations that greatly

Subaru/WFIRST Synergies for Cosmology and Galaxy EvolutionCollaborators: Peter Capak, Olivier Doré, Jason Rhodes, Shoubaneh Hemmati, Daniel Stern, Judy Cohen,

WFIRST Cosmology SIT (http://www.wfirst-hls-cosmology.org)

Dan Masters (JPL/California Institute of Technology)

Artist’s concept

ⓒ 2017 California Institute of Technology.Government sponsorship acknowledged.

Page 2: Artist’s concept Subaru/WFIRST Synergies for Cosmology and ... · Subaru/WFIRST Synergies for Cosmology and Galaxy Evolution ... • HSC/PFS could conduct observations that greatly

• WFIRST HLS will measure weak lensing over ~2000 deg2

– Accurate photo-z distributions are critical– NIR-selected WFIRST shear sample à many faint optical

sources• HSC/PFS could conduct observations that greatly

enhance WFIRST cosmology– PFS spectroscopy to calibrate WFIRST photo-zs– HSC complementary imaging observations

• In turn WFIRST would enhance cosmology with Subaru

WFIRST/Subaru cosmology in the 2020s

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WFIRST photometric redshift calibration

• Different approaches possible• Need to know N(z) distribution of ~10-20 tomographic

bins to high accuracy (~0.2%)• Combination of cluster-z (e.g. Newman 2008, Menard et

al. 2013) + “direct” calibration (e.g. Masters et al. 2015) of P(z|C) relation likely

• Independent methods important to validate calibration

Page 4: Artist’s concept Subaru/WFIRST Synergies for Cosmology and ... · Subaru/WFIRST Synergies for Cosmology and Galaxy Evolution ... • HSC/PFS could conduct observations that greatly

Rahman et al. 2015

SDSS galaxy distribution in two colors

Photo-z’s are fundamentally a mapping of galaxy colors to redshiftColor distribution of galaxies to a given depth is limited and measurable

The empirical P(z|C) relationg-

i

g-r

Page 5: Artist’s concept Subaru/WFIRST Synergies for Cosmology and ... · Subaru/WFIRST Synergies for Cosmology and Galaxy Evolution ... • HSC/PFS could conduct observations that greatly

The Self-Organizing Map

Illustration of the SOM (From Carrasco Kind & Brunner 2014)

• The problem of mapping a high-dimensional dataset arises in many fields, and a number of techniques have been developed

• We adopt the widely-used Self-Organizing Map (SOM), or Kohonen Map

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Model of P(z|C)

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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Cell # 8642, x = 17, y = 115Photo-z estimate: 1.186

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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Cell # 8342, x = 17, y = 111Photo-z estimate: 1.298

0.5 1.0 1.5 2.027

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0.5 1.0 1.5 2.0Wavelength (micron)27

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Cell # 2043, x = 18, y = 27Photo-z estimate: 0.760

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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Cell # 8988, x = 63, y = 119Photo-z estimate: 0.595

0.5 1.0 1.5 2.0Wavelength (μm)

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Cell # 6490, x = 40, y = 86Photo-z estimate: 2.364

0.5 1.0 1.5 2.027

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0.5 1.0 1.5 2.027

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Cell # 3051, x = 51, y = 40Photo-z estimate: 0.529

Wavelength (micron)

Median 30-band Photo-z

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0 1 2 3 4 5 6

0.5 1.0 1.5 2.0Wavelength (μm)

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Cell # 8642, x = 17, y = 115Photo-z estimate: 1.186

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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AB m

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Cell # 8342, x = 17, y = 111Photo-z estimate: 1.298

0.5 1.0 1.5 2.027

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0.5 1.0 1.5 2.0Wavelength (micron)27

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AB m

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Cell # 2043, x = 18, y = 27Photo-z estimate: 0.760

0.5 1.0 1.5 2.0Wavelength (μm)

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AB m

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Cell # 8988, x = 63, y = 119Photo-z estimate: 0.595

0.5 1.0 1.5 2.0Wavelength (μm)

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AB m

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Cell # 6490, x = 40, y = 86Photo-z estimate: 2.364

0.5 1.0 1.5 2.027

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0.5 1.0 1.5 2.027

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Cell # 3051, x = 51, y = 40Photo-z estimate: 0.529

Wavelength (micron)

SOM based on Euclid colorsEmpirical P(z|C)

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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AB m

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Cell # 8642, x = 17, y = 115Photo-z estimate: 1.186

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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AB m

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Cell # 8342, x = 17, y = 111Photo-z estimate: 1.298

0.5 1.0 1.5 2.027

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25

24

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0.5 1.0 1.5 2.0Wavelength (micron)27

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AB m

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Cell # 2043, x = 18, y = 27Photo-z estimate: 0.760

0.5 1.0 1.5 2.0Wavelength (μm)

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0.5 1.0 1.5 2.0Wavelength (μm)

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AB m

ag

Cell # 8988, x = 63, y = 119Photo-z estimate: 0.595

0.5 1.0 1.5 2.0Wavelength (μm)

27

26

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20

0.5 1.0 1.5 2.0Wavelength (μm)

27

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Cell # 6490, x = 40, y = 86Photo-z estimate: 2.364

0.5 1.0 1.5 2.027

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25

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0.5 1.0 1.5 2.027

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AB m

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Cell # 3051, x = 51, y = 40Photo-z estimate: 0.529

Wavelength (micron)0 20 40 60

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Median spec-z, confidence > 95% redshifts

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Masters et al. 2015, ApJ, 813, 53

Self-organized map of galaxy colors

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u Designed to “fill the gaps” in our knowledge of the color-redshift relation to Euclid depth

u Collaboration of Caltech (PI J. Cohen, 16 nights), NASA (PI D. Stern, 10 nights, PI D. Masters, 10 nights (2018A/2018B)), the University of Hawaii (PI D. Sanders, 6 nights), and the University of California (PI B. Mobasher, 2.5 nights), European participation with VLT (PI F. Castander)- Multiplexed spectroscopy with a combination of Keck DEIMOS, LRIS, and

MOSFIRE and VLT FORS2/KMOS targeting VVDS, SXDS, COSMOS, and EGS

- DR1 published (Masters, Stern, Capak et al. 2017) with 1283 redshifts, DR2 (in prep) will bring total to >4000 redshifts, observations in 2017B and later will comprise DR3

- New Hawaii program (H20) led by Dave Sanders will also contribute

u Currently a total of 44.5 Keck nights awarded (29.5 observed in 2016A-2017A, 5 nights each in 2017B/2018A/2018B)

Complete Calibration of the Color-Redshift Relation (C3R2) Survey:

C3R2: Mapping the galaxy P(z|C) relation

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C3R2 survey strategyMedian 30-band Photo-z

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0 1 2 3 4 5 6Median spec-z, confidence > 95% redshifts

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0 1 2 3 4 5 6Cell Occupation

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The ingredients of the survey:Left: Prior on galaxy properties across color space from deep, multiband dataCenter: Shows parts of color space that have redshifts and that don’tRight: Density of sources across color space to Euclid depth

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• C3R2 designed to map galaxy color space to i~25 – Euclid depth, also well-matched to HSC survey

• WFIRST shear sample will be significantly deeper • Need an analog to anticipated WFIRST photometric

sample – CANDELS is only current dataset that can match the depth in optical-NIR

• It is small (~0.2 deg2) and heterogeneous– Impacted by cosmic variance, shot noise

• Best current option

C3R2: The challenge of WFIRST

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CANDELS interpolated to LSST+WFIRST

Hemmati et al. (in prep)

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Redshifts on WFIRST-analog SOM

CANDELS median photo-z CANDELS median spec-z

Hemmati et al. (in prep)

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Position on SOM predicts spectral properties

Hemmati et al. (in prep)

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WFIRST “faint” vs. “bright” sample

Left: Distribution of WFIRST faint (i > 25) sample on SOM; fills ~50%Right: Distribution of WFIRST bright (i < 25) sample; most cells filled

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Key issues for WFIRST photo-z calibration

• Do faint galaxies that share colors with brighter galaxies have the same redshift?– i.e., is there are meaningful luminosity prior when

using ~7 colors spanning optical-NIR– How to demonstrate the answer short of lots of

spectroscopy of very faint sources?

• How to calibrate the WFIRST-faint sample that has no bright counterparts?

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Targeted spectroscopy with PFS

• PFS has significant potential to contribute to photo-z calibration for WFIRST

• Two notional uses are:1. Targeted samples calibrating P(z|C) relation to faint magnitudes

directly, like C3R2 (difficult)2. Observe a bright sample selected to facilitate cluster-z

• The latter option may be appropriate for the faintest WFIRST sources

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Flexible observations with HSC

• Intermediate band surveys with HSC may be able to improve WFIRST photo-zs substantially– Stronger constraints on emission lines, weak spectral breaks

• Could design ideal deep field complementary to WFIRST• Time to refine strategy as we learn more

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Galaxy science with Subaru/WFIRST• Statistical power!• Surveys like SDSS reveal relationships (FMR, dust-mass relation, N/O-

mass relation, star-forming main sequence) that become apparent only with large samples with high-quality rest-optical spectra

• This level of study at intermediate-to-high redshift not currently possible

Kashino et al. 2016Mannucci et al. 2010 Masters et al. 2016

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Emission line science with PFS+WFIRST grism

• Possible to get full suite of optical emission lines to z~2, or up to [OIII]5007 to z~3

• Incredible statistical power– JWST will focus on very high redshift– Limited total numbers

• Could build Sloan-like sample at z~0.5-3 with stellar masses, rest-optical spectra, etc. for many thousands of galaxies

Faisst, Masters, Wang et al. 2017 (submitted)