Surface Brightness Fluctuations in the Hubble Space Telescope ACS/WFC F814W Bandpass and an Update on Galaxy Distances
John P. Blakeslee, Michele Cantiello, Simona Mei, Patrick Cote, Regina Barber DeGraaff, Laura Ferrarese, Andres Jordan, Eric W. Peng, John L. Tonry, Guy Worthey
aa r X i v : . [ a s t r o - ph . C O ] S e p A CCEPTED FOR PUBLICATION IN A P J Preprint typeset using L A TEX style emulateapj v. 8/13/10
SURFACE BRIGHTNESS FLUCTUATIONS IN THE HUBBLE SPACE TELESCOPE ACS/WFC F814W BANDPASSAND AN UPDATE ON GALAXY DISTANCES * J OHN
P. B
LAKESLEE , M
ICHELE C ANTIELLO , S IMONA M EI , P ATRICK C ÔTÉ , R EGINA B ARBER D E G RAAFF ,L AURA F ERRARESE , A NDRÉS J ORDÁN , E RIC
W. P
ENG , J OHN
L. T
ONRY , G UY W ORTHEY Accepted for publication in ApJ
ABSTRACTWe measure surface brightness fluctuation (SBF) magnitudes in the F814W filter and ( g - I ) colors fornine bright early-type Fornax cluster galaxies imaged with the Hubble Space Telescope
Advanced Camerafor Surveys (ACS). The goal is to achieve the first systematic SBF calibration for the ACS/F814W bandpass.Because of its much higher throughput, F814W is more efficient for SBF studies of distant galaxies than theACS/F850LP bandpass that has been used to study nearby systems. Over the color range spanned by the samplegalaxies, 1 . < ( g - I ) < .
32 (AB mag), the dependence of SBF magnitude m on ( g - I ) is linearto a good approximation, with slope ∼
2. When the F850LP SBF distance measurements from the ACS FornaxCluster Survey are used to derive absolute M magnitudes, the dependence on ( g - I ) becomes extremelytight, with a slope of 1 . ± . Subject headings: galaxies: distances and redshifts — galaxies: clusters: individual (Fornax) — galaxies:elliptical and lenticular, cD INTRODUCTION
The measurement of galaxy distances has been a centralproblem in astronomy ever since the discovery of “spiral neb-ulae” by Lord Rosse in the mid-nineteenth century. Becausegeometric methods were of no avail, the nature of these ob-jects remained a matter of conjecture for many decades. Onlywith the work of Henrietta Swan Leavitt did accurate photo-metric distance estimates to resolved stellar systems becomea reality. Her painstaking photographic measurements of thelight curves for 1800 variable stars (and hundreds of com-parison stars) in the Magellanic Clouds led her to note thatfor variables of a certain class, the brighter ones had longertemporal periods (Leavitt 1908). The Leavitt Law, relatingthe luminosities of Cepheid variables to their periods, provedto be the key to the mystery of the spiral nebulae, locatingthem firmly beyond the spatial extent of our own Galaxy;thus it was also the key to comprehending the true scale of * Based on observations with the NASA/ESA
Hubble Space Telescope ,obtained from the Space Telescope Science Institute, which is operated byAURA, Inc., under NASA contract NAS 5-26555. Herzberg Institute of Astrophysics, National Research Council ofCanada, Victoria, BC V9E 2E7, Canada; [email protected] Department of Physics and Astronomy, Washington State University,Pullman, WA 99163-2814 INAF-Osservatorio Astronomico di Teramo, via M. Maggini, I-64100,Teramo, Italy University of Paris Denis Diderot, 75205 Paris Cedex 13, France GEPI, Observatoire de Paris, Section de Meudon, 5 Place J. Janssen,92195 Meudon Cedex, France Departamento de Astronomía y Astrofísica, Pontificia UniversidadCatólica de Chile, Santiago 22, Chile Department of Astronomy, Peking University, Beijing 100871, China Institute for Astronomy, University of Hawaii, Honolulu, HI 96822 the Universe, eventually accomplished with the work of Hub-ble (1926, 1929).Accurate galaxy distances remain of fundamental impor-tance to most astrophysical applications. Errors in distanceestimates generally translate into equal or larger fractional un-certainties in derived quantities such as masses (of everythingfrom central black holes to dark matter haloes), linear sizes,dynamical timescales, star formation rates, and ages. Thus,accurate distance estimation is essential for inter-comparingthe physical properties of galaxies in the local volume whereredshift is not a reliable indicator of distance, and for com-paring the properties of nearby galaxies to those at high red-shift. Of course, they are also essential for mapping localthree-dimensional structures and velocity fields.There are a variety of distance indicators that can be usedwithin and beyond the limit of classical Cepheid distances;Freedman & Madore (2010) provide a recent overview of themethods. One of the most accurate of these is surface bright-ness fluctuations (SBF; Tonry & Schneider 1988; for a histor-ical review, see Blakeslee et al. 2009, hereafter ACSFCS-V).The SBF method measures the intrinsic variance in a galaxyimage resulting from the random variations in the numbersand luminosities of the stars falling within individual pixelsof the image. This variance is normalized by the local galaxysurface brightness and then converted to the apparent SBFmagnitude m . The distance modulus, m - M follows once theabsolute magnitude M is known.The value of M in a given bandpass depends on the stellarpopulation properties. For early-type systems, a single broad-baseline color generally suffices for characterizing the stellarpopulation (e.g., Tonry et al. 1997; Ajhar et al. 1997; Fer- Blakeslee et al.rarese et al. 2000; Blakeslee et al. 2001; Mei et al. 2005b;ACSFCS-V). The zero-point of the I -band M calibration hasbeen tied directly to the Cepheid distance scale to an accuracyof 0.08 mag, or ∼
4% in distance, from ground-based SBFmeasurements in spiral bulges (Tonry et al. 2000). For dis-tance estimation purposes, SBF is best measured in the red-dest optical bandpasses. The fluctuations arise mainly fromred giant branch stars and thus are brighter at redder wave-lengths. However, the stellar population dependence becomesmore complicated in the near-infrared (Jensen et al. 2003),which adds intrinsic scatter to that application of the method.Thus, the red end of the optical spectrum is something of a“sweet spot” for SBF.The SBF method has been an important part of two recent
Hubble Space Telescope ( HST ) surveys of early-type clus-ter galaxies carried out with the Advanced Camera for Sur-veys’ Wide Field Channel (ACS/WFC). The 100-orbit ACSVirgo Cluster Survey (ACSVCS; Côté et al. 2004) and the43-orbit ACS Fornax Cluster Survey (ACSFCS; Jordán et al.2007) both observed one galaxy per orbit, with the time splitbetween the F475W and F850LP filters. The SBF analy-sis was performed on the F850LP ( z -band) images, whilethe second bandpass enabled the calibration of the SBF z magnitude in terms of ( g - z ) color (Mei et al. 2005b;ACSFCS-V). These single-orbit observations were adequateat the distances of the Virgo and Fornax clusters, but forgalaxies significantly farther away, the relatively low through-put of F850LP can make the required exposure times pro-hibitive. The F814W filter then becomes more attractive forSBF work simply because the higher total throughput of thispassband reduces the exposure time by at least a factor of two.However, although there have been some ACS/WFC mea-surements of SBF in this bandpass (Cantiello et al. 2007a,b;Barber DeGraaff et al. 2007; Biscardi et al. 2008), there hasbeen no systematic empirical calibration of the SBF method inF814W similar to that in F850LP. The main goal of the presentwork is to provide such a calibration that will be applicable tothe bright early-type galaxies targeted at large distances.The following section presents our observational sampleand basic imaging reductions. Section 3 describes our SBFand color measurements in detail and compares the resultsto our previous F850LP measurements. Section 4 providesa comparison with predictions from stellar population mod-els and discusses the uncertainty in the absolute distance tothe Fornax cluster. Section 5 presents the conclusions fromthis study. In Appendix A, we revisit the ground-based SBFdistances from Tonry et al. (2001) and provide a simple cor-rection formula for possible bias in those distances. Finally,Appendix B presents two additional SBF distance measure-ments from the ACSVCS F475W and F850LP imaging data. OBSERVATIONS AND IMAGE REDUCTIONS
The proximity ( ∼
20 Mpc) and compactness of theelliptical-rich Fornax cluster makes it the ideal target for cali-brating the stellar population dependence of the SBF methodin any bandpass (e.g., Tonry 1991; ACSFCS-V). As we aremainly interested in the calibration for luminous early-typegalaxies, we selected the eight brightest Fornax galaxies aslisted by Jordán et al. (2007), all of which have M B < - ± .
02 mag over the normal color range forgiant ellipticals.As part of
HST program GO-10911, we observed six fields with the ACS/WFC targeting large galaxies in the Fornaxcluster. Each observation consisted of three dithered expo-sures in the F814W filter totaling 1224 s and two ditheredexposures in F475W totaling 680 s. The galaxy NGC 1375is separated by only 2 . ′ . ′ HST archive on the For-nax galaxies NGC 1316 (from GO-9409, PI: Goudfrooij) andNGC 1344 (from GO-9399, PI: Carter) and suitable F475Wdata on the same two galaxies from GO-10217 (PI: Jordán).Table 1 summarizes the properties and basic observational de-tails for our nine target galaxies, including the z SBF dis-tances from the ACSFCS-V.The exposures were bias and dark current subtracted andflatfielded by the standard STScI pipeline processing. Thecalibrated “flt” data were then run through the Apsis pipeline(Blakeslee et al. 2003) to produce geometrically rectified,clean, combined images. Apsis uses Drizzle (Fruchter &Hook 2002) for the geometric transformation of the images,and we use the Lanczos3 interpolation kernel in order to pre-serve the essential properties of the image power spectra (seeMei et al. 2005a). All photometry reported here is on the ABsystem, calibrated based on Sirianni et al. (2005) and Bohlin(2007) with the revised zero points from the ACS instrumentwebsite for data obtained before July 2006. In particular,we adopted: m (F475W) = 26 . m (F814W) = 25 . m = - . f ) + m , and f is in electrons per second.The ACS/WFC F814W and F475W bandpasses closely ap-proximate the Kron-Cousins I and Sloan Digital Sky Survey g bands, so we refer to magnitudes in these bandpasses as g and I , respectively. We corrected for Galactic extinctionusing the dust maps from Schlegel et al. (1998) with the ex-tinction ratios given by Sirianni et al. (2005). The extinctionin this direction is small, E ( B - V ) . .
02 mag. SBF ANALYSIS
Measurements within Annuli
There have been a variety of implementations of the SBFanalysis within different reduction packages (e.g., Tonry et al.1990; Lorenz et al. 1993; Pahre et al. 1999; Nielsen & Tsve-tanov 2000; Liu et al. 2002; Mieske et al. 2003; Mei et al.2005a; Cantiello et al. 2005; Dunn & Jerjen 2006), but fewdetailed comparisons between them. One notable exceptionis the comparison made by Pahre et al. (1999) of their SBFresults for one galaxy observed with HST/WFPC2 with theresults for the same observation using the Tonry et al. (1990,1997) software. They found good agreement for this one case.Otherwise, the comparisons have mainly been between sets ofpublished numbers, rather than tests of different analysis pro-cedures applied to the same data.In order to ensure that our calibration is as general as pos-sible, we performed two complete sets of SBF reductions onall the galaxies. We first used the custom SBF analysis soft-ware developed by J. Tonry within the Vista environment for ∼ jt/soft.html BF Distances 3 F IG . 1.— Power spectrum measurements for different annuli within our program galaxies (labeled); the radii of the annuli increase from leftto right, as described in the text. The red curves show our fits to the power spectra. Because of the significant dust features, the annuli forNGC 1316 differ from the other galaxies’, and only three were used. The power spectra are normalized by the local galaxy surface brightness, sothat the amplitude P of the PSF component (dotted curve) corresponds to the SBF magnitude m , after a small .
2% correction for backgroundvariance.
Blakeslee et al.the ground-based SBF survey (Tonry et al. 1997) and appliedmost recently to
HST /ACS data by Barber DeGraaff et al.(2007). We refer to this set of reductions as the “Tonry” SBFanalysis; details can be found in the referenced works and sev-eral others that have used the same software (e.g., Blakesleeet al. 1997; Jensen et al. 1998). These reductions tend to be in-teractive, with the user selecting radial limits for the analysisregions within each galaxy and power spectrum fitting limits.Second, we applied the identical SBF analysis code as used inACSFCS-V, which was only slightly modified from the analy-sis routines developed and used by Mei et al. (2005a,b). Theseroutines are written in IDL and the SBF analysis is more au-tomated, which facilitates multiple runs to test for systematicseffects. As an example, Mei et al. (2005a) reran the analysisnumerous times on simulated images processed with Apsis toassess the effects of different Drizzle interpolation kernels.While there are no fundamental differences between thetwo analysis codes likely to cause any significant disagree-ments, the current data set affords a useful test of the levelconsistency that can be expected. For both sets of SBF mea-surements, we model and subtract the galaxy, mask all vis-ible sources, and estimate the residual variance from unde-tected sources as detailed in our previous works (Mei et al.2005b; Barber DeGraaff et al. 2007; Jordán et al. 2004, 2007;ACSFCS-V). These steps are the same for nearly all im-plementations of the SBF method, and we used the samegalaxy models and background variance corrections for bothsets of reductions. For this sample of high-resolution, high-throughput F814W ACS imaging data, the estimated back-ground corrections ranged from 0.011 to 0.019 mag. As inour previous works, we assign 25% uncertainty to these val-ues, meaning that the contribution to the total error in the SBFmagnitude is less than 0.005 mag. This contrasts stronglywith ground-based analyses, for which the source detectionlimits tend to be much brighter and the background variancecorrection is often a major source of uncertainty. We maskeddusty regions in the galaxy images as described in Ferrareseet al. (2006) by taking the ratio of the images in the twobands and identifying areas that significantly deviated fromthe smooth color profile. The dust masks were augmented byhand as needed. The two galaxies in our sample with signif-icant dust features are NGC 1316 and NGC 1380. Thus, thiscomparison of SBF analyses does not address possible prob-lems with galaxy modeling or residuals due to dust or othercontaminants. However, the consistency of the results as afunction of radius within a galaxy can be used to check forsuch problems.Both the Tonry and IDL analysis procedures are performedin a series of annuli with increasing radii. The inner radius ofthe innermost annulus was 6 . ′′ . ′′
8. The outer radius of each annulus was typically twice itsinner radius, although for the IDL code we used a maximumannular width of 256 pix to be more similar to our past analy-ses, and only annuli where the galaxy I surface brightnessis at least twice the sky background were used. For the Tonrycode analysis, we set the maximum outer radius somewhat ar-bitrarily at 1000 pix, except in the case of the faintest galaxyNGC 1375, for which it was 512 pix. The two different analy-sis procedures independently calculate the power spectra andfit the amplitude of the component that has been convolvedwith the point spread function (PSF), which corresponds tothe SBF signal after correcting for the background variance.Section 3.2 discusses systematic effects from different PSFs. In fitting the power spectra, the IDL code omits the low-est wavenumbers, those representing spatial scales larger than20 pix, since these are affected by the galaxy and large-scalebackground light subtraction, and it also omits the severalhighest wavenumbers because of the pixel correlation intro-duced by the geometric correction (see Mei et al. 2005 for de-tails). However, with the adopted Lanczos3 kernel, the pixelcorrelation is very mild and the power spectrum fit is notvery sensitive to the maximum wavenumber, assuming thatthe PSF model is accurate. The Tonry code also omits thelowest numbers, although this is done interactively by select-ing the point where the fitted amplitude P of the PSF compo-nent becomes stable. There is no option in this code to omitthe highest wavenumbers, so this is another difference in theanalyses. Figure 1 displays power spectra fits for multiple an-nuli within the program galaxies from the IDL analysis code.The signal is very strong and well fitted in all cases; note thelogarithmic scale.The two analysis procedures both measure the ( g - I )color in each annulus after applying the same mask as usedfor the SBF measurement. We then calculate the biweightmeans of the color and SBF measurements from among theannuli to get the average values for each galaxy. We note thatradial color gradients are common in early-type galaxies andSBF magnitudes follow the same trends. SBF and color gra-dients have been studied in ACS imaging data from a stellarpopulation perspective by Cantiello et al. (2005, 2007a). Allof the galaxies in our sample have detectable color gradientsexcept the bluest galaxy NGC 1375. However, as found byACSFCS-V, the presence of such gradients is not a problemfor our averaging procedure as long as the SBF–color rela-tion is approximately linear over the color range within eachgalaxy. Figure 2 shows SBF and color measurements for theindividual annuli within the galaxies. The top panel plots theobserved values of m , while the lower panel plots abso-lute M after subtracting the z SBF distance moduli fromACSFCS-V. There is a clear trend between SBF magnitudeand ( g - I ) color, well approximated by a linear relation.The scatter is about ∼
30% lower for M as compared to m . The improvement in scatter for a quadratic fit, as com-pared to linear one, is not significant.The mean difference in galaxy SBF magnitudes from theTonry and IDL power spectrum analyses was 0 . ± . Effect of the Point Spread Function
As noted in the previous section, the SBF measurement in-volves fitting the amplitude of the component of the powerspectrum that has been convolved with the PSF of the im-age. Thus, the PSF template is an important considerationBF Distances 5 F IG . 2.— Top: apparent SBF magnitude as a function of ( g - I ) colorfor individual annuli within the nine program galaxies. Bottom: mean abso-lute SBF magnitudes after subtracting the individual distance moduli fromACSFCS-V are plotted versus color. The dashed lines are simple linear least-squares fits, while the solid curves show quadratic fits for comparison. Rep-resentative measurement errors are indicated in the lower right of each panel;the M error bar includes the typical distance uncertainty. in the analysis. The ACSVCS and ACSFCS analyses (Meiet al. 2005b; ACSFCS-V) both used a composite empiricalPSF constructed from archival images by Blakeslee et al.(2006) for deconvolving the profiles of high-redshift clustergalaxies. The PSF variation within ACS/WFC images af-ter distortion-corrected is small (Krist 2003) and occurs onsmall scales (largest wavenumbers) that do not significantlyaffect the power spectrum fits (Mei et al. 2005a), althougha 2% error in the fitting for different annuli was assumed inACSFCS-V (as well as here, since the same code was used)from the spatial variation in the PSF. However, tests by Meiet al. (2005a) and Cantiello et al. (2005, 2007b) using multi-ple ACS/WFC PSF stars (generally taken from different im-ages) found variations of 0.02–0.05 mag in the final m val-ues. Similar, though slightly larger, variations of 0.04–0.06mag were found in tests using multiple PSFs in ground-baseddata with a variable PSF and in HST /NICMOS data (Blakeslee1999; Jensen et al. 2001). The variations in m are due to acombination of effects, including errors in determining thecorrect normalization of each PSF template (systematic fora given data set), and mismatch between the PSF templateand galaxy image (potentially random, if the PSF varies fromimage to image).For this study, we searched all of our fields for relativelyisolated stars that were bright but unsaturated, and could beused to make a high signal-to-noise model of the PSF powerspectrum. The density of stars in these fields, which are at Galactic latitude b ≈ - ◦ , is low. We found only one suit-able star, which was in the IC 2006 field, and used this as ourprimary PSF template. We also tried PSFs from other datasets and reran the full IDL power spectrum analysis to as-sess the effect on m . The ACS Instrument DevelopmentTeam made available the composite PSFs constructed fromthe white dwarf spectrophotometric standard stars analyzedby Sirianni et al. (2005) and processed with the same inter-polation kernel. The composite star for the F814W bandpasshas been used for some previous SBF studies (Barber DeGraffet al. 2007; Cantiello et al. 2005, 2007a,b). When we used thistemplate, our final m values became systematically fainterby 0.036 mag. We also tried individual stars from a randomACS F814W image that we had available, and the final m values became brighter by a similar amount.Consistent with previous studies, these tests indicate vari-ations of ∼ SBF Calibration for F814W
Figure 3 plots the SBF magnitudes versus ( g - I ) colorfor our sample of nine Fornax galaxies, similar to Figure 2,but here using the final averaged quantities for each galaxy.Fitting a linear relation for m in terms of ( g - I ), in-cluding errors in both axes and an additional 0.06 mag of in-trinsic (or “cosmic”) scatter in m at fixed ( g - I ) due tostellar population effects (ACSFCS-V), we find m = (30 . ± . + (2 . ± .
33) [( g - I ) - . , (1)where ( g - I ) = 1 . . ± .
02 mag for our nine sample galaxies, butsince we have good z SBF measurements for each one, andwant the calibrations of the two bandpasses to be as consis-tent as possible, we instead derive absolute M magnitudesusing the individual distance measurements. The lower panelof Figure 3 shows the results, which give the following cali-bration fit: M = ( - . ± . ± . + (1 . ± .
20) [( g - I ) - . , (2)which is valid for AB colors 1 . < ( g - I ) < .
32 mag.The rms scatter of the data points with respect to this linear Blakeslee et al. F IG . 3.— The F814W SBF calibration.
Top: mean apparent SBFmagnitude as a function of ( g - I ) color for the sample galaxies.The vertical error bars are the quadrature sums of the measurementerrors and an intrinsic stellar population scatter of 0.06 mag, as esti-mated in ACSFCS-V. Horizontal error bars represent measurementerrors. Galaxies are labeled by their catalogue numbers. Bottom: themean absolute SBF magnitudes after subtracting the individual dis-tance moduli from ACSFCS-V are plotted against color. The ver-tical error bars are the quadrature sums of the measurement errorsand the distance error (which includes the intrinsic component) fromACSFCS-V. Horizontal error bars again represent measurement er-rors. The lines show linear fits including errors in both coordinates;the coefficients are given in Equations (1) and (2), respectively. calibration is 0.029 mag, and the fit has been derived usingthe ( g - I ) and m measurement errors, plus 0.015 magof additional error added in quadrature to make χ n = 1 . M values. However, when we do this,we find χ n = 0 .
2, which has less than a 2% probability of oc-currence. The likely explanation relates to the behavior of theintrinsic scatter of 0.06 mag that was estimated by ACSFCS-Vand has been included in the distance errors. This is the largestcomponent of the error for some galaxies, and apparently itis strongly coupled between the F814W and F850LP band-passes, so that M and M scatter in the same way (seethe following section for more discussion). We have there-fore omitted this part of the error in deriving the above fit, andadd only 0.015 mag to make χ n unity. This 0.015 mag rep-resents an allowance for differential intrinsic scatter betweenthe two bands, although it may include a small contributionfrom some additional measurement error.The first error bar on the constant coefficient in Equation (2)reflects the uncertainty from the fit, which is smaller than for F IG . 4.— SBF color ( m - m ) versus integrated color ( g - I ) forthe sample galaxies. There is some indication that this SBF color becomesslightly bluer as the galaxies get redder, but the slope of the plotted linear fitis significant at only the . σ level. Equation (1) because the scatter of the data points is lowerwhen using M . The second error bar gives our estimate ofthe systematic uncertainty including the 0.08 mag for the tieof the SBF method to the Cepheid scale (Tonry et al. 2000,2001; Ferrarese et al. 2000), 0.02 mag for the mean distanceof these galaxies from ACSFCS-V, and 0.04 mag for the pos-sible systematic error in the PSF normalization (Sec. 3.2). Itdoes not include the additional uncertainty in the Cepheid dis-tance scale, which may be of order ∼ . m - M ) and lineardistances d derived for the current sample using the cali-bration given by Equation (2). The tabulated distance uncer-tainties reflect the total random errors, including measurementerrors and the estimated 0.06 mag of intrinsic scatter. They donot include the systematic error in the calibration zero-point,which is common to all. Comparison with z -band SBF
It is useful to compare directly our I SBF magnitudes anddistance estimates with the z results from ACSFCS-V. Wefind a mean “SBF color” for these galaxies of m - m =0 .
72, with an rms of 0.027 mag. However, the SBF colordecreases slightly, or gets “bluer,” as the SBF magnitudes getfainter in redder galaxies, as shown in Figure 4, where thefitted relation including errors in both coordinates is given by m - m = (0 . ± . - (0 . ± .
18) [( g - I ) - . , (3)with an rms scatter of 0.021 mag. The significance of theslope is slightly less than 2 σ , but the same trend occurs asa function of ( g - z ), with the same scatter. It is not toounusual for the SBF color to become bluer while photomet-ric color becomes redder over some range in population pa-rameters, especially when age is increased at fixed metallicity(Blakeslee et al. 2001). However, SBF and color measure-ments would be needed for more galaxies in more bandpassesto place strong constraints on the underlying populations. Putanother way, the slope of m as a function of m is slightlyless than one, as shown in the left panel of Figure 5, where theplotted linear fit has slope 0 . ± .
06. The rms scatter aboutthis fit is 0.022 mag, which is consistent with random mea-surement errors, as the reduced χ n = 0 . m and m due to stellarpopulation effects must track closely between the two bands.The right panel of Figure 5 provides a comparison of theBF Distances 7 F IG . 5.— Left:
SBF m magnitude from this study is plotted against m from ACSFCS-V. The errors bars include only measurement error. The slope ofthe linear fit is 0 . ± .
06, and the residuals are shown at bottom, with the error bars here being the quadrature sums of the measurement errors.
Right:
Distancemodulus ( m - M ) ≡ ( m - M ) from the current study using the calibration in Equation (2) is plotted against distance modulus ( m - M ) ≡ ( m - M )from ACSFCS-V. The dotted line shows equality, and the differences between the distance moduli are shown as a function of their average at bottom. Theintrinsic component of the errors appears to be strongly correlated between the two bands; see text. distance moduli from the present work using Equation (2)with those from ACSFCS-V. The plotted line indicates unity,and the mean difference between the two sets of measure-ments is zero by design, since the distance moduli fromACSFCS-V went into deriving the M magnitudes usedfor the I calibration. The plotted error bars include the0.06 mag of intrinsic scatter for each band, and naively us-ing these errors, χ n ≈ .
1, which has only a ∼ . .
03 mag. Further, the tight correlation ensuresconsistency of the ACSFCS-V distances with those measuredhere, and thus with future F814W SBF studies that use ourcalibration. MODEL COMPARISON AND THE DISTANCE TO FORNAX
The SBF distance zero point used in this study is an empiri-cal one, ultimately tied to the metallicity-corrected Cepheiddistance scale. More specifically, it assumes a mean dis-tance of 16.5 Mpc to the Virgo cluster based on the Tonryet al. (2001) ground-based SBF distances recalibrated withthe final set of
HST
Key Project Cepheid distances of Freed-man et al. (2001); see Mei et al. (2005b) and Appendix A ofthe present work for further details. The mean distance of20 Mpc for the Fornax cluster then comes from the measured0 . ± .
03 magnitude offset between the Virgo and Fornax(ACSFCS-V).There is also a long history of attempts to calibrate the SBFmethod from stellar population modeling, thereby making itanother “primary” distance indicator not tied to the Cepheids (e.g., Worthey 1993; Buzzoni 1993; Blakeslee et al. 2001;Mei et al. 2001; Cantiello et al. 2003; Raimondo et al. 2005;Marin-Franch & Aparicio 2006). Biscardi et al. (2008) usedthe Teramo “SPoT” models (Raimondo et al. 2005) in orderto derive a theoretical linear calibration of the absolute SBFmagnitude in the ACS/WFC F814W bandpass as a function of( g - I ) color. This is the same combination of bandpassesas we have calibrated here from an empirical standpoint, al-though we work in the AB system while Biscardi used theVEGAMAG system. The slope is of course unaffected bythis difference, and their quoted value of 2 . ± . - . , - . , . , + .
3, and ages ranging from 3to 14 Gyr for each. We also show our measurements from Fig-ure 3, along with the fit from Equation (2). The lower panelis similar, but symbols are used to show the model values for6 different ages at each metallicity. The linear empirical cal-ibration overlaps remarkably well with the locus of the solarmetallicity models, which must be at least partly fortuitous,but consistent with the mean metallicities in these galaxiesbeing not too far from solar. The curve in the lower panel is acubic polynomial fit to the plotted models.Two things are particularly worthy of note in Figure 6. First, Blakeslee et al. F IG . 6.— Comparison of SBF observations with model predictions. Top: in-terpolated curves for Teramo SPoT models with metallicities [Fe/H] = - . , - . , . , + . Bottom: similar to the top panel, but here the models with differ-ent [Fe/H] are represented by symbols having three ( - . - . + .
3) points. Symbol size increases with age, and we plotmodel ages of 3 , , , , , and 13 Gyr. The curve shows a cubic polynomialfit to the plotted models. Over the range of the observations, the fitted modelrelation follows the empirical one fairly well, but the models predict morecurvature beyond this range, similar to what has been observed for M overa larger range of galaxy colors. there is remarkable consistency between the zero points of theobservations and models. In fact, the fits to data and mod-els cross very near the mean color of ( g - I ) = 1 .
2. Theexcellent agreement between two very different avenues forcalibrating the F814W SBF magnitudes suggests that neitheris likely to be far wrong, and thus the mean Fornax distanceof ∼
20 Mpc appears correct. Second, the fit to the modelpredictions indicates some curvature in the relation, similarto what we found in ACSFCS-V for the m magnitudes ofa larger sample of galaxies including dwarfs that extended tomuch bluer colors. Over the color range of the galaxies inour sample, the deviation between the linear and cubic fits issmall, so the linear calibration suffices. However, one shouldnot blindly apply this calibration beyond the fitted range, as itis reasonable to expect that the curvature may be significant. SUMMARY
We have measured SBF m magnitudes and ( g - I )colors for nine bright early-type galaxies in the Fornax clus-ter from new and archival HST
ACS/WFC imaging data. Weemployed two different analysis procedures for measuringthe SBF and found excellent agreement between them. Forthis sample of galaxies, which spans the color range 1 . < ( g - I ) < .
32 (AB mag), there is a clear trend of m with ( g - I ) that is well approximated by a linear rela-tion of slope ∼
2. We have used the z SBF distances fromACSFCS-V to obtain absolute M for all the galaxies andderive an empirical calibration of the I SBF method thatis consistent with the large sample of existing z SBF data.Because of the greater efficiency of the F814W bandpass, thelinear calibration defined by Equation (2) will allow accurateSBF distances to be measured with the ACS/WFC at greaterdistances than can be reached with the z band in the sameamount of time. For instance, 4 orbits in I suffices for anSBF distance to the Coma cluster at 100 Mpc, whereas ∼ z .The observed scatter in the calibration of M as a functionof ( g - I ) is only 0.03 mag, significantly smaller than theexpected ∼ z and I SBF relations,as expected from the similarity, and even partial overlap, ofthese passbands. Thus, stellar population effects cause the( m - M ) and ( m - M ) distance moduli to scatter inthe same direction, so that they are not fully independent. Di-rect comparison of the two sets of distances supports this con-clusion, which helps to ensure a high degree of consistencybetween SBF distances measured in these two bands.Comparison of our measurements with stellar populationmodel predictions provides support for the empirically-basedmean distance of 20 Mpc to the Fornax cluster. According tothese models, and by analogy to the broader-baseline z SBFcalibration, it is likely that the I SBF calibration will showcurvature beyond the color limits of our sample. Therefore,the calibration should not be linearly extrapolated far beyondthe range explored here. However, our sample was designedto have colors similar to those of the giant ellipticals targetedin more distant SBF studies; consequently, there should be lit-tle need for extrapolation. At least two different SBF studiesin the F814W bandpass are ongoing and can benefit from ourcalibration. We have emphasized the need for good PSF tem-plates in SBF measurements and the importance of investigat-ing systematic variations due to the PSF. Our results indicatethat when properly calibrated and controlled for systematics,the SBF method remains one of the most accurate ways ofmeasuring extragalactic distances.Support for this work was provided by NASA through grantnumber GO-10911 from the Space Telescope Science Insti-tute, which is operated by AURA, Inc., under NASA con-tract NAS 5-26555. M.C. acknowledges support from COFISASI-INAF I/016/07/0 and PRIN-INAF 2008 (PI. M. Mar-coni). A.J. acknowledges support from BASAL CATA PFB-06, FONDAP CFA 15010003 and MIDEPLAN ICM NucleusP07-021-F. This research made use of the NASA/IPAC Extra-galactic Database (NED) which is operated by the Jet Propul-sion Laboratory, California Institute of Technology, undercontract with NASA.
Facility:
HST (ACS/WFC)
APPENDIXA. SBF SURVEY DISTANCE CORRECTIONS
Tonry et al. (2001; hereafter in this appendix, T01) published distances for 300 galaxies from the ground-based I -band SBFSurvey of Galaxy Distances (Tonry et al. 1997). The median quoted uncertainty of 0.22 mag, just over 10% in distance, makesthis the largest catalogue of nearby galaxy distances with this level of precision. It has proven a useful resource for numerousBF Distances 9extragalactic studies. However, following the publication of our combined sample of 134 galaxies with high-quality ACS z -band SBF distances (median error 0.075 mag) and the direct comparisons for 50 galaxies in common with T01, there has beensome confusion over the possible need for correcting the T01 distances. As we have received more than a few queries on thisissue, we address here in detail the question of the T01 distances, as well as those of Jensen et al. (2003; hereafter J03).The ground-based SBF survey was conducted over numerous observing runs at multiple observatories with different types ofdetectors under variable seeing and photometric conditions during the course of a decade which saw great evolution in astro-nomical instrumentation and our own reduction software. It targeted galaxies ranging from the Local Group out to the fuzzy,condition-dependent limit of the ground-based SBF method. Although great effort was taken to homogenize the disparate datasets and produce the best possible set of final distances, the limitations of the data were already clear at the time; the authorsrecommended “further study of the degree of bias present in [the T01] data set” (see Sections 4 and 7 of T01).A separate issue was the zero point. The calibration of the T01 distance catalogue was based on comparisons to six galaxieswith HST
Key Project (KP) Cepheid distances as tabulated by Ferrarese et al. (2000), which yielded an M I zero point of - . - .
68 mag. If there were no distance-dependentbiases, then this simple shift in zero point would mean that all the T01 distance moduli just needed to be revised downwardby 0.06 mag. For instance, our ACSVCS papers applied this shift to the mean Virgo distance presented by T01, thus adopting31.09 mag, or 16.5 Mpc, for Virgo. This was a reasonably “safe” assumption, given that the six galaxies used to tie together theSBF and Cepheid distances extended out to the Virgo cluster, and were generally targeted in above-average observing conditions.Note that some researchers have misinterpreted this 0.06 mag shift as resulting from a change in the adopted Hubble constant,but there is no explicit dependence on the Hubble constant, only a dependence on the zero point of the Cepheid distances.In addition to rederiving the distance zero point based on the revised KP Cepheid distances, Blakeslee et al. (2002) found someevidence for distance bias in the lowest quality T01 data, in the sense that the relative distances tended to be underestimatedfor the lower quality data, as suspected by T01. This conclusion was based on comparisons with distances estimated from thefundamental plane and density field-corrected velocity measurements. Note that the absolute data quality generally decreaseswith distance, e.g., the errors increase with distance in T01, so this could potentially translate into a distance-dependent bias.Because of this combination of zero point and bias issues, Blakeslee et al. (2009) chose to compare the distances for the 50galaxies in common between the T01 and ACS data sets without first applying any shifts to T01. This contrasted with ourapproach in Mei et al. (2007), where the comparison was made only for Virgo galaxies and the zero-point shift from Blakesleeet al. (2002) was applied; this difference may have been the cause of some subsequent confusion. Blakeslee et al. (2009) foundthe same mean Fornax distance modulus to within ± .
01 mag as T01, without any shifting in zero point. However, the T01Virgo distance modulus is then necessarily too high by 0 .
06 mag. As compared to the ACS studies, the data tabulated by T01therefore give a smaller relative distance modulus of Fornax with respect to Virgo, although the uncertainties overlap. In lightof these results, it becomes unclear whether or not a simple shift in the zero point of the T01 distance moduli is useful withouta second-order correction that may depend on the distances of the galaxies under consideration. Given the 0.22 mag medianerror of the T01 distances, it could be argued that these effects are in the noise for any given galaxy. For galaxies within Virgoand Fornax, the tabulated ACS distances from Blakeslee et al. (2009) are much more accurate, and negligibly affected by thebackground variance corrections that were suggested to bias the ground-based data.However, for some purposes, it may be desirable to have a general correction formula for the published T01 distances, includingboth the zero point and second-order bias corrections. Given our high-quality measurements for a sizable fraction of the T01sample, we have attempted to derive one. We investigated possible correlations of the distance modulus difference ∆ T01 ≡ ( m - M ) ACS - ( m - M ) T01 , where ( m - M ) ACS comes from Blakeslee et al. (2009), with various quantities tabulated by T01 so that thecorrection is available for that full sample. In general, the correlations are weak, except between ∆ T01 and ( m - M ) T01 ; there is nosignificant correlation with ( m - M ) ACS . This is easily understood if the ACSFCS-V distances are taken as the “true” values, or atleast unbiased and homogeneous in quality; then the distance measurement error ∆ T01 will correlate strongly with the measureddistance over any limited range in true distance. But this correlation, caused by measurement error, cannot be used to bias-correctthe measured distances for the full sample. There is no correlation of ∆ T01 with the quoted measurement error, perhaps becauseof the relatively small range in the latter quantity and the multitude of effects that contribute to it.It seemed more promising to investigate correlations with parameters that directly reflect the data quality. It is also necessaryfor the correction parameter to span reasonably well the same range in the current subsample as in the complete T01 catalogue.T01 supplied two measures of the quality of the data for each galaxy. One such parameter, called PD , was the normalized productof the width of the seeing disk in arcseconds and the expected distance based on the galaxy recessional velocity in units of 1000km s - , thus making it independent of any potential distance biases in the SBF distance measurement itself. PD is proportional tothe linear size of the resolution element at the distance of the galaxy, and thus is smaller for better quality data. Another measureof data quality, called Q by T01 and here referred to as Q T01 , scaled logarithmically with the ratio of the signal-to-noise and PD ;thus it is larger for better quality data. Blakeslee et al. (2002) investigated bias as a function of PD ; we have found a slightlymore significant trend as a function of Q T01 . Figure 7 shows ∆ T01 plotted against Q T01 . The fitted relation suggests that the T01distance moduli can be bias-corrected according to( m - M ) T01 , cor = ( m - M ) T01 , raw + . - . Q T01 (A1)= ( m - M ) T01 , raw - . Q T01 - . . Thus, as published without any zero-point shifting, the poorest quality T01 distances with Q T01 ≈ ∼ + Q T01 ≈ ∼ - Q T01 inFigure 7, we do not recommend applying corrections any larger than this. The six Cepheid calibrator galaxies have an average0 Blakeslee et al. F IG . 7.— Difference between the Tonry et al. (2001) distance moduli and the ACSFCS-V distance moduli, defined such that ∆ T01 = ( m - M ) ACS - ( m - M ) T01 , isplotted as a function of the Tonry et al. observation quality Q T01 for the 50 galaxies in common between the two samples. Note that the typical error on ∆ T01 is ∼ .
23 mag, so the scatter is expected to be large. See Appendix for details. h Q T01 i = 6 .
0, giving h ∆ T01 i = - .
08 mag, (or, omitting the Local Group galaxy M31: h Q T01 i = 5 . h ∆ T01 i = - .
06 mag), veryclose to the expected shift from the Cepheid calibration, which is included within the correction formula. The significance ofthe fitted slope is only 1 . σ based on these 50 galaxies, and the relative Fornax–Virgo distance modulus from the sample isunchanged, but if the trend persisted for the full T01 sample of 300 galaxies, the significance would reach 4 σ ; therefore studiesrelying on many T01 galaxy distances may benefit from applying a correction such as Equation (A1).Finally, we address the J03 HST /NICMOS F160W SBF distances for 65 galaxies. These were tied to the KP Cepheid distancesfrom Freedman et al. (2001), but without the espoused - - metallicity correction. The evidence for this correction wasambiguous at the time, and J03 found that the agreement with SBF predictions from stellar population models was better whenthe distance zero point was based on the Cepheid results without metallicity correction. Since then, there has been additionalevidence to support a Cepheid metallicity dependence (Sakai et al. 2004; Macri et al. 2006; Scowcroft et al. 2009), and betterunderstanding of the uncertainty in model predictions for near-IR SBF (Raimondo 2009; González-Lópezlira 2010; Lee et al.2010). Given the high signal-to-noise and good resolution of the J03 NICMOS data, there is no reason to suspect a bias similar tothat of T01. However, to bring them into agreement with other work requires putting them on the Cepheid scale that includes themetallicity correction. J03 derived their distance zero point by comparison to 47 T01 galaxies after shifting the distance moduliby - .
16 mag, which comes from repeating the Tonry et al. (2000) calibration using the revised Cepheid distances withoutmetallicity correction. As noted above, the change in the T01 moduli when calibrated on the revised Cepheid distances withmetallicity correction is - .
06 mag. This suggests a shift of + .
10 mag to the Jensen et al. distance moduli, although there issome question about possible bias in the particular subsample of T01 that was used. J03 also measured SBF in nine KP Cepheidgalaxies and tabulate the resulting M values for the distances with and without metallicity correction; the mean difference is0.08 mag, which is consistent with the shift in the T01 calibration caused by the metallicity correction. We therefore concludethat the J03 distance moduli should be increased uniformly by + z SBF measurements, and the present work.
B. ADDITIONAL ACSVCS DWARF GALAXY DISTANCES
Mei et al. (2007) published SBF measurements for 90 galaxies from the ACSVCS g and z imaging data, and Blakesleeet al. (2009) tabulated recalibrated distances for these along with the 43 ACSFCS galaxies and NGC 4697 in the Virgo SouthernExtension. No SBF measurements were published for ten of the ACVCS galaxies, mainly owing to irregular morphologies.However, the problem for the galaxies VCC 1192 and VCC 1199 was different: they are both compact elliptical companions ofthe Virgo brightest cluster galaxy M49 (NGC 4472 or VCC 1226) and the strong background gradient from the giant galaxy’shalo caused the photometric measurements for these galaxies to be unreliable. Since the physical distances from M49 of theselikely stripped (Ferrarese et al. 2006; Côté et al. 2010) companions are of interest, we have undertaken new measurements ofthese two galaxies. Although not directly related to the main content of this paper, these data are part of our larger HST
SBFeffort, and we present them here.We constructed initial isophotal models of the light distributions of VCC1192 and VCC1199 in each filter. We then subtractedthese models, masked the background sources, and interpolated two-dimensional cubic spline surfaces on a 16 ×
16 grid (eachgrid cell being ∼
270 pix on a side) to make smooth fits of the background light distribution. Since these galaxies are so compact,and they had been removed by the initial models, they did not perceptibly affect the fits. After subtraction of the fitted surfaces,the backgrounds were extremely flat. We then constructed a new galaxy model for each and proceeded with the SBF and colormeasurements as usual, using the same code as in the present work. Table 3 presents our measurements for these galaxies in thesame format as for the other ACSVCS galaxies in Table 2 of Blakeslee et al. (2009). This brings the total number of galaxieswith measured z SBF distances to 136.BF Distances 11
REFERENCESAjhar, E. A., Lauer, T. R., Tonry, J. L., Blakeslee, J. P., Dressler, A.,Holtzman, J. A., & Postman, M. 1997, AJ, 114, 626Barber DeGraaff, R., Blakeslee, J. P., Meurer, G. R., & Putman, M. E. 2007,ApJ, 671, 1624Binggeli, B., Sandage, A., & Tammann, G.A., 1985, AJ, 90, 1681Biscardi, I., Raimondo, G., Cantiello, M., & Brocato, E. 2008, ApJ, 678, 168Blakeslee, J. P. 1999, AJ, 118, 1506Blakeslee, J. P., Anderson, K. R., Meurer, G. R., Benítez, N., & Magee, D.2003, Astronomical Data Analysis Software and Systems XII, 295, 257Blakeslee, J. P., Lucey, J. R., Tonry, J. L., Hudson, M. J., Narayanan, V. K.,& Barris, B. J. 2002, MNRAS, 330, 443Blakeslee, J. P., Tonry, J. L., & Metzger, M. R. 1997, AJ, 114, 482Blakeslee, J. P., Vazdekis, A., & Ajhar, E. A. 2001, MNRAS, 320, 193Blakeslee, J. P., et al. 2006, ApJ, 644, 30Blakeslee, J. P., et al. 2009, ApJ, 694, 556 (ACSFCS-V)Bohlin, R. C. 2007, Instrument Science Report ACS-2007-006 (Baltimore:STScI)Buzzoni, A. 1993, A&A, 275, 433Cantiello, M., Blakeslee, J. P., Raimondo, G., Mei, S., Brocato, E., &Capaccioli, M. 2005, ApJ, 634, 239Cantiello, M., Blakeslee, J., Raimondo, G., Brocato, E., & Capaccioli, M.2007a, ApJ, 668, 130Cantiello, M., Raimondo, G., Blakeslee, J. P., Brocato, E., & Capaccioli, M.2007b, ApJ, 662, 940Cantiello, M., Raimondo, G., Brocato, E., & Capaccioli, M. 2003, AJ, 125,2783Côté, P., et al. 2004, ApJS, 153, 223Côté, P., et al. 2010, ApJ, submittedDunn, L. P., & Jerjen, H. 2006, AJ, 132, 1384Ferguson, H.C. 1989, AJ, 98, 367Ferrarese, L., et al. 2000, ApJ, 529, 745Ferrarese, L., et al. 2006, ApJS, 164, 334Freedman, W. L., et al. 2001, ApJ, 553, 47Freedman, W. L., & Madore, B. F. 2010, arXiv:1004.1856Fruchter, A. S. & Hook, R. N. 2002, PASP, 114, 144González-Lópezlira, R. A., Bruzual-A., G., Charlot, S., Ballesteros-Paredes,J., & Loinard, L. 2010, MNRAS, 403, 1213Hubble, E. 1929, Proceedings of the National Academy of Science, 15, 168Hubble, E. P. 1926, ApJ, 64, 321Jensen, J. B., Tonry, J. L., Barris, B. J., Thompson, R. I., Liu, M. C., Rieke,M. J., Ajhar, E. A., & Blakeslee, J. P. 2003, ApJ, 583, 712 (J03)Jensen, J. B., Tonry, J. L., & Luppino, G. A. 1998, ApJ, 505, 111Jensen, J. B., Tonry, J. L., Thompson, R. I., Ajhar, E. A., Lauer, T. R., Rieke,M. J., Postman, M., & Liu, M. C. 2001, ApJ, 550, 503 Jordán, A., Blakeslee, J. P., Côté, P., Ferrarese, L., Infante, L., Mei, S.,Merritt, D., Peng, E. W., Tonry, J. L., West, M. J. 2007, ApJS, 169, 213Jordán, A., Blakeslee, J. P., Peng, E. W., Mei, S., Côté, P., Ferrarese, L.,Tonry, J. L., Merritt, D., Milosavljevi´c, M., West, M. J. 2004, ApJS, 154,509Krist, J. 2003, STScI Instrument Status Report ACS2003-06Leavitt, H. S. 1908, Annals of Harvard College Observatory, 60, 87Lee, H.-c., Worthey, G., & Blakeslee, J. P. 2010, ApJ, 710, 421Liu, M. C., Graham, J. R., & Charlot, S. 2002, ApJ, 564, 216Lorenz, H., Bohm, P., Capaccioli, M., Richter, G. M., & Longo, G. 1993,A&A, 277, L15Macri, L. M., Stanek, K. Z., Bersier, D., Greenhill, L. J., & Reid, M. J. 2006,ApJ, 652, 1133Marín-Franch, A., & Aparicio, A. 2006, A&A, 450, 979Mei, S., Blakeslee, J.P., Tonry, J.L., Jordán, A., Peng, E.W., Côté, P.,Ferrarese, L., Merritt, D.; Milosavljevi´c, M., & West, M.J. 2005a, ApJS,156, 113Mei, S., Blakeslee, J.P., Tonry, J.L., Jordán, A., Peng, E.W., Côté, P.,Ferrarese, L., West, M.J., Merritt, D., & Milosavljevi´c, M. 2005b, ApJ,625, 121Mei, S., Blakeslee, J. P., Côté, P., Tonry, J. L., West, M. J., Ferrarese, L.,Jordán, A., Peng, E. W., Anthony, A., & Merritt, D. 2007, ApJ, 655, 144Mei, S., Quinn, P. J., & Silva, D. R. 2001, A&A, 371, 779Mieske, S., Hilker, M., & Infante, L. 2003, A&A, 403, 43Neilsen, E. H., Jr., & Tsvetanov, Z. I. 2000, ApJ, 536, 255Pahre, M. A., et al. 1999, ApJ, 515, 79Raimondo, G. 2009, ApJ, 700, 1247Raimondo, G., Brocato, E., Cantiello, M., & Capaccioli, M. 2005, AJ, 130,2625Sakai, S., Ferrarese, L., Kennicutt, R. C., Jr., & Saha, A. 2004, ApJ, 608, 42Schlegel, D.J., Finkbeiner, D.P., & Davis, M. 1998, ApJ, 500, 525Scowcroft, V., Bersier, D., Mould, J. R., & Wood, P. R. 2009, MNRAS, 396,1287Sirianni, M., et al. 2005, PASP, 117, 1049Tonry, J.L. 1991, ApJ, 373, L1Tonry, J.L., Ajhar, E.A., & Luppino, G.A. 1990, AJ, 100, 1416Tonry, J. L., Blakeslee, J. P., Ajhar, E. A., & Dressler, A., 1997, ApJ, 475,399Tonry, J. L., Blakeslee, J. P., Ajhar, E. A., & Dressler, A., 2000, ApJ, 530,625Tonry, J.L., Dressler, A., Blakeslee, J.P., Ajhar, E.A., Fletcher, A.B.,Luppino, G.A., Metzger, M.R., & Moore, C.B. 2001, ApJ, 546, 681 (T01)Tonry, J.L., & Schneider, D.P. 1988, AJ, 96, 807Worthey, G. 1993, ApJ, 409, 530
TABLE 1G
ALAXY D ATA
Galaxy B T Morph v h Other T F475 T F814 ( m - M ) Program(1) (2) (3) (4) (5) (6) (7) (8) (9)NGC 1316 9.4 S0 pec 1760 FCC 21 760 4680 31 . ± .
065 10217,9409NGC 1344 11.3 E5 1169 NGC 1340 760 960 31 . ± .
068 10217,9399NGC 1374 11.9 E0 1294 FCC 147 680 1224 31 . ± .
070 10911NGC 1375 13.6 S0 740 FCC 148 680 1224 31 . ± .
072 10911NGC 1380 11.3 S0/a 1877 FCC 167 680 1224 31 . ± .
075 10911NGC 1399 10.6 E1 1425 FCC 213 680 1224 31 . ± .
091 10911NGC 1404 10.9 E2 1947 FCC 219 680 1224 31 . ± .
072 10911NGC 1427 11.8 E4 1388 FCC 276 680 1224 31 . ± .
068 10911IC 2006 12.2 E2 1382 ESO 359-07 680 1224 31 . ± .
086 10911 N OTE . — Columns list: (1) galaxy name; (2) total B magnitude from the FCC (Ferguson1989) or NED; (3) morphological type from the FCC or NED; (4) heliocentric velocity fromNED (km s - ) (5) alternative galaxy designation; (6) HST /ACS exposure time for the F475Wbandpass (sec); (7)
HST /ACS exposure time for the F814W bandpass (sec); (8) distancemodulus and uncertainty from z -band SBF (ACSFCS-V); (9) HST program IDs for theobservations used in this study.
TABLE 2G
ALAXY C OLOR AND
SBF M
EASUREMENTS
Galaxy ( g - I ) m ( m - M ) d (Mpc)(1) (2) (3) (4) (5)NGC 1316 1 . ± .
011 30 . ± .
020 31 . ± .
066 21 . ± . . ± .
015 30 . ± .
039 31 . ± .
076 21 . ± . . ± .
022 30 . ± .
015 31 . ± .
074 19 . ± . . ± .
009 30 . ± .
037 31 . ± .
072 20 . ± . . ± .
011 30 . ± .
016 31 . ± .
065 20 . ± . . ± .
017 30 . ± .
022 31 . ± .
071 21 . ± . . ± .
014 30 . ± .
018 31 . ± .
068 20 . ± . . ± .
019 30 . ± .
017 31 . ± .
072 19 . ± . . ± .
016 30 . ± .
035 31 . ± .
075 20 . ± . N OTE . — Columns list: (1) galaxy name; (2) mean galaxy ( g - I )color; (3) mean SBF magnitude m ; (4) distance modulus derived fromthe linear I SBF calibration presented here; (5) the distance in Mpc.The distance errors include contributions from SBF and color measure-ment errors, as well as the estimated intrinsic (“cosmic”) scatter in themethod.
TABLE 3D
ISTANCES FOR A DDITIONAL
ACS V
IRGO C LUSTER S URVEY G ALAXIES
Galaxy ( g - z ) m z ( m - M ) d B T Name(1) (2) (3) (4) (5) (6) (7)VCC1192 1 . ± .
009 29 . ± .
065 31 . ± .
091 16 . ± . . ± .
030 29 . ± .
169 31 . ± .