tip of the red giant branch as distance indicator - eso

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TIP OF THE RED GIANT BRANCH AS DISTANCE

INDICATOR

ESO KES, October 2019

Marina Rejkuba

Lemaitre

1927

Robertson

1928

Hubble

1929

Jan Oort

Sandage

Baade

Allan Sandage &

Gustav Tammann

Gerard de Vauculeurs

1996 Scale of the Universe debate:

Gustav Tammann vs Sidney van den Bergh

HST KEY PROJECT

β€’ 1990 launch of the Hubble Space Telescope

β€’ R. Giacconi (first director) established HST Key Projects:

1. Measure H0 with an accuracy of 10%

2. Study of the IGM through quasar absorption lines

3. Medium-deep survey of galaxies

2001: HST Key Program:

𝐻0 = 72 Β± 8 π‘˜π‘š π‘ βˆ’1π‘€π‘π‘βˆ’1

Age of the Universe in the Einstein-de Sitter model: 9.1 Gyr

(still younger than some of the oldest stars)

Wendy Freedman

THE CARNEGIE-CHICAGO HUBBLE PROGRAM

RED GIANT BRANCH TIP THEORETICAL BACKGROUND

Solar composition tracks:

M= 0.9, 1, 1.2 …. 2.1 Mo

2.3, 2.5, 3 , 4, 5, 6 Mo

7 , 8 , 9 , 10 Mo

from BaSTI database

Dashed lines: constant radii

R=0.01,0.1,1,10,100,1000 Ro

Dot-dashed for WDs:

R= 0.008,0.013 Ro

(MWD=1,0.6 Mo)

Hot HB, AGB-Manque’,

normal HB tracks for

MHB=0.48,0.5,0.55 Mo

Stellar Evolutionary Tracks

PN

RED GIANT BRANCH EVOLUTION

RGB: He-core supported by e- degeneracy pressure surrounded by a H-burning shell that provides the luminosity

RGB evolution:

core mass increases β†’ radius shrinks β†’

shell T & consequently the luminosity

generated in the shell increases β†’ star

climbs along the RGB with increasing luminosity and core temperature

RGB Tip:

He core ignition β†’ lifts e- degeneracy in the

core β†’ core flash quenched within seconds β†’ core inflates & star settles at lower

luminosity burning He in the core

H-R DIAGRAM FOR OLD STELLAR POPULATIONS

Stellar

evolutionary

tracks from

ZAMS to TRGB

for stars with masses: 0.8, 1,

and 1.3 M

i.e. age > 4 Gyr

Serenelli et al.

2017

Note:

Age-Metallicity

Degeneracy

RED GIANT BRANCH TIP

β€’ Theoretically well understood: discontinuity for old metal-poor stars evolving on RGB

β€’ Attractive alternative for RR Lyr & Cepheid distance scale

β€’ Population II: lower extinction and crowding

β€’ Single epoch observations – easy to observe/measure

β€’ I-band TRGB nearly constant for old metal-poor stars

β€’ 4 mag brighter than RR Lyr, less extinction than Cepheids

β€’ Da Costa & Armandroff 1990 (DA90): β€œStandard Globular Cluster Giant Branches in the [MI vs (V-I)0] Plane”

β€’ Lee, Freedman & Madore 1993: β€œThe Tip of the Red Giant Branch as Distance Indicator for Resolved Galaxies”

DA COSTA & ARMANDROFF 1990: β€œSTANDARD GLOBULAR CLUSTER

GIANT BRANCHES IN THE [MI VS (V-I)0] PLANE”

β€œIn Sec. IV the cluster giant branch results are compared with the predictions of theory. … The agreement found is quite satisfactory

indicating, inter alia, that the giant branch tip luminosity can be used as a distance indicator for old stellar populations.”

MI assuming HB distances based on

Lee, Demarque & Zinn 1990 calibration:

MV(RR) = 0.82 + 0.17 [Fe/H]

DA90 Standard GC RGBs

𝐡𝐢𝐼 = 0.881 βˆ’ 0.234 𝑉 βˆ’ 𝐼 𝑇𝑅𝐺𝐡

π‘€π‘π‘œπ‘™π‘‡π‘…πΊπ΅ = βˆ’0.19

𝐹𝑒

π»βˆ’3.81

π‘š βˆ’π‘€ 𝐼 = 𝐼𝑇𝑅𝐺𝐡 βˆ’ 𝑀𝐼,𝑇𝑅𝐺𝐡 = 𝐼𝑇𝑅𝐺𝐡 + 𝐡𝐢𝐼 βˆ’π‘€π‘π‘œπ‘™π‘‡π‘…πΊπ΅

𝑀𝐼 β‰… βˆ’4.05

𝐹𝑒/𝐻 = βˆ’15.16 + 17.0 𝑉 βˆ’ 𝐼 βˆ’3 βˆ’ 4.9 𝑉 βˆ’ 𝐼 βˆ’32

LEE, FREEDMAN & MADORE 1993:β€œTHE TIP OF THE RED GIANT

BRANCH AS A DISTANCE INDICATOR FOR RESOLVED

GALAXIES”

LEE ET AL. 1993

β€’ Edge detection – zero sum Sobel Kernel [-2, 0, 2] convolution with I-band luminosity function

Madore & Freedman β€˜95

LEE ET AL. 1993

β€’ Method as in DA90 with slight modification:𝐹𝑒/𝐻 = βˆ’12.64 + 12.6 𝑉 βˆ’ 𝐼 βˆ’3.5 βˆ’ 3.3 𝑉 βˆ’ 𝐼 βˆ’3.5

2

β€’ Since 𝑀𝐼 β‰… βˆ’4 Β± 0.1 π‘šπ‘Žπ‘” with little variation with metallicity for [Fe/H]≀ βˆ’0.7 dex, the method can be used up to ~4 Mpcfrom the ground and up to Virgo and Fornax with the HST

EARLY WORKS

β€’ Sakai et al. 1996:

β€’ replace the discrete LFs with their respective Gaussians (smooth)

β€’ apply adaptive edge-detection – localised slope estimator with 4-point smoothing

β€’ Madore & Freedman 1995: extensive computer simulations

β€’ Signal-to-noise – larger than 5 to limit photometric errors

β€’ Crowding – less than 25% (one star every 3 contaminated)

β€’ Population size – need ~50 stars within upper 1 mag

β€’ Contamination from non-RGB stars – work in outer halo

𝐸 π‘š = Ξ¦ 𝐼 + ΰ΄€πœŽπ‘š βˆ’Ξ¦ 𝐼 βˆ’ ΰ΄€πœŽπ‘š

Sakai+1996: Sextans A

TRGB brightness in the main body 21.64

and in the halo 21.79

β€’ Authors attribute to crowding

β€’ Age may play a role as well

MEASURING TRGB

β€’ Cioni et al. 2000

β€’ LMC & SMC – TRGB in I, J, K band

β€’ Bolometric correction using J-K color

β€’ Using Savitzky-Golay filter to estimate the 2nd

derivative

β€’ Use Gaussian fit to identify TRGB

β€’ Systematic correction up to ~0.02 mag (AGB, photometric errors)

MAXIMUM LIKELIHOOD

β€’ Mendez, B. et al. 2002, Makarov et al. 2006

β€’ Maximum likelihood

β€’ logarithmic edge detection to smooth the luminosity function

β€’ RGB LF is a power law: 𝑁 π‘š π‘‘π‘š ∝ 10π‘Žπ‘š & π‘Ž = 0.30 Β± 0.04

β€’ Marginalising over free parameters: TRGB mag, LF slope brighter than TRGB, discontinuity strength

Makarov et al. 2006

TRGBDETECTION

Edge detection + smoothing due to

Poisson noise in the LF

Smoothing incorporated:

(i) in the edge detection of the kernel(ii) applied to the LF itself

(iii) folded in the model

Edge detection:

1. Discrete approx. to derivative (Sobel kernel)

2. Discrete approx. to derivative that

incorporate smoothing (Gaussian

formulation of Sobel kernel)

3. Maximum likelihood fitting

TRGB CALIBRATION

GCs: Ferraro+2000, Bellazzini+2004; Valenti+2004

Galaxies: Rizzi et al. 2007, Jang & Lee 2017

Bellazzini et al. 2004

Large dots:

Omega Cen

47 Tuc

Solid lines:

Empirical calibrations

Dashed lines:Fit to data

Open squares:

theoretical models

Salaris & Cassisi β€˜98

RED GIANT BRANCH TIPNGC 5128

IRGBT=24.1Β± 0.1 mag

D = 3.8 Β± 0.1 Mpc Rejkuba et al. 2005

I-BAND COLORDEPENDENT CALIBRATION

Rizzi et al. 2007:

β€’ Slope is always the same

β€’ Zero point calibrated via

HB in 5 Local Group

galaxies & applying

Carretta et al. 2000 calib

β€’ MI = - 4.05 +/- 0.02 at

(V-I) = 1.6

TRGB: METALLICITY CORRECTION

𝑀𝐼𝑇𝑅𝐺𝐡 = 0.14

𝐹𝑒

𝐻

2

+ 0.48𝐹𝑒

π»βˆ’ 3.629

𝑉 βˆ’ 𝐼 = 0.581𝐹𝑒

𝐻

2

+ 2.472𝐹𝑒

𝐻+ 4.013

Belazzini et al. 2001, 2004:

Mager et al. 2008

Jang & Lee 2017

Quadratic fit to measure TRGB vs color

Zero point anchors:

β€’ LMC (eclipsing binaries)

β€’ NGC 4258 (Maser)

ERROR BUDGET

Jang & Lee

2017

aF555W – F814W to F606W – F814W transformation.

SUMMARY: I-BAND CALIBRATIONS

Beaton et al. 2018

TRGB IN INFRARED

Z = 0.004, 0.001, 0.004,

0.008, 0.19, and 0.30

Girardi+02 isochrones

NIR data for

24 GCs

Valenti + 2004

AGE DEPENDENCY

Salaris & Girardi 2005:

β€œβ€¦ the TRGB method for distance determinations has to be applied with

caution to all galaxies that present signatures of intermediate-age stars.”

TRGB CALIBRATION WITH GAIA DR2

SkyMapper Gaia DR2 RGB with overplotted calibration of

the TRGB by Rizzi et al. 2007 (solid line)

Mould,

Clementini

& Da Costa

2019

BOLOMETRIC CORRECTION

Serenelli et al. 2017 𝑀𝐼𝑇𝑅𝐺𝐡 = π‘€π‘π‘œπ‘™

𝑇𝑅𝐺𝐡 βˆ’ 𝐡𝐢𝐼

Full age range

NGC 4258

THE CARNEGIE-CHICAGO HUBBLE PROGRAM

Extragalactic distance scale using only Population II distance indicators

Beaton+2018

Beaton et al. 2018

TAKE HOME MESSAGES

β€’ TRGB potential for Cepheid-independent precise & accurate distance scale measurement

β€’ TRGB as RELATIVE distance indicator – precision < 5%

β€’ TRGB as ABSOLUTE distance indicator – accuracy > 5%

β€’ Need better I-band bolometric corrections

β€’ Future application for H0 measurements with ELT, JWST:

β€’ K-band (and J, H) calibration work ongoing

β€’ application possibly more complex

REFERENCES AND FURTHER MATERIAL

β€’ Freedman, Wendy & Madore, Barry F., 2010, ARA&A: β€œThe

Hubble Constant”

β€’ Beaton, R. L., et al. 2018: β€œOld Aged Stellar

Population Distance Indicators”

β€’ Serenelli, A, Weiss, A., Cassisi, S., et al., 2017: β€œThe

brightness of the RGB tip. Theoretical framework, a set of

reference models, and predicted observables”

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