=20

=20

=20
=20

=20
=20
# Concept

# Components

## "a" terms

## "k" terms

## Flat field

# Non-photom=
etric data

# Application=
details

# Abso=
lute Calibration

=20
Relative zero points for the PS1 images are determined by the photometri= c calibration algorithm of Schlafly et al. (2012), which refines the photom= etric calibration algorithm of Padmanabhan et al. (2008), used in the Sloan= Digital Sky Survey. The throughput of the system is modeled with as a cons= tant system throughput and atmospheric k-term each night. The model is dete= rmined by finding the parameters of the model that minimize the variance in= flux of repeated observations of the same sources. The photometric calibra= tion also simultaneously fits for a low resolution flat field correction ve= ctor and a trend in system throughput with PSF.

Contents

=20

- =20
- Concept = =20
- Components=20
- =20
- "a" t= erms =20
- "k" t= erms =20
- Flat field= =20

=20
- Non-= photometric data =20
- Appli= cation details =20
- Abso= lute Calibration =20

The starting point for the PS1 data archive is at The Pan-STARRS1 data archive home= page.

The relative zero points for the PS1 survey are determined by minimizing= the variance in the fluxes of repeated observations of the same stars, in = the context of a simple model for the system throughput, as described in Sc= hlafly et al. (2012). The relative zero points bring instrumenta= l magnitudes onto a common scale, independent of the night on which they we= re taken, of the transparency of the night sky on that night, and of the lo= cation in the focal plane the star was observed.

The model has three basic terms: a nightly system zero point a; a nightl= y atmospheric transparency k; and a seasonal flat field f. The overall zero= point is given by Z =3D a - k*x + f, where a is the system zero point on t= he night of the observation, k is the atmospheric transparency on that nigh= t, x is the airmass of the observation, and f is the term in the appropriat= e seasonal flat field for that observation. The terms of this model are det= ermined by solving for the parameters a, k, and f that minimize the varianc= e in repeat observations of the same sources over the course of the PS1 sur= vey.

The model treats the different filters completely independently, and so = is, in effect, five separate independent models. Each model is compos= ed of a set of a & k terms and a flat field vector f. Two additio= nal parameters in each filter account for a small variation in measured flu= x as a function of PSF size.

Each night of the survey with observations in a given filter are fit wit= h a constant "a" term, intended to give the telescope + camera throughput o= n that night. There are roughly 1000 nights of observations in any gi= ven filter in the PS1 survey, making for 1000 a terms fit in the model.

Each night of the survey with observations in a given filter are fit wit= h a "k" term, which is intended to describe the transparency of the atmosph= ere on that night. The typical overall nightly zero points are determ= ined by Z =3D a - k*x, where x is the airmass of a particular observation. = There are again roughly 1000 k terms fit per filter, corresponding to= each of about 1000 nights of observations in that filter.

A flat field correction is fit simultaneously with the other parameters of =
the survey. The linear fit routines (i.e., SVD decomposition to perfo=
rm matrix inversion) we adopt in the photometric calibration limits the num=
ber of free parameters we can fit simultaneously, which places a limit on t=
he resolution we can achieve. We choose to split each PS1 chip into 4=
quadrants, making for a 240 element flat field vector. We allow the =
flat field to vary with time, defining 5 "seasons" at which the flat field =
changes discontinuously: MJDs 54900, 55296, 55327, 55662, and 56110. &=
nbsp;

The rms of the overall flat field correction is about 15 mmag; the rm=
s in the seasonal corrections to this overall flat field are only about 5 m=
mag.

The relative calibration model for the survey zero points is very rigid;= ignoring relatively small flat field correction, it is composed of only tw= o numbers per night. On nights where there is significant cloud coverage th= e atmospheric transparency varies dramatically on short time scales; such v= ariation is not accommodated in this simple model. Accordingly, images take= n in non-photometric conditions must be excluded from the simple model for = the system throughput. Approximately 25% of 3pi images are excluded. = These images are identified through their residuals; stars observed t= hrough clouds appear too faint relative to their mean magnitudes, and stars= observed through patchy clouds additionally show high dispersion. Th= e photometric calibration algorithm iteratively applies more and more aggre= ssive clipping to remove images and chips with large mean residuals and lar= ge residual variances. Additionally, preliminary QA plots are inspect= ed visually for signatures of non-photometric conditions, and non-photometr= ic periods are marked by hand as bad, mostly to prevent the algorithm from = trying to find one photometric image in a sea of non-photometric images on = a night.

Some of this data can be recovered by assigning individual non-photometr= ic images zero points that best bring them into agreement with the calibrat= ed photometric data, though a significant amount of non-photometric data is= very non-photometric, where a single zero point per exposure is not satisf= actory. A night of imaging may be largely photometric with a few non-photom= etric periods; in this case, only the non-photometric periods are excluded = from the calibration. Despite the very rigid model, for the 75% of images t= aken in photometric conditions, the model zero points seem to be very close= to the true zero points. If we allow any individual image to float and sol= ve for its zero point independently, forcing it to the global solution, the= typical difference in zero point is <5 mmag, presumably stemming from u= nmodeled variations in the night sky transparency.

The operational application of relative zero points is non-trivial= . PS1 single-epoch data (SMF files) are downloaded to Harvard and processed= to obtain relative zero points. These zero points are adopted in the "relp= hot" analysis, which additionally solves for zero points of the non-photome= tric data by tying it to photometric data when possible, or by solving for = a more relaxed photometric model (single zero point per exposure) when no p= hotometric data is available . The relphot analysis deriv= es zero points for the non-photometric data and together with the zero poin= ts determined above derives mean magnitudes for all stars in the survey, wh= ich eventually become the photometric portion of the PS1 reference catalog.= Once a reference catalog has been constructed, future processed data is ti= ed to the reference catalog using a single zero point per processing unit, = which can be image or skycell depending on the product being analyzed. I'm = not sure if the final single-epoch data making it to e.g. PSPS is calibrate= d in the sense that it has had the original relative zero point applied, or= that it has been tied to the reference catalog, which used the original re= lative zero points. However, the difference between these two approaches is= expected to be <5 mmag.

The PS1 Absolute photometric calibration combines accurate measurement= s of the filter bandpass edges and throughput curves with measurements of H= ST Calspec standards with the PS1 system.

=20

=20
=20

=20