Index: /trunk/doc/release.2015/ps1.analysis/analysis.tex =================================================================== --- /trunk/doc/release.2015/ps1.analysis/analysis.tex (revision 41332) +++ /trunk/doc/release.2015/ps1.analysis/analysis.tex (revision 41333) @@ -100,6 +100,6 @@ images from other telescopes. We describe the analysis of the astronomical sources by \ippprog{psphot} in general as well as for the -specific case of the 3rd processing version used for the first \textmod{two public -releases} of the Pan-STARRS $3\pi$ survey data. +specific case of the 3rd processing version used for the first +\textmod{two public releases} of the Pan-STARRS $3\pi$ survey data. \end{abstract} @@ -156,6 +156,6 @@ partners collaborate with the Pan-STARRS team to harvest the transient sources such supernovae and graviational wave counterparts. A second -Pan-STARRS telescope \citep[PS2][]{chambers2017,chambers2020}, -generally matching the PS1 design \citep{Morgan2012} has since been +Pan-STARRS telescope \citep[PS2][Chambers et al 2020 in prep]{chambers2017}, +generally matching the PS1 design \citep{2012SPIE.8444E..0HM} has since been constructed and has been producing science results since early 2018. @@ -281,10 +281,10 @@ The photometric and astrometric precision goals for the Pan-STARRS\,1 -surveys were quite stringent. The astrometric goals were relative astrometric accuracy of 10 milliarcseconds -and absolute astrometric accuracy of 100 milliarcseconds with respect -to the ICRS reference stars. For photometry, the goal was 10 -millimagnitudes accuracy within the internal photometric system across -the sky, though the tie to an absolute standard was not required to -meet this standard. +surveys were quite stringent. The astrometric goals were relative +astrometric accuracy of 10 milliarcseconds and absolute astrometric +accuracy of 100 milliarcseconds with respect to the ICRS reference +stars. For photometry, the goal was 10 millimagnitudes accuracy +within the internal photometric system across the sky, though the tie +to an absolute standard was not required to meet this standard. An additional constraint on the Pan-STARRS analysis system comes from @@ -303,8 +303,8 @@ efficient. Not only is it necessary to make a careful measurement of the flux of individual sources, it is also critical to characterize -the image point spread function (PSF), and its variations across the field -and from image to image. Since comparisons between images must be -reliable, the measurements must be stable for both photometry and -astrometry. +the image point spread function (PSF), and its variations across the +field and from image to image. Since comparisons between images must +be reliable, the measurements must be stable for both photometry and +astrometry. A variety of astronomical software packages perform the basic source @@ -518,11 +518,26 @@ \end{itemize} -\note{Discuss the psphot photometry accuracy and the ubercal solution, - etc. mention Paper V} - -\textadd{The success of the \ippprog{psphot} implementation is meeting +\textadd{The success of the \ippprog{psphot} implementation in meeting the photometry and astrometry design requirements is demonstrated by - the achieved accuracy for the Pan-STARRS $3\pi$ Survey data. -} + the achieved accuracy for the Pan-STARRS $3\pi$ Survey data. For a + survey like the Pan-STARRS\,1 $3\pi$ survey to achieve photometry + and astrometry accuracy at the level of our goals, not only must the + measurement of the astronomical detections be precise, but it is + necessary for the detrending (instrumental signature remove) and + calibration processes to correct for a wide variety of systematic + effects and it is also necessary for the observations to be + performed in such a way that the data can be calibrated well. These + others aspects of the process are discussed in detail elsewhere + (Papers I, III, V). In the end, the goals were largely achieved for + the Pan-STARRS\,1 $3\pi$ survey. As reported in Paper V, the + resulting photometric system is consistent across the sky to between + 7 and 12.4 millimagnitudes depending on the filter. The systematic + error floor for individual photometry measurements is $(\sigma_g, + \sigma_r, \sigma_i, \sigma_z, \sigma_y) = (14, 14, 15, 15, 18)$ + millimagnitudes. The bright-star systematic error floor for + individual astrometric measurements is 16 milliarcseconds and the + Pan-STARRS Data Release 2 (DR2) astrometric system is tied to the + Gaia DR1 coordinate frame with a systematic uncertainty of $\sim 5$ + milliarcseconds. } \section{Basic Analysis} @@ -554,5 +569,5 @@ \item {\bf Output} Write out sources in selected format, write out - difference image, variance image, etc, as selected. + difference image, variance image, etc, as selected. \end{enumerate} @@ -578,4 +593,13 @@ PSF model may already be available from external information, in which case the PSF modeling stage can be skipped. + +\textadd{Ultimately, all measurements of individual astronomical + sources from \ippprog{psphot} are reported in one of the tables in + the PSPS database. As discussed in detail in Paper VI, measurements + from individual exposures are available from the + \ippdbtable{Detection} table. Measurements of objects in the + stacked images are stored in one of several \ippdbtable{Stack...} + tables while the `forced' measurements from individual warp images + are stored in tables beginning with \ippdbtable{ForcedWarp...}.} \begin{table*} @@ -893,6 +917,14 @@ Since a typical smoothing or warping operation may introduce correlation between 25 - 100 neighboring pixels, the size of such a -covariance image is prohibitive. -\note{describe the way we handle covariance} +covariance image is prohibitive. + +%% \note{describe the way we handle covariance} + +%% Within the IPP analysis generally, we carry a simplified +%% representation of the impact of covariance on the variance values +%% used in pixel analysis operations. Whenever image operations +%% introduce covariance by combining information from multiple pixels, +%% we update a matrix tracking the covariance at the image center for +%% a small range of pixels. Before sources are detected in the image, a model of the background is @@ -930,8 +962,42 @@ 50\% of the peak bin value. +\begin{table} +\caption{\label{tab:sky.offset} Comparison of background + measurement methods. Backgrounds were measured for simulated images with the given stellar + density (at the low-density detection threshold) and known + background level. The {\tt psphot} technique is less biased at high +stellar densities.} \vspace{-0.5cm} +\begin{center} +% \footnotesize +\begin{tabular}{cccccc} +\hline +\hline +{\bf Density} & {\bf True} & {\bf Image} & {\bf Image} & {\bf Gauss} & {\bf \tt psphot} \\ +{\bf \footnotesize $\log_{10}(\mbox{deg}^{-2}$)} & {\bf Sky} & {\bf Mean} & {\bf Median} & {\bf Fit} & {\bf \tt Value} \\ +\hline +4.2 & 202.8 & 203.3 & 202.8 & 202.8 & 202.9 \\ +4.7 & 202.8 & 204.9 & 203.1 & 203.0 & 203.0 \\ +5.2 & 202.8 & 210.6 & 204.0 & 203.5 & 203.5 \\ +5.7 & 202.8 & 233.9 & 207.4 & 205.4 & 205.3 \\ +6.2 & 202.8 & 300.9 & 219.7 & 211.2 & 210.6 \\ +6.7 & 202.8 & 534.6 & 286.2 & 242.8 & 233.9 \\ +\hline +%\multicolumn{5}{l}{$^1$ a footnote} \\ +\end{tabular} +\end{center} +\end{table} + If the fit to the asymmetric lower fraction of the curve is less than the symmetric fit, but greater than the above lower-bound of the full symmetric fit, then the lower fraction value is kept as the true mean -sky value for this superpixel. +sky value for this superpixel. Table~\ref{tab:sky.offset} shows a +comparison of this technique to several other methods to measure the +sky background using simulated data with a range of stellar +densities. The stellar density listed in the table is the number of stars per +square degree at the $5\sigma$ detection limit {\em in the + lowest-density image}. In our simulations, we find that as the +stellar density rises to values typical in the Galactic plane regions, +this technique results in a more accurate estimate of the background, +though it still over-estimates the background compared to the truth. Bilinear interpolation is used to generate a full-resolution image @@ -986,5 +1052,5 @@ \textadd{For an image with a Gaussian PSF of the same size, this method would represent the optimal detection algorithm, equivalent to a - matched filter \note{add ref}. At this stage, our goal is simply to + matched filter. At this stage, our goal is simply to detect the brighter sources, so the exact size and shape of the PSF is not critical. } @@ -1378,8 +1444,9 @@ parameters would be the shape terms ($\sigma_x, \sigma_y, \sigma_{\rm xy}$) while the independent parameters would be the centroid, -normalization and local sky values ($x_o, y_o, I_o, S$). \note{we do - not fit sky as a free parametery, right?} Thus the -shape parameters are each a function of the source centroid -coordinates: +normalization and local sky values ($x_o, y_o, I_o, S$), though as +noted below (Section~\ref{sec:nonlinear.psf.model}), in practice we do +not allow the sky to be fitted independently since we subtract the +background model. Thus the shape parameters are each a function of +the source centroid coordinates: \begin{eqnarray} \sigma_x & = & f_1(x_{\rm ccd},y_{\rm ccd}) \\ @@ -1423,5 +1490,5 @@ \textadd{For these PSF models, the functions are evaluated at the pixel center. Unlike some galaxy model representations (see -Section~\label{sec:galaxy.conv.fit} ), the first derivatives of these +Section~\ref{sec:galaxy.conv.fit} ), the first derivatives of these functions approach zero as the radius approaches zero, so sub-pixel integration is not necessary.} @@ -1616,5 +1683,5 @@ With $\sigma_a$, $\sigma_b$, $\theta$ in hand, we can now transform these values to the parameters of our fits, $\sigma_x$, $\sigma_y$, -$\sigma_{\rm xy}$ (Eqn~\label{eqn:2d.gaussian} above). This transformation +$\sigma_{\rm xy}$ (Eqn~\ref{eqn:2d.gaussian} above). This transformation can be determined by rotating the 2D Gaussian equation, yielding: \begin{eqnarray} @@ -1802,5 +1869,5 @@ not to be in the current thread group). -\note{explain number of superpixels (psphotThreadTools.c)} +% \note{explain number of superpixels (psphotThreadTools.c)} As the threads complete their analysis, they are assigned the next @@ -1897,6 +1964,5 @@ sky radius. These values are saved in the \textmod{output FITS catalog files}, but not sent to the PSPS. The sky radius value is used below in the -calculation of the Kron magnitude. \note{used in both versions?} -\note{calculated for the second pass?} +calculation of the Kron magnitude. \subsubsection{Kron Magnitudes} @@ -1949,6 +2015,4 @@ the neighbors.} -% \note{give a test example} - \subsubsection{Source Size Assessment} \label{sec:source.size} @@ -2025,13 +2089,18 @@ PV3 analysis of the $3\pi$ survey data, this limit was set to a signal-to-noise ratio of 20.0 for all analysis stages. In these fits, -the dependent parameters are fixed by the PSF model and only the 4 -independent source model parameters are allowed to vary in the fit. -\ippprog{psphot} again uses Levenberg-Marquardt minimization for the -non-linear fitting. The sources are fitted in their S/N order, -starting with the brightest and working down to the user-specified -limit, with the other sources subtracted as discussed above. All -sources for which a non-linear PSF model has been attempted have the -flag bit \code{PM_SOURCE_MODE_FITTED} set, regardless of the quality -of that fit. +the dependent parameters are fixed by the PSF model and only \textmod{the 3 +independent source model parameters (position in $X$ and $Y$ and flux +normalization) are allowed to vary in the fit. Note that we do {\em + not} allow the local sky to be fitted as a free parameters. Since +we have subtracted a model for the background, allowing the sky to be +again at this stage is redundant. In fact, in our testing, we found +that allowing the sky to float resulted in higher scatter for the flux +normalizations.} \ippprog{psphot} again uses Levenberg-Marquardt +minimization for the non-linear fitting. The sources are fitted in +their S/N order, starting with the brightest and working down to the +user-specified limit, with the other sources subtracted as discussed +above. All sources for which a non-linear PSF model has been +attempted have the flag bit \code{PM_SOURCE_MODE_FITTED} set, +regardless of the quality of that fit. Since the PSF model describes the variation of the PSF across the @@ -2148,14 +2217,12 @@ As the sources are fitted to the PSF model, those which survive the exclusion stage are subtracted from the image. The subtraction -process modifies the image pixels (removing the fitted flux, though -not the locally fitted background)\note{is the background actually - fitted locally?} but does not modify the mask or the variance -images. The signal-to-noise ratio in the image after subtraction -represents the significance of the remaining flux. If the -subtractions are sufficiently accurate models of the PSF flux -distribution, \textmod{the remaining flux should be normally distributed about -zero with a standard deviation of 1 $\sigma$}. In practice the cores -of bright stars are poorly represented and may have larger residual -significance. +process modifies the image pixels (removing the fitted flux) but does +not modify the mask or the variance images. The signal-to-noise ratio +in the image after subtraction represents the significance of the +remaining flux. If the subtractions are sufficiently accurate models +of the PSF flux distribution, \textmod{the remaining flux should be + normally distributed about zero with a standard deviation of 1 + $\sigma$}. In practice the cores of bright stars are poorly +represented and may have larger residual significance. For sources in groups of blended stars, the resulting fits are @@ -2201,6 +2268,4 @@ comparing the ratio to that expected. -\note{more on the parameter guess} - For each type of extended source model (in fact for all source models), a function is defined which examines the fit results and @@ -2238,4 +2303,39 @@ \subsection{Faint Source Analysis} \label{sec:faint.psf.model} + +% pueo:/home/real/eugene/ppsim.20200407 +\begin{figure}[htbp] + \begin{center} + \includegraphics[width=\hsize,clip]{\picdir/{completion.ppsim}.pdf} + \caption{\label{fig:complete.ppsim} Completeness as a function of + magnitude (blue curves) for different stellar densities in + simulated data. The curves are labeled with the logarithm of the + stellar density at the detection threshold of the low-density + image. The dotted red line shows the detection limit expected for + the sky level and seeing. The solid red curve shows the + completeness estimated for the low-density image based on + injection and recovery.} + \end{center} +\end{figure} + +% pueo:/home/real/eugene/ppsim.20200407 +\begin{figure}[htbp] + \begin{center} + \includegraphics[width=\hsize,clip]{\picdir/{psphot.complete.pv3}.pdf} + \caption{\label{fig:complete.pv3} Completeness and bogus fraction + as a function of magnitude for different stellar densities in real + PS1 exposures. Each panel represents an exposure at different + Galactic latitudes towards anti-center, labeled by the density of + stars at the detection limit of the low-density exposure. In each + panel, the completeness (compared to deep stack data) and fraction + of false detections (bogus fraction) is shown for a series of + cuts. The gold curves show all detections in the exposures. The + dotted black curve shows the impact of cutting detections + identified by {\tt psphot} as cosmic rays. The blue curve + excludes cosmic rays and detections with {\tt PSF\_QF} $< 0.95$ + while the red curve excludes cosmic rays and detections with {\tt + PSF\_QF\_PERFECT} $< 0.95$.} + \end{center} +\end{figure} After a first pass through the image, in which the brighter sources @@ -2274,8 +2374,9 @@ centroids.} -\textadd{After the flux-normalization is calculated, the moments - are used to calculate the preliminary Kron radius and flux (see - Section~\ref{sec:kron.mags}). These are in turn used to assess the - source sizes as in Section~\ref{sec:source.size}. However, the +\textadd{After the flux-normalization is calculated, the radial + profile is measured (Section~\ref{sec:radial.profile}) and the + moments are used to calculate the preliminary Kron radius and flux + (see Section~\ref{sec:kron.mags}). These are in turn used to assess + the source sizes as in Section~\ref{sec:source.size}. However, the non-linear fitting steps for the PSF model fits (Section~\ref{sec:nonlinear.psf.model}) and the extended source @@ -2288,6 +2389,5 @@ parameters. In addition, the positions (for PSF sources) are not much improved using the non-linear fitting compared with the - non-parametric centroid measurement for these faint sources. - \note{show with a model}.} + non-parametric centroid measurement for these faint sources. } The PV3 threshold for the bright source analysis is a signal-to-noise @@ -2312,6 +2412,4 @@ on one image based on detections in other images have the flag bit \code{PM_SOURCE_MODE2_MATCHED} set. - -\note{need to discuss the injection \& recovery analysis of the completeness} \subsection{Aperture Correction and Total Aperture Fluxes} @@ -2338,33 +2436,4 @@ will by determined by how inconsistently the models represent the actual source flux. - -Aperture photometry attempts to avoid these problems, but introduces -other difficulties. In aperture photometry, if a large enough -aperture is chosen, the amount of flux which is lost will be a small -fraction of the total source flux. Even more importantly, as the -image conditions change, the amount lost will change by an even -smaller fraction, at least for a large aperture. -% -% This can be seen by -% the fact that the dominant variations in the image quality are in the -% focus, tracking and seeing. All of these errors initially affect the -% cores of the stellar images, rather than the wide wings. The wide -% wings are largely dominated by scattering in the optics and scattering -% in the atmosphere. The amplitude and distribution of these two -% scattering functions do not change significantly or quickly for a -% single telescope and site. -% -Aperture photometry can then be used to -correct the PSF photometry. - -The difficulty for aperture photometry is the need to make an accurate -measurement of the local background for each source. As the aperture -grows, errors in the measurement of the sky flux start to become -dominant. If the aperture is too small, then variations in the image -quality are dominant. The brighter is the source, the smaller is the -error introduced by the large size of the aperture. However, the -number of very bright stars is limited in any image, and of course the -brighter stars are more likely to suffer from non-linearity or -saturation. % /data/kukui.1/eugene/psphot.examples.20190423/compare.sh @@ -2402,4 +2471,81 @@ \end{figure*} +% on pueo ~eugene +% /data/kukui.1/eugene/psphot.examples.20190423/compare.sh +\begin{figure}[htbp] + \begin{center} + \includegraphics[width=\hsize,clip]{\picdir/{bright.mag.resid}.\plotext} + \caption{\label{fig:mag.resid.stdevs} Demonstration of photometric + accuracy using the image sequence from + Figure~\ref{fig:mag.resid.psf}. Using only bright stars (7 - 8 + magnitudes above the detection threshold), we calculate the + difference between the magnitudes in the first image and the other + 17 images. The plotted dots show for each pair the mean + difference vs the standard deviation of the difference. Red dots + show the PSF magnitudes and blue dots show aperture + magnitudes. Despite real transparency variations of 0.4 over the + 50 minutes of this sequence, magnitudes are consistent at the few + millimagnitude level. Aperture magnitudes have scatter in + the 2 - 7 millimagnitude range, while the PSF magnitudes have + scatter of 7 - 14 millimagntiudes. +} +\end{center} +\end{figure} + +% on pueo ~eugene/zpts.20200406/mana.sh +\begin{figure*}[htbp] + \begin{center} + \includegraphics[width=\hsize,clip]{\picdir/{zpt.mjd.v0.i}.\plotext} + \caption{\label{fig:zpt.iband} Historical \ips-band zero points. + Blue dots are the individual exposure zero points, corrected to + airmass at the zenith. Red dots are the median of zero points + from images groups in bins of 10 nights. The grey line is a + spline fit to these median values. } +\end{center} +\end{figure*} + +% on pueo ~eugene/zpts.20200406/mana.sh +\begin{figure}[htbp] + \begin{center} + \includegraphics[width=\hsize,clip]{\picdir/{zptres.hist.v0.i}.\plotext} + \caption{\label{fig:zpt.resid.hist} Historical \ips-band zero-point + residual variations. Log-histogram (black line) of the + per-exposure zero points, corrected to the zenith, after + subtracting a spline fit to the median of image groups in bins of + 10 nights. The inset shows the core of the distribution. In + both, the red line is a Gaussian fit to the distribution. The + large negative tails are due to clouds and haze. } +\end{center} +\end{figure} + +Aperture photometry attempts to avoid these problems, but introduces +other difficulties. In aperture photometry, if a large enough +aperture is chosen, the amount of flux which is lost will be a small +fraction of the total source flux. Even more importantly, as the +image conditions change, the amount lost will change by an even +smaller fraction, at least for a large aperture. +% +% This can be seen by +% the fact that the dominant variations in the image quality are in the +% focus, tracking and seeing. All of these errors initially affect the +% cores of the stellar images, rather than the wide wings. The wide +% wings are largely dominated by scattering in the optics and scattering +% in the atmosphere. The amplitude and distribution of these two +% scattering functions do not change significantly or quickly for a +% single telescope and site. +% +Aperture photometry can then be used to +correct the PSF photometry. + +The difficulty for aperture photometry is the need to make an accurate +measurement of the local background for each source. As the aperture +grows, errors in the measurement of the sky flux start to become +dominant. If the aperture is too small, then variations in the image +quality are dominant. The brighter is the source, the smaller is the +error introduced by the large size of the aperture. However, the +number of very bright stars is limited in any image, and of course the +brighter stars are more likely to suffer from non-linearity or +saturation. + In order to thread the needle between these effects, \ippprog{psphot} measures the aperture photometry on a modest-sized aperture, and then @@ -2431,5 +2577,10 @@ analysis, a grid with a maximum of $6\times 6$ samples per GPC1 chip image was used. The reported PSF magnitudes for all objects have this -aperture correction applied. +aperture correction applied. \textadd{Note that an initial aperture correction was +measured during the initial steps of the analysis before the PSF model +was chosen. However, since the sources in the image were not yet +measured and subtracted, that aperture could be contaminated by +neighbors. The analysis here is performed one fairly bright star at a +time with all other sources subtracted in order to minimize such contamination.} % growth curve analysis in psphot: @@ -2481,4 +2632,104 @@ %%% term. +\subsection{Completeness \& Contamination} + +At the end of the \ippprog{psphot} analysis of the sources in the +image, an analysis is performed to test the detection efficiency. A +number of fake PSF sources are injected into the image and the peak +detection analysis (Section~\ref{sec:peaks}) is use to determine if +these sources would have been recovered. The PSF model fluxes are +measured for the source which are detected. For a given image, the +detection threshold is predicted based on the median image variance +and the seeing. A series of brightness bins straddling the threshold +are defined and a number of sources are injected with magnitudes +corresponding to each of these bin values. The \ippprog{psphot} +recipe value \code{EFF.NUM} specifies the number of sources in each +brightness bin (500 the PV3), and the value \code{@EFF.MAG} specifies +the bins as magnitudes above and below the threshold. For PV3, the 13 +magnitude offsets were (-2.0, -1.0, -0.5, -0.25, -0.1, -0.05, 0.0, +0.05, 0.1, 0.25, 0.5, 1.0, 2.0), providing fine sampling near the +limit, but more coarse coverage further away. Poisson noise +appropriate to the photon counts of the injected sources are included +in the image. Injected sources are uniformly distributed across the +image in $X$ and $Y$ pixel coordinates {\em without any consideration + of the masked regions}. This last point means the recovered +fraction in the bright bins can be used to test the masking fraction. + +As the stellar density increases, the completeness suffers due to +crowding and confusion. Since the injection and recovery analysis of +the fake sources operates on the source-subtracted image and does not +attempt to fully discovery the sources, this analysis over-estimates +the completeness in crowded fields. To explore the completeness in +crowded field images, we generate a series of simulated images using a +Gaussian PSF with FWHM = 1\arcsec for a range of stellar densities. +We generate fake stars with fluxes as faint as $\frac{1}{5}$ of the +flux as the low-density detection limit, with densities ranging from +\approx 14,000 stars per square degree at low-density detection limit +to \approx 4.8 million stars per square degree at the low-density +detection limit. The latter is comparable to observed densities in +the Galactic plane. We run the \ippprog{psphot} analysis on these +simulated images and compare the detected stars to those injected to +calculate the completeness for each image as a function of the true +magnitude of the stars. Figure~\ref{fig:complete.ppsim} shows the measured +completeness for each of the six simulated images, labeled by the +logarithm of their faint-end stellar density. The red dashed line +shows the expected detection limit based on the background and seeing, +while the red curve shows the completeness curve calculated +automatically by \ippprog{psphot} using the injection and recovery +analysis. + +For low-density fields, the completeness function determined by +injection and recovery is similar to that measured by the simulation, +with the 50\% completeness threshold roughly 0.3 magnitudes too faint. +As the stellar density increases, the true 50\% completeness magnitude +rises relative to the value estimated by injection and recovery. + +Ideally, all sources detected by \ippprog{psphot} would correspond to +real astrophysical objects. In reality, many sources are detected in +the images which do not correspond to real sources in the sky. In the +very simplified simulations discussed above, which do not include +realistic detector artifacts, we find that the fraction of bogus +detections is extremely low, even at the very faint end. In real +data, bogus detections are due to a variety of typical instrumental +features including cosmic rays, diffraction spikes, satelite tracks, +glows, non-Gaussian noise, variance mis-estimation, etc. See paper III +for extensive discussion of instrumental artifacts in the Pan-STARRS images. + +Figure~\ref{fig:complete.pv3} illustrates the completeness and bogus +detection fraction for a set of 4 real PS1 exposures from the $3\pi$ +Survey. This figure uses \ips-band exposures with Galactic longitude +roughly 200\degrees and latitudes of 0, 10, 30, 90 degrees. We +identify the real astrophysical sources in these fields by comparing +with the deeper stack exposures and counting as real any source +detected in both \rps\ and \ips. We correct for the masking fraction +in the exposures (which is roughly 80\%) in the case of GPC1 and plot +the completeness fraction for all detections in 0.5 magnitude wide +bins from the saturation limit to below the detection limit. We also +show the bogus fraction, calculated as $1 - f_{\rm pure}$, where +$f_{\rm pure}$ is the ratio of real detections to all detections for +the given sample. We then apply three cuts to remove certain kinds of +bogus sources. First, we exclude cosmic rays identified by +\ippprog{psphot} by rejecting sources with the flag bit +\code{PM_SOURCE_MODE_CR_LIMIT} (see Section~\ref{sec:source.size}). +Next, we also remove detections with \ippmisc{PSF_QF} less than 0.95. +Because this cut removes detections with heavy masking, it exclude a +number of bogus detections due to glows and edge defects. Finally, we +also exclude detections with \ippmisc{PSF_QF_PERFECT} less than +0.95. This cut removes detections on residual persistent glows and +diffraction spikes. + +For the exposures at high-Galactic latitude, with a relatively low +density of sources, the cosmic rays represent a significant +contamination, as seen in the excess of bogus sources with \ips-band +magnitudes in the range 17 - 19. These are efficiently removed with +the cosmic ray cut listed above without noticable impact on the +completeness. The other two cuts remove significant numbers of bogus +detections, especially at the faint end, but at a significant cost in +completeness at even brighter magnitudes. The completeness impact of +these cuts is more significant at low-Galactic latitude, likely +because the chance of having a source lie on the diffraction spikes or +persistence glows is greatly increased at higher stellar densities. +The impact of the crowding on the completeness is also clear in this dataset. + \subsection{Stellar Photometry Example} \label{sec:phot.example} @@ -2498,8 +2749,8 @@ configuration for \ippprog{psphot} as used for the full PV3 \ippstage{chip} analysis. The first image of the sequence is compared -to the remaining 17 images. A relative zero point correction is +to the remaining 17 images. A relative zero-point correction is applied, measured as the median of the photometry difference for stars with signal-to-noise greater than 50. The combined error is reported -and used to generate the histograms shows in the figures. From these +and used to generate the histograms shown in the figures. From these two figures, one can observe the trade-off between PSF and aperture photometry. For the brightest instrumental magnitudes, corresponding @@ -2528,4 +2779,84 @@ with the aperture photometry degrading rapidly as the flux of the star decreases. + +{\TEXTADD The figures above show the relative photometric accuracy for + observations at a consistent pointing compared to the photon + counting statistics. A related question is to ask how consistent is + the photometry of the very brightest stars in terms of magnitudes. + Figure~\ref{fig:mag.resid.stdevs} shows the accuracy of the + brightest stars in these images for both PSF and aperture + magnitudes. The relative zero point between the 1st image in the + sequence and each of the remaining images was calculated and the + standard deviations were measured using stars 7 to 8 magnitudes + brighter than the detection threshold, for which the photon noise is + less than 1 millimagnitude. Significant zero-point differences + between the images are observed, largely due to the atmospheric + transparency variations. Even so, the relative zero points + calculated from the aperture magnitudes have standard deviations of + 2.4 - 7.4 millimags with a median of 3.5 millimags, while for PSF + magnitudes, the standard deviations are in the range 6.7 - 14.2 + millimags, with a median of 9.2. } + +{\TEXTADD Our ultimate ability to accurately measure the brightness of + individual sources depends on a few factors: the accuracy of the + flat-field response, the consistency of the flux measurement across + the image (either due to the accuracy of the PSF model or the + accuracy of the aperture correction), and the accuracy of our + correction for any zero point changes. Our ability to accurately + measure the zero point of each exposure depends in part on the + characteristics of the observing site. In hazy conditions, the + transparency of the atmosphere may vary substantially in time but be + relatively stable across the field-of-view of the camera, as is + shown in Figure~\ref{fig:mag.resid.stdevs}. Conversely, thin patchy + clouds can result in small average transparency changes but + substantial localized variations. If the site experiences more + patchy clouds than smooth haze, photometric calibration will be + difficult. A large fraction of time with cloudless conditions will + benefit the calibration.} + +{\TEXTADD To examine the Pan-STARRS site characteristics, we extracted + \ips\ zero points for the lifetime of the observatory (2009 June - + 2020 April), shown in Figure~\ref{fig:zpt.iband}. These zero points + were measured as part of the PV3 analysis of the $3\pi$ Survey, and + from the nightly data analysis after the end of the $3\pi$ Survey, + in both cases using the Pan-STARRS-based reference catalog. The + zero points vary from night-to-night and over long periods. Over + the 11 years of PS1 operation, the observed \ips-band zero point + (for data in good weather, extrapolated to the zenith), has varied + over 0.175 magnitudes (see Figure~\ref{fig:zpt.iband}). The + long-term variations are believed to be due mostly to dust + accumulation on the primary mirror and occasional cleaning, though + the effect of the atmosphere cannot be ruled out.} + +{\TEXTADD Figure~\ref{fig:zpt.resid.hist} shows a log-scale histogram + of the \ips-band zero points after subtracting a smoothly varying + spline fit to the median of groups of 10 nights. A Gaussian fit to + this distribution has $\sigma = 28.4$ millimags. If we + alternatively subtract a median zero point for each night, the + standard deviation is reduced to 18.9 millimags. These values can be + compared to the results of \cite{2012ApJ...756..158S} in which only + photometric nights were included, yielding a standard deviation of + 9.0 millimags. On short time scales, weather (e.g., clouds \& haze) + causes the deviations to lower zero point values. A small fraction + of positive deviations also seen in Figure~\ref{fig:zpt.resid.hist} + which are not expected from the normal effects of weather. We + believe these are largely due to aperture correction errors.} + +\subsection{Basic Analysis Summary} + +\textadd{This section is focused on the basic analysis of the image + for point-source detection and measurement. This analysis is + applied as described to the invidual exposures in the + \ippstage{chip}-stage analysis and the measurements are exposed in + the public release PSPS database in the \ippdbtable{Detection} + table. The same analysis is applied to the individual skycells in + the \ippstage{stack}-stage analysis and the resulting values are + presented in the PSPS \ippdbtable{StackObjectThin} and + \ippdbtable{StackObjectAttribute} tables, with the later presenting + values in instrumental units and the former giving calibrated + values. The detection efficiency information determined from the + injection and recovery analysis is stored in the + \ippdbtable{ImageDetEffMeta} and \ippdbtable{StackDetEffMeta} tables + for the \ippstage{chip} and \ippstage{stack} stage analysis. } \section{Extended Source Analysis} @@ -2684,9 +3015,8 @@ saved as equal-length vectors in the FITS table (\code{PROF_FLUX} and \code{PROF_FILL}). The values of the radial bins are saved in the -output file FITS header (\code{RMIN_NN}, \code{RMAX_NN}). - -\note{specify PV3 config values?} - -% \note{these profiles are not saved in PSPS} +output file FITS header (\code{RMIN_NN}, \code{RMAX_NN}). \textadd{These +measurements are saved in the catalog FITS files generated by +\ippprog{psphot}, but they are not currently exported to the PSPS +database for easy access.} \subsection{Petrosian Radii and Magnitudes} @@ -2746,5 +3076,6 @@ parameters were attempted, but for which the radial profile analysis failed have the flag bit -\code{PM_SOURCE_MODE2_PETRO_NO_PROFILE} set. +\code{PM_SOURCE_MODE2_PETRO_NO_PROFILE} set. \textadd{These measurements are +available from the PSPS \ippdbtable{StackPetrosian} table.} @@ -2959,4 +3290,10 @@ \note{how much error does this approximation introduce?} +The convolved galaxy model fit results are available in one of three +PSPS database tables: \ippdbtable{StackModelFitExp}, +\ippdbtable{StackModelFitDeV}, \ippdbtable{StackModelFitSer} for the +Exponential, DeVaucouleur, and S\'ersic models, respectively. + + \subsection{Fixed Aperture Photometry} \label{sec:fixed.aperture.photom} @@ -3031,5 +3368,14 @@ SDSS aperture magnitudes.} -\note{test this?} +\textadd{The measurements described in this subsection are presented + in the PSPS database (Paper VI) in the + \ippdbtable{StackApFlxExGalUnc}, \ippdbtable{StackApFlxExGalCon6}, + \ippdbtable{StackApFlxExGalCon8}, and \ippdbtable{StackApFlx} tables. + The first three tables present measurements for all apertures from + the unconvolved, 6, and 8-pixel FWHM convolved images (respectively) + while the last table presents a subset of the radii from all three + sets of measurements joined together for ease of access.} + +\note{test SDSS radial apertures?} % at least out to aperture # RADIAL_AP_MIN (= 4), but no further than @@ -3190,8 +3536,11 @@ Traditionally, projects which use multiple exposures to increase the depth and sensitivity of the observations have generated something -equivalent to the stack images produced by the IPP analysis -(c.f, CFHT Legacy survey, COSMOS, etc). In theory, the photometry of -the stack images produces the ``best'' photometry catalog, -with best sensitivity and the best data quality at all magnitudes. In +equivalent to the stack images produced by the IPP analysis, +\textadd{as done for example by the CFHT Legacy Survey + \citep{2006ApJ...647..116H} or the Cosmic Evolution Survey + \citep[COSMOS][]{2007ApJS..172...99C}}. In theory, the photometry +of the stack images produces the ``best'' photometry catalog, with +best sensitivity and the best data quality at all magnitudes +\citep[see e.g., the discussion of]{2017ApJ...836..187Z}. In practice, these images have some significant limitations due to the difficulty of modeling the PSF variations. This difficulty is @@ -3201,4 +3550,7 @@ single exposure, and the wide range of image quality conditions under which data were obtained and used to generate the $3\pi$ PV3 stacks. + +% CFHTLS release doc: +% http://www.cfht.hawaii.edu/Science/CFHLS/T0007/CFHTLS_T0007-TechnicalDocumentation.pdf For any specific stack, the point spread function at a particular @@ -3256,6 +3608,11 @@ (Section~\ref{sec:ensemble.fitting}). -\textmod{Aperture fluxes, Kron fluxes}, and moments are also measured at -this stage for each warp. Note that the flux measurement for a faint, +\textmod{Aperture fluxes, Kron fluxes}, and moments are also measured +at this stage for each warp. \textmod{For the Kron fluxes, the radii + are fixed to the value determined in the analysis of the stack. + Fluxes are also measured in 3 of the fixed apertures discussed in + Section~\ref{sec:fixed.aperture.photom}: those with 3.00, 4.64, + and 7.44 arcsecond radii.} + Note that the flux measurement for a faint, but significant, source from the stack image may be at a low significance (less than the $5\sigma$ criterion used when the @@ -3277,5 +3634,10 @@ system. The PSF photometry measurements are combined in the context of the DVO database system \citep{magnier2017.datasystem}, including -recalibration of the zero points for the individual warp. +recalibration of the zero points for the individual warp. \textadd{These +measurements for each warp are available from the PSPS database +\ippdbtable{ForcedWarpMeasurement} and \ippdbtable{ForcedWarpExtended} +tables, the latter containing the three fixed-aperture fluxes. The +average values calculated over the warps are found in the +\ippdbtable{ForcedMeanObject} tables.} \note{discuss the relative quality of average exposure, forced warp @@ -3339,5 +3701,7 @@ In this way, the forced galaxy model analysis uses the PSF information from each warp image to determine a best set of convolved galaxy -models for each galaxy model measured for the stack image. +models for each galaxy model measured for the stack image. The +results of these galaxy model fits are available from the PSPS +database \ippdbtable{ForcedGalaxyShape} table. \subsection{Galaxy Lensing Parameters} @@ -3527,4 +3891,9 @@ \code{PSF_QF_PERFECT} is less than 0.85. +The lensing parameters measured for individual warps are available +from the PSPS database \ippdbtable{ForcedWarpLensing} table while the +average values calculated over the warps is found in the +\ippdbtable{ForcedMeanLensing} tables. + % \note{example of using the lensing elements for binaries?} @@ -3673,4 +4042,19 @@ \section{Conclusions} +\note{add lessons learned here} + +\begin{verbatim} +Suggestions for improvements / changes +* use more external knowledge: + ** Gaia or PS1 to select stars as PSF sources + ** pre-seed information about the very bright or very crowded + regions +* background model + ** allow the superpixel scale to change as a function of environment + ** do not use the lower-end model unless region is known to be dense +* use galactic latitude or local stellar density to smoothly + transition from double / multi-PSF to galaxy model fitting +\end{verbatim} + The Pan-STARRS Image Processing Pipeline has used the \ippprog{psphot} software to detect and characterize astronomical sources in images Index: /trunk/doc/release.2015/ps1.analysis/response.txt =================================================================== --- /trunk/doc/release.2015/ps1.analysis/response.txt (revision 41332) +++ /trunk/doc/release.2015/ps1.analysis/response.txt (revision 41333) @@ -16,5 +16,5 @@ data sets. -**** TBD : all of these items until Abstract +** added to the end of Section 3 Psphot Design Goals For many of the sections, the reader would benefit by starting with @@ -77,5 +77,7 @@ state the same for galaxy astrometry, fluxes and colors. -**** TBD +** for each section, we have added a summary of where the values may + be found, and added an overall summary of this issue to the end of + the Basic Analysis section. A detail of the code is presented (variable names, etc) that imply @@ -96,5 +98,5 @@ that the photometric goals are achieved -**** TBD see note section Forced PSF Phot +**** TBD : discuss relative quality of chip, forced, stack photometry - Sec 7, where the image differencing detections and photometry is used @@ -124,5 +126,5 @@ in one place would be a useful service. -**** TBD +**** TBD : summarize the lessons learned Abstract: @@ -219,5 +221,9 @@ applying to bright sources, and another addessing all (==faint) sources. -**** TBD +** We have expanded the discussion in 4.7 (Faint Source Analysis) to + explain which of the steps in the bright source pass are repeated + and which are skipped. We refer back to the specific sections and + explain where there are detailed differences in the bright and + faint versions of the same step. Sec 4.1: @@ -227,9 +233,14 @@ of Sec 4.8) that the PSF model for an image is actually selected. -**** TBD ** The aperture correction is measured at the end of the bright-star -** pass, at which point the PSF model is chosen and fixed. A final -** aperture correction is measured at the end of the full analysis, -** but only for the PSF model class selected earlier. + pass, at which point the PSF model is chosen and fixed for the rest + of the analysis. A final aperture correction is measured at the + end of the full analysis, but only for the PSF model class selected + earlier. But for PV3, the PDF model was fixed to the PS1_V1 + version, so this selection was not performed. We have added text to + 4.5.3 to explain how the aperture correction is used to select a + PSF model, and that only the single model form was used for PV3. + We also note in section 4.8 that we re-measure the aperture + correction at the end with the other sources subtracted. Sec 4.3: @@ -264,5 +275,7 @@ measure is used. -**** TBD: model? +** added a table showing sky recovery vs stellar density from + simulations using the standard psphot analysis vs other methods, + added discussion of the results. Sec 4.4.1: @@ -319,4 +332,6 @@ **** TBD: SHOW SOME EXAMPLES of PSF variations + choose 3 exposures: 1 with good IQ, one with bad IQ, but round, one with bad IQ but not round, + plot some IQ stats (Mxx - Myy) / (Mxx + Myy) - Please state whether the PSF model is this set of formulae @@ -344,5 +359,6 @@ sources by GAIA. -***** TBD +** This is an interesting suggestion, but out of the scope of this + effort. we have added this to the lessons-learned discussion Sec 4.5.3: @@ -419,10 +435,12 @@ and presented as a future development effort. -**** TBD +**** TBD : wording of full PSF model section 4.6.6 - Remind the reader that the 4 independent parameters includes a local sky value. -**** TBD: double-check if the sky is allowed to float in this step +** in fact, we do not allow the sky to float; fixed the wording to + specify the *3* independent parameters and to explain why we do not + allow the sky to float. - "remaining flux should be below 1\sigma significance" -> @@ -437,5 +455,5 @@ range. -**** TBD: was the turned on for PV3? +**** TBD: double-star mode: was this turned on for PV3? ppSim to show recovery Sec 4.7: @@ -444,5 +462,7 @@ could be included here. -**** TBD: include detection limit description +** This was a definitely gap. We have added a subsection (4.9) + discussing the completeness and contamination, using both simulated + and real data to illustrate these effects Sec 4.8: @@ -501,5 +521,9 @@ atmospheric transparency variations. -**** TBD +** we have added discussion and some plots showing the repeatability + of the brightest stars for PSF and aperture magnitudes. We also + discuss the long-term site characteristics and the impact of the + atmosphere on the photometric calibration, relating back to the + ubercal work of Schlaley et al 2012. Sec 5: @@ -534,5 +558,5 @@ compare well to those in the PS1 catalog? -**** TBD: compare to SDSS +**** TBD: compare Petrosian mags to SDSS for some example Sec 5.3: @@ -561,5 +585,5 @@ error of this approximation should be stated. -**** TBD: model +**** TBD: model central pixel errors for Sersic models Sec 5.4: @@ -626,5 +650,5 @@ discussion would be Zackay & Ofek 2016. -**** TBD +** added references and updated the text - The terms "skycell" and "warp image" are first used here without @@ -664,5 +688,5 @@ and if not, which code would it be most similar to? -**** TBD +**** TBD : check on GREAT challenge to compare code - Define "KSB" and "HFK" references in-line @@ -789,5 +813,5 @@ - Some additional references should be included; some suggestions above. -**** TBD +** added additional references ** Also, we have added Danny Farrow (UK Durham & MPIA) to the authors