Zeropoints

For convenience, the ACS Team implemented the Zeropoint Calculator webtool to compute time-dependent zeropoints for all supported observing modes as well as a python module within ACSTOOLS, acszpt. We strongly advised users to use this calculator or python module to compute the zeropoints required for photometric calibration of their observation. For convenience, we provide examples below demonstrating how to use the acszpt module on this webpage. 

This webpage contains information for how to calibrate photometric measurements made with the HST/ACS instrument. There are several supporting documents linked below which give a more detailed explanation of many topics and methods used to in the photometric calibration of the ACS instrument. The topics on this page will be suitable for most users performing basic aperture photometry. Aperture correction tables can be found on the Aperture Corrections webpage.

Bohlin 2016 and Bohlin 2020 (hereafter  ACS ISR 2016-03 and ACS ISR 2020-08) continue the work documented in ACS ISR 2011-02, ACS ISR 2011-03, and ACS ISR 2012-01 by performing the most precise set of flux calibration for the HRC and WFC cameras to date.

In ACS ISR 2016-03, the data are comprised of ~18 orbits of the primary hot white dwarf stars G191B2B, GC153, and GD71, which are used to define the ACS flux calibration and its change over time, spanning a ~7 year period from August 2009 to March 2016. The average decline in sensitivity was 0.061% ± 0.007% per year across all filters, which differs at most by <1σ from the measured rate of 0.035% ± 0.037% for F850LP; therefore, the average loss rate was adopted for all WFC data taken after SM4 (2009.4). Even with gain adjustments made after the revival of the ACS WFC to match post-SM4 photometry to 2002.4 epoch photometry of 47 Tuc for F606W (ACS ISR 2011-03), an additional (small) shift in sensitivity by 0.997 improves the match at F606W. These adjustments range from 0.996 to 1.007 for the other filters. After applying corrections for sensitivity loss and renormalizing, the new observations and newly reprocessed data for F435W and F814W required shifts to each filter's bandpass transmission function to reduce the maximum error. Once all of the adjustments are made, the fully corrected photometry at the WFC1-1K reference point in the eight broadband filters achieves the 1% precision goal. Comparing the WFC PHOTFLAM results of ISR ACS ISR 2016-03 with Sirianni et al. (2005) for 2002.16 epoch reveals differences ranging from 5% smaller for F660N to 1% larger for F550M, while the eight broadband filters are 1−3% smaller. For the HRC, differences range from 0−3% smaller, except for F344N, where the new calibration is 3% larger. These differences are due mostly to changes in the CALSPEC reference spectral energy distributions (SEDs) and to a refined and expanded set of ACS observations of these standard stars.

In ACS ISR 2020-08, the analysis of sensitivity changes with time began to incorporate data from a fourth white-dwarf (secondary) standard (GRW+70D 5824), starting from Cycle 25 (late-2017) onwards. With this addition (and a longer baseline of data), the reported decline in sensitivity is now determined to be 0.0574% ± 0.0066% per year averaged across all filters, within 1σ of the results from ACS ISR 2016-03. Updated spectral energy distributions for the three primary white dwarf standards were incorporated in this analysis following the same framework as ACS ISR 2016-03, and updated values for flux calibration were delivered to the ACS reduction pipeline starting October 12, 2020.

The most recent calibration of the ACS/SBC zeropoints was undertaken by Avila et al. (ACS ISR 2019-05). Spectroscopic and imaging observations of a half dozen stars in the calibration field NGC6681 were used to derive corrections to the imaging mode throughput curves derived on the ground and immediately after installation of the camera (Tran et al. 2002a, Tran et al. 2002b, Sirianni et al. 2002). A study of the time-dependent sensitivity has also shown that time varying zeropoints are required to maintain accurate calibration (ACS ISR 2019-04). The sensitivity has been measured to drop by ~0.5% per year, on average. 

Beginning in 2019, calibrated FLT images obtained from the MAST archive contain the date appropriate inverse sensitivity values in the headers. The examples below can also be used to generate zeropoints for the SBC imaging modes, if one does not want to re-download their data. 

Here we define several terms generally used in the photometric analysis of HST/ACS observations.

Flux 

The average flux F (units: erg cm⁻² s⁻¹ Å⁻¹) over an ACS bandpass is F= N x PHOTFLAM, where N is the count rate in an infinite aperture. For count rates N_ap in a given aperture, N=N_ap/EE where EE is the fractional encircled energy. Encircled energy curves may be found on the Aperture Corrections webpage. For more general information, see chapter 5 of the ACS Data Handbook. For instrument specific information see ISR 2016-03 (HRC and WFC)  or ISR 2016-05 (SBC).

VegaMag 

The magnitude system in which Vega has an apparent magnitude of 0 at all wavelengths. Using the flux spectrum of Vega from the CALSPEC archive (F_Vega), the magnitude of a star with flux F in the VegaMag system is:

• \(m = −2.5*log_{10}(F/F_{Vega})\)

The latest version of the Vega spectrum is available on CALSPEC as alpha_lyr_sts_011.fits

STMag and ABMag

These magnitude systems differ from the VegaMag system in that they have an artifical reference flux for conversion to magnitude. The reference flux for STMag (3.63×10⁻⁹ erg cm⁻² s⁻¹ Å⁻¹) is flat in wavelength space, while the reference for ABMag (3.63×10⁻²⁰ erg cm⁻² s⁻¹ Hz⁻¹) is flat in frequency space. The conversion between flux density and magnitude for these photometric systems are:

• \(STMag = −2.5*log_{10}(F_{\lambda})−21.10 \)
• \(ABMag = −2.5*log_{10}(F_{\nu})−48.60\)​

Here we describe several header keywords present in ACS FITS files. These keywords can be used to obtain photometric calibration information for your data.

• PHOTMODE: Observation configuration for photometric calibration.
• PHOTFLAM: Inverse sensitivity (units: erg cm⁻² Å⁻¹ electron⁻¹). This represents the scaling factor necessary to transform an instrumental flux in units of electrons per second to a physical flux density.
• PHOTZPT: STMag zeropoint.
• PHOTPLAM: Pivot wavelength (units: Å)

The PHOTFLAM and PHOTPLAM header keywords are used to derive the instrumental zeropoint magnitudes, which are defined to be the magnitude of an object that produces one count per second. The instrumental magnitudes are defined as follows:

• \(ZP_{ST} = −2.5*log_{10}( PHOTFLAM )−21.10\)

• \(ZP_{AB} = −2.5*log_{10}( PHOTFLAM )-5*log_{10}⁡( PHOTPLAM )−2.408\)

In addition to being present in the image headers, the PHOTFLAM value for a given date can be calculated using the acszpt module. See the Examples below.

Calculating the Zeropoints for a Specific Date

The gradual loss in instrument sensitivity of the ACS detectors necessitates timedependent zeropoints. These time-dependent zeropoints can be retrieved via the web interface, ACS Zeropoints Calculator, or programmatically via the acszpt module. Below we demonstrate how to use the acszpt to generate zeropoints for the ACS/WFC detector on an arbitrarily chosen date:

from acstools import acszpt                                                       

# Specify the date, must be in ISO Format (YYYY-MM-DD)
date = '2016-04-01'                                                               

# Specify the detector
detector = 'WFC'                                                                  

# Create an instance of the Query class
q = acszpt.Query(date=date, detector=detector)                                    

# Fetch the results for all filters
zpt_table = q.fetch()

# Create an instance and search for a specific filter
q_filter = acszpt.Query(date=date, 
                        detector=detector, 
                        filt='F435W')

# Fetch the results for the F435W filter
filter_zpt = q_filter.fetch()

Converting Between Instrumental and Physical Fluxes/Magnitudes

In this example, we have a measurement of the fluxes of several point sources in 0.2 arcsecond (4 pixel) radius apertures using the ACS/WFC camera and the F555W filter taken on Jan 1, 2017. First, we will apply an aperture correction to our measurements. Aperture corrections from a variety of radii to the infinite aperture radius can be found on the Aperture Corrections webpage.  After the aperture corrections have been applied, we use the acszpt module to generate the STmag, ABmag, and VegaMag zeropoints and use them to convert the instrument magnitudes to physical magnitudes.

from acstools import acszpt
import numpy as np
from astropy.table import Table

# Create some fake fluxes in electrons per second.
instrumental_flux = np.array([5.2393, 7.2935, 3.2355, 4.9368])

# Apply the correction from 0.2" to infinity.
# For F555W, the correction is 0.841
correction_inf = 0.841
flux_inf = instrumental_flux / correction_inf

# Query the zeropoint calculator for the F555W zeropoint information
q = acszpt.Query(date='2017-01-01', detector='WFC', filt='F555W')
filter_zpt = q.fetch()

# Now convert instrumental fluxes to physical fluxes and magnitudes.
# F_lambda is the flux density in units of erg/sec/cm^2/Angstrom.
F_lambda = flux_inf * filter_zpt['PHOTFLAM']
m_st = -2.5 * np.log10(flux_inf) + filter_zpt['STmag'][0].value
m_ab = -2.5 * np.log10(flux_inf) + filter_zpt['ABmag'][0].value
m_vega = -2.5 * np.log10(flux_inf) + filter_zpt['VEGAmag'][0].value

# Assemble the values into an Astropy Table. Note that we could
# attach units to these columns, however advanced Astropy
# Tables use is outside the scope of this example.
phot_table = Table({'Measured Flux': instrumental_flux, 'F_lambda': F_lambda,
                    'ST Mag': m_st, 'AB Mag': m_ab, 'Vega Mag': m_vega}, 
                   names=['Measured Flux', 'F_lambda', 'ST Mag', 'AB Mag', 'Vega Mag'])

An extensive PASP paper (Sirianni et al. 2005) that discusses the ACS Photometric Calibration and Photometric Transformations is available. The photometric calibration has been improved over the years, however this paper still remains the fundamental text for transformations to other filter systems.

Sirianni et al. (2005) provides the coefficients to translate ACS photometry to other well known photometric systems. Coefficients are provided for transformations between WFC and HRC, providing internal consistency. It also provides conversion from ACS to WFPC2 and from ACS to the Landolt UBVRI system. In general, two sets of transformations are available: the first based on observation of two star clusters and the second based on synthetic photometry. These transformations should be used with appropriate caution – the paper discusses the accuracy of these transformations and their sensitivity to details of the spectra being transformed, such as extreme color (intrinsic or due to reddening or redshift) or unusual SED. The paper also contains a photometric calibration cookbook and detailed information about the aperture correction to be applied to point source photometry when using the ACS zeropoints.

ACS ISR 2019-10 presented color corrections between Johnson V and ACS magnitudes for all three ACS channels, and between GALEX NUV and FUV for ACS/SBC magnitudes, considering a variety of target spectra. These were derived via synthetic photometry with pysynphot (now superseded by stsynphot). The color corrections can be found in Tables 10.1 through 10.5 in the ACS IHB, and are updated as needed to reflect changing sensitivities.

• Avila, R. J., Chiaberge, M. 2016, ACS ISR 2016-05
• Bohlin, R. C. 2011, ACS ISR 2011-02
• Bohlin, R. C. 2012, ACS ISR 2012-01
• Bohlin, R. C. 2016, ACS ISR 2016-03
• Bohlin, R. C., Mack, J., & Ubeda L. 2011, ACS ISR 2011-03
• Tran, H. D., et al. 2002a, 2003SPIE.4854..686T
• Tran, H. D., et al. 2002b, 2002 HST Calibration Workshop
• Sirianni, M. et al. 2002, 2002 HST Calibration Workshop
• Sirianni, M. et al. 2005, PASP, 117, 1049S