Index: trunk/doc/design/ippSRS.tex =================================================================== --- trunk/doc/design/ippSRS.tex (revision 2192) +++ trunk/doc/design/ippSRS.tex (revision 2241) @@ -1,3 +1,3 @@ - %%% $Id: ippSRS.tex,v 1.11 2004-10-22 04:43:35 eugene Exp $ + %%% $Id: ippSRS.tex,v 1.12 2004-10-29 22:00:08 eugene Exp $ \documentclass[panstarrs,spec]{panstarrs} @@ -6,5 +6,5 @@ \subtitle{Software Requirements Specification} \shorttitle{IPP SRS} -\author{Eugene Magnier, Paul A. Price, Josh Hoblitt} +\author{Eugene A. Magnier, Paul A. Price, Josh Hoblitt} \audience{Pan-STARRS PMO} \group{Pan-STARRS Algorithm Group} @@ -34,9 +34,11 @@ \RevisionsStart % version Date Description -DR.01 & 2003.01.01 & First draft \\ \hline -DR.02 & 2003.03.10 & Second draft \\ \hline -DR.03 & 2003.04.13 & Most paragraphs fleshed out \\ \hline -DR.04 & 2003.04.27 & Basic text frozen for internal review \\ \hline -DR.05 & 2003.05.24 & Incorporating comments from internal review \\ \hline +DR.01 & 2004.01.01 & First draft \\ \hline +DR.02 & 2004.03.10 & Second draft \\ \hline +DR.03 & 2004.04.13 & Most paragraphs fleshed out \\ \hline +DR.04 & 2004.04.27 & Basic text frozen for internal review \\ \hline +DR.05 & 2004.05.24 & Incorporating comments from internal review \\ \hline +DR.06 & 2004.08.06 & Revisions in prep of SRR \\ \hline +DR.06 & 2004.10.22 & Revisions based on SRR \\ \hline \RevisionsEnd @@ -580,50 +582,7 @@ \subsubsection{Image Server} -%% IPP Image Server T & F - -Image Server tasks and functions: - -\begin{itemize} - -\item The IPP Image Server stores images on a distributed collection - of computer disks. Individual instances of a file are only required - to be stored on a single machine (striping across computers is not a - requirement). - -\item The IPP Image Server attempts to store an image on a specific - machine if requested by the user. - -\item If such a request cannot be honored (ie, the machine is down), - the IPP Image Server selects an appropriate machine and notifies the - requesting agent of the new location. - -\item The IPP Image Server stores multiple copies of each image upon - request, the number of copies specified independently for each file - by the user. - -\item The IPP Image Server maintains a record of all image copies - currently available in the repository. This record includes at - least the image name, location (which machine), the image size, and - the state of the image (available, locked, - deleted). - -\item The IPP Image Server locks images in the repository on request. - Both read (shared) and write (exclusive) locks are provided. A read - lock prevents write access to the file; a write lock prevents both - read and write access. Access prevention may be advisory rather - than rigorously enforced. - -\item The IPP Image Server return the image location (the computer or - computers on which it resides) upon request. - -\item The IPP Image Server provides a specified image upon request. - -\item The IPP Image Server deletes images in the repository on - request. -\end{itemize} - %% IPP Image Server Requirements -IPP Image Server requirements: +IPP Image Server has the following requirements: \begin{enumerate} @@ -697,95 +656,4 @@ \end{center} \end{table} - -%% IPP AP DB T & F - -The purpose of the AP Database is: -\begin{itemize} -\item to enable the photometric calibration of images -\item to enable the astrometric calibration of images -\item to enable the construction of flat-field correction frames -\item to enable the construction of a photometric calibration catalog -\item to enable the construction of an astrometric calibration catalog -\item to monitor the system photometry calibration parameters -\item to monitor the system astrometry calibration parameters -\item to perform the identification of single-occurance transients -\end{itemize} - -The tasks and functions of the AP Database include: - -\begin{itemize} -\item The AP Database accepts and stores individual detections and - collections of detections along with information about the image - which provided the detections. - -\item Detections are saved as one of several detection classes (P2, - P4$\Sigma$, P4$\Delta$, SS) and the AP Database stores the - appropriate parameters, listed in Table~\ref{APdetections}, for each - class. - -\item The AP Database identifies the image which provided the - detection, or in the case of external references, an identifier - specific to the reference source. - -\item The AP Database groups detections into objects on the basis of - positional coincidence and measures average parameters of those - objects. - -\item The AP Database stores parallax and proper motion parameters for - a subset of the average objects. - -\item The AP Database stores image and filter calibration information - necessary to convert between instrumental magnitudes and calibrated - magnitudes in standard systems. - -\item The AP Database performs at least the follow queries, with - constraints on the output based on at least time ranges, magnitude - limits, error limits: - - \begin{itemize} - \item given $(RA,DEC)$ and a Radius, return all objects and/or - detections in the region. - - \item given $(RA,DEC)_0$ to $(RA,DEC)_1$, return all objects and/or - detections in the region. - - \item given $(RA,DEC)$, return closest object. - - \item given object ID, return all detections. - - \item given detection, return source image data. - - \item given detection, return object. - - \item given $(RA,DEC)$, return all images overlapping coordinate. - - \item given $(RA,DEC)$ and a Radius, return all images overlapping region. - - \item given $(RA,DEC)_0$ to $(RA,DEC)_1$, return all images overlapping region. - - \item given detection instrumental magnitude, return derived - magnitudes based on calibration information. - - \item given a collection of detections in a filter, determine the - object average magnitude in that filter. - - \item given a collection of objects and detections, determine the - individual image zero-points. - - \item given a region, return all possible combinations of the object - or detection magnitudes $(M_1 - M_2)$. - - \item given a list of $(RA,DEC)$ entries, return all nearest objects. - - \item given a filter, telescope, or detector, return all calibration - terms and history. - - \item given a detection, return all non-detections from images which - overlapped the detection coordinates. - \end{itemize} - -\item The AP Database shall accept detection IDs of moving objects and - label the detections with the identified object. -\end{itemize} %% IPP AP DB Requirements @@ -834,28 +702,4 @@ \end{table} -%% Metadata DB T & F - -The Metadata Database tasks and functions: - -\begin{itemize} -\item The Metadata Database stores the classes of data listed in - Table~\ref{metadata}. Thus, the Metadata Database stores and serves - metadata for all raw images, for processed images, for the - calibration images (both raw and master), for the extracted object - lists. Metadata describing the environmental conditions at the - telescope is also stored and provided as needed. - -\item The Metadata Database responds to simple queries which return - the data in the categories listed in Table~\ref{metadata} based on - the primary data key and with basic constraints of time ranges and - other simple conditional constraints. - -\item The Metadata database stores the configuration information with - restricted access so that only specific people may change the - information (eg, science parameters available to the science team; - software configuration parameters available to the system - maintainers). -\end{itemize} - %% Metadata DB Requirements @@ -883,61 +727,4 @@ \subsubsection{Controller} -%% IPP Controller T & F - - IPP Controller tasks and functions: - -\begin{itemize} - -\item On startup, the IPP Controller attempts to establish - communication with all of its computers and set their state to be - {\tt alive} or {\tt dead} based on the success of the - connection. - -\item The IPP Controller detects computers which crash or stop - responding and set their state to {\tt dead}. - -\item The IPP Controller attempts to re-establish communication with - {\tt dead} computers. - -\item The IPP Controller accepts tasks from external users and - systems, which may specify a desired CPU (node) and priority in - addition to the task command. - -\item The IPP Controller attempts to run pending tasks on the desired - node, if available (not {\tt dead} or {\tt off}). - -\item If the node is unavailable, the IPP Controller attempts to run - the task on another node. - -\item If the node is available, the IPP Controller attempts to run a - given task only if no higher-priority tasks are available and no - task is currently being executed. - -\item The IPP Controller monitors the output from the task and writes - it to an associated log destination. - -\item The IPP Controller monitors the execution status of each task - currently executing on a node and performs the following actions: - - \begin{itemize} - \item identify the task as successful if it has a valid exit status. - \item identify the task as unsuccessful if it has an error exit status. - \item identify the task as unattempted if the computer crashed. - \end{itemize} - -\item The IPP Controller accepts and performs the following external - commands: - \begin{itemize} - \item add a task to the pending task list. - \item delete a specific task from the pending task list. - \item return the current status of a specific task. - \item return a list of all pending and non-pending tasks. - \item set a specified computer state to {\tt off} or {\tt dead}. - \item restrict a specified CPU to a class of tasks. - \item halt execution of a specified task. - \item set the IPP Controller state to {\tt finish}, {\tt abort}, or {\tt stop}. - \end{itemize} -\end{itemize} - %% IPP Controller Requirements @@ -963,30 +750,4 @@ \subsubsection{Scheduler} - -%% IPP Scheduler T & F - -The IPP Scheduler tasks and functions: - -\begin{itemize} -\item The IPP Scheduler sends the analysis tasks which it initiates to - the IPP Controller. - -\item All analysis tasks sent by the IPP Scheduler include a complete - UNIX command with necessary arguments, the priority of the task, and - optionally the desired processing node. - -\item When the IPP Scheduler is placed in the {\em paused state}, it - only initiates User-requested tasks. - -\item When the IPP Scheduler is placed in the {\em interactive state}, - it initiates User-requested tasks as well as data transfer tasks. - -\item When the IPP Scheduler is placed in the {\em automatic state}, - it initiates the most appropriate task based on the inputs and - dependency rules. - -\item The IPP Scheduler sends the exit status of the analysis tasks to - the appropriate destination as defined by the task dependency table. -\end{itemize} %% IPP Scheduler Requirements @@ -1078,28 +839,7 @@ \subsubsection{Phase 1 : image processing preparation} -Phase 1 is the image processing preparation stage. The analysis is -performed on a complete FPA. At the end of this analysis, the FPA is -ready to be analysed in detail in Phase 2. The Phase 1 tasks and -functions are: - -\begin{itemize} - -\item Extract FPA guide stars to determine astrometry across the full FPA - -\item If no guide stars are available, phase 1 must measure the pixel - coordinates of known bright stars expected in the field from the - image data. - -\item The total number of stars and size of the bright-star - acquisition box shall be a user-configurable parameter in the range - 20 - 250. - -\item Calculate the Image cell / Sky cell overlaps for each image. - Sky cells which do not have sufficient science image overlap $< 5\%$ - are excluded from the overlap table. - -\end{itemize} - -The Phase 1 requirements are: +The Phase 1 analysis stage is performed on each science exposure (each +complete FPA image) to calculate basic astrometric data needed by the +later stages. The Phase 1 requirements are: \begin{enumerate} @@ -1123,5 +863,5 @@ %% Phase 2 \subsubsection{Phase 2 : image reduction} - + Phase 2 is the detrend stage, in which each detector is separately processed to remove instrumental signatures. The result of Phase 2 is @@ -1129,68 +869,5 @@ collection of objects detected in the image and characterized in a rudimentary way (star / non-stellar), and a measurement of the PSF -across the detector. - -The tasks and functions of Phase 2 are as follows: - -\begin{itemize} - -\item Convolve the flat-field and high-spatial-frequency fringe images - with the OT kernel. - -\item Mask ghosts of bright stars which introduce residual feature - more significant than 1\% of the background. - -\item Bias subtract the image. - -\item Correct each chip independently for non-linearity. - -\item Flat-field correct the image. - -\item Subtract a fit to the detector-dependent fringing pattern. - -\item Subtract a fit to the low-spatial frequency sky background. - -\item Identify `cosmic rays' on the basis of morphology. - -\item Perform (positive) object detection on the processed images, - down to a user-configured threshold, likely to be $\sim 20\sigma$. - The detection threshold may optionally be a function of the average - background flux or the local noise level. - -\item Measure the following object parameters: - - \begin{itemize} - \item object centroid and position errors. - \item an extended object position ($x_g, y_g$). - \item instrumental PSF magnitude and error. - \item local background level and error. - \item second moments ($\sigma_{\rm min}, \sigma_{maj}$) of the object - and their covariance matrix. - \end{itemize} - -\item Perform minimal object classification to distinguish objects - which are consistent with a single PSF, objects which are - inconsistently large, objects which are inconsistently small, and - objects which are saturated. - -\item Match the detected objects with known astrometric reference - objects, including proper-motion compensation. - -\item Fit the reference and detected object coordinates to determine - astrometric parameters for the individual OTAs, including - polynomials of the coordinates up to 3rd order (user-specified - parameter). The Cell astrometric parameters are not allowed to vary - in the fit, which uses outlier rejection to determine a robust - solution. - -\item Extract subrasters (`postage stamps') surrounding a - user-specified list of coordinates from the flattened - images, to be saved in the IPP Image Server. - -\item measure the PSF variation as a function of detector position. - -\end{itemize} - -The Phase 2 requirements are: +across the detector. The Phase 2 requirements are: \begin{enumerate} @@ -1238,36 +915,6 @@ reference catalogs to determine improved photometric and astrometric calibrations for the FPA as a whole, and to improve the measurement of -the PSF and sky variations across the field. The Phase 3 tasks and -functions are as follows: - -\begin{itemize} - -\item Phase 3 uses the objects detected in Phase 2, matched with a - user-specified reference photometry catalog, to determine the image - photometric zero point and zero-point variations across the field. - -\item If zero-point variations are significant ($> 0.01$ mag - peak-to-peak), the zero-point variations are modeled with a - polynomial correction of order 3 or less. - -\item The photometric nature of the FPA image is categorized on the - basis of the zero-point consistency, the transparency compared with - recent long-term measurements in the filter, and the external - indicators of photometricity. - -\item Phase 3 uses the objects detected in Phase 2, matched with an - appropriate astrometric reference catalog, to improve the distortion - model used for the image. The resulting astrometric accuracy is - consistent across the field to 30 mas, and is limited by the - astrometric reference catalog, (eg, 100 - 250 mas for - USNO-B1.0). - -\item The Phase 3 analysis modifies the background correction of Phase - 2 based on the full-field statistics to achieve an accuracy of 1\% - of the background. - -\end{itemize} - -The Phase 3 requirements are: +the PSF and sky variations across the field. The Phase 3 requirements +are: \begin{enumerate} @@ -1310,110 +957,5 @@ Phase 4 is the image combination stage, in which multiple images of the same portion of the sky are merged and confronted with the static -sky image. The Phase 4 tasks and functions are as follows: - -\begin{itemize} - -\item The Phase 4 analysis determines the corresponding set of image - pixels for a given sky cell. - -\item These pixels are extracted from the input images, using the - astrometric information for each OTA and Cell to determine the exact - overlaps. - -\item The Phase 4 analysis skips any sky cells with fewer than 5\% of - their pixels overlapping the input images. - -\item Pixels which have been extracted from the input images are - geometrically warped to match the corresponding pixels in the sky - image. This transformation is based on the measured astrometric - solution for the input images relative to the reference catalog used - to generate the static sky image. The warping may use a - locally-linear astrometric solution to speed the processing. - -\item Phase 4 determines the appropriate photometry scaling factors - needed to combine the images photometrically. - -\item When multiple images are combined, the group of input pixels - which contribute to an output pixel are examined and pixels from the - group of images which are inconsistent with the ensemble (by an - amount defined by the user-configurable parameters) are identified - and flagged, though this outlier rejection shall be performed - optionally. - -\item The resulting collection of pixels is used to construct a single - output image, cleaned of the outliers. - -\item The cleaned, combined image is PSF matched with the static sky - image. - -\item The static sky image is subtracted from the stacked, cleaned - image, resulting in the difference image (P4$\Delta$ image) - -\item The Phase 4 analysis performs object detection on the difference - images. All objects in the difference image above a user-configured - signficance threshold are detected, including both positive and - negative flux objects. The detection threshold may optionally be a - function of the average background flux or the local noise - level. The likely significance threshold is $\sim 3\sigma$. - -\item P4$\Delta$ objects have the following object parameters - measured: - \begin{itemize} - \item object centroid and position errors. - \item instrumental PSF magnitude and error. - \item local background level and error. - \item streak L, $\phi$, $\sigma_L$, $\sigma_\phi$. - \item second moments ($\sigma_{\rm min}, \sigma_{maj}$) and their covariance matrix. - \end{itemize} - -\item Minimal object classification is performed to distinguish - objects which are consistent with a single PSF, objects which are - inconsistent, and objects which are saturated. - -\item The pixels belonging to variable sources are masked in the - input image. - -\item A new, cleaned image is constructed from the masked input images - (P4$\Sigma$ image) - -\item Object detection is performed on the cleaned, summed image to a - user-configured significance threshold ($\sim 7\sigma$). Only - positive flux object are considered. The detection threshold may - optionally be a function of the average background flux or the local - noise level. - -\item P4$\Sigma$ objects have the following object parameters - measured: - \begin{itemize} - \item object centroid and position errors. - \item an extended object position ($x_g, y_g$). - \item instrumental PSF magnitude and error. - \item local background level and error. - \item second moments ($\sigma_{\rm min}, \sigma_{maj}$) and their - covariance matrix. - \item the Petrosian radius, magnitude, axis ratio, and angle. - \item the S\'ersic radius, magnitude, axis ratio, angle, and parameter $\nu$. - \end{itemize} - -\item Minimal object classification is performed to distinguish - objects which are consistent with a single PSF, objects which are - inconsistent, and objects which are saturated. - -\item Before the image is added to the static sky, it must pass Q/A - tests: - \begin{itemize} - \item the measured photometry scatter for the image must be less - than \tbr{1\%}. - - \item the measured astrometry scatter for the image must be less - than \tbr{30 mas}. - \end{itemize} - -\item The final, cleaned input image is added to the static sky so - that an incrementally-deeper static sky image may be - made. -\end{itemize} - -The Phase 4 requirements are: +sky image. The Phase 4 requirements are: \begin{enumerate} @@ -1433,7 +975,7 @@ time. \VER{TEST}{TLR:17} -\item completeness? - -\item contamination? +\item \tbd{completeness} + +\item \tbd{contamination} \end{enumerate} @@ -1458,226 +1000,18 @@ \end{enumerate} -\subsubsection{Bias Image Creation} - -The Bias calibration stage constructs a master bias image from a -collection of raw bias images. The tasks and functions include: +The calibrations consist of the following types of data: \begin{itemize} - -\item The Bias calibration stage corrects the input images based on - the overscan region, determined from either the header or from - metadata. - -\item The Bias calibration stage combines the input images using the - statistic specified by the user, selected from one of the following: - sample mean, median, and mode, robust mean, median, and mode, and - the clipped mean and median. - -\item The Bias calibration stage construct residual images, in which - the master bias is applied to the input images. - -\item Outlier residual images, those for which the residual bias and - variance in the bias image are excessive, are excluded from the - input image stack and the bias image reconstructed. +\item Mask +\item Bias +\item Dark +\item Flat-field +\item Fringe Pattern +\item Low-spatial-frequency sky model +\item Flat-field correction image +\item Non-linearity correction +\item Telescope astrometry model +\item Zero-point corrections \end{itemize} - -\subsubsection{Dark Image Creation} - -The Dark calibration stage shall construct a master dark image from a - collection of raw dark images. The tasks and functions include: - -\begin{itemize} - -\item The Dark calibration stage raises an error if the input images - have exposure times which deviate by more than 2\%. - -\item The Dark calibration stage corrects the input dark images for - the bias. - -\item The Dark calibration stage combines the input images using the - statistic specified by the user, selected from one of the following: - sample mean, median, and mode, robust mean, median, and mode, and - the clipped mean and median. - -\item The Dark calibration stage constructs residual images, in which - the master dark is applied to the input images. - -\item Outlier residual images, those for which the residual level and - variance are excessive, are excluded from the input image stack and - the dark image reconstructed. -\end{itemize} - -\subsubsection{Flat-field Image Creation} - -The Flat-field calibration stage constructs a master flat-field image -from a collection of raw flat-field images. The tasks and functions -include: - -\begin{itemize} - -\item The Flat-field calibration stage accepts a group of images from - one of the following flat-field sources: dome, twilight, - night-sky. - -\item The flat-field calibration stage raises an error if the - input images in a single stack used more than one of the above - flat-field sources or multiple filters. - -\item The Flat-field calibration stage corrects the input flat-field - images for the bias and dark. - -\item The Flat-field calibration stage combines the input images using - the statistic specified by the user, selected from one of the - following: sample mean, median, and mode, robust mean, median, and - mode, and the clipped mean and median. - -\item The Flat-field calibration stage constructs residual images, in - which the master flat-field is applied to the input images. - -\item Outlier residual images, those for which the residual level and - variance are excessive ($> 0.1$\%, or 1.02 times the Poisson limit - of the flat-field image), are excluded from the input image stack - and the flat-field image reconstructed. -\end{itemize} - -\subsubsection{Mask Image Creation} - -The Mask calibration stage constructs a bad-pixel mask from a stack of -raw flat-field images and a master flat-field image. The tasks and -functions include: - -\begin{itemize} - -\item The Mask calibration stage masks the pixels which are - inconsistent in the input flats by more than 1\%, given sufficient - signal-to-noise in the input flats. - -\item The Mask calibration stage mask the pixels which are - consistently low or high in the input flats by more than a factor of - 3 beyond the typical pixel. - -\item The Mask calibration stage masks the pixels identified in a - table of bad pixels generated externally to the calibration stage. - -\item The Mask calibration stage uses multiple bit values to identify - the different types of masked pixels. - -\item The Mask calibration stage raises an error if the input images - generate too many bad pixels in the mask. -\end{itemize} - -\subsubsection{Fringe-frame Creation} - -The Fringe-frame Creation calibration stage constructs a master fringe -frame from a stack of raw night-time sky images or from a stack of -dome fringe frames. The tasks and functions include: - -\begin{itemize} - -\item The Fringe-frame Creation calibration stage raises an error if - the input stack consists is images generated with more than one type - of fringe source or with multiple filters. - -\item The Fringe-frame Creation calibration stage flattens the input - images to remove the pixel-to-pixel sensitivity variations of the - detector. - -\item The Fringe-frame Creation calibration stage measures the fringe - amplitude on the input fringe images. - -\item The Fringe-frame Creation calibration stage scales the input - fringe images based on the fringe amplitude. - -\item The Fringe-frame Creation calibration stage combines the scaled - input images using the statistic specified by the user, selected - from one of the following: sample mean, median, and mode, robust - mean, median, and mode, and the clipped mean and median. - -\item The Fringe-frame Creation calibration stage constructs residual - images, in which the master fringe image is applied to the input - images, along with all necessary preceding calibration images. - -\item The Fringe-frame Creation calibration stage measures the - residual fringe amplitude on the residual images. -\end{itemize} - -\subsubsection{Low-spatial-frequency Sky Models} - -The Sky Model calibration stage constructs a sky model image set from -a stack of raw night-time sky images. - -\subsubsection{Flat-field correction Frame Creation} - -The Flat-field correction calibration stage constructs a flat-field -correction image from dithered observations of a stellar field. The -tasks and functions include: - -\begin{itemize} - -\item The Flat-field correction calibration stage constructs a - flat-field correction image from dithered observations of a stellar - field. - -\item The Flat-field correction calibration stage constructs a - flat-field correction image for each filter and camera - independently. - -\item The Flat-field correction calibration stage constructs a - correction image which makes the photometry of multiple observations - of the same stellar source consistent at different locations in the - focal plane. - -\item The Flat-field correction calibration stage constructs corrected - flat-field images using the measured correction. - -\item The Flat-field correction calibration stage determines the - consistency of the corrected flat-field images using the dithered - stellar field observations flattened with the corrected flat-field - image. -\end{itemize} - -\subsubsection{Non-linearity correction} - -The Non-linear correction calibration stage constructs a correction -model for low-level non-linearity effects in the detector. The tasks -and functions include: - -\begin{itemize} - -\item The Non-linear correction calibration stage constructs a - non-linear correction from a collection of images of a constant - source with varying exposure times. - -\item The Non-linear correction calibration stage construct a - non-linear correction which linearizes the detector fluxes - $<0.5\%$. - -\item The Non-linear correction calibration stage determines the - saturation regime, in which the non-linear correction is no longer - consistent to $<0.5\%$. -\end{itemize} - -\subsubsection{Telescope Astrometry Parameters} - -\begin{itemize} -\item The IPP Calibration system constructs static models of the - telescope astrometry parameters (e.g., distortion, detector warps) - once per week. - -\item The IPP Calibration system constructs static models of the - telescope astrometry parameters (e.g., distortion, detector warps) - with an accuracy to produce astrometry consistent to 30 - milliarcsec. - -\item The IPP Calibration system monitors changes in the telescope - astrometry parameters and issue a warning if the parameters change - by more than 2\%. -\end{itemize} - -\subsubsection{Zero-Point Monitoring} - -The IPP Calibration system determines telescope filter and camera -zero-points on a nightly basis with an accuracy sufficient to -determine photometry in the native filter systems to 5 millimags. \subsection{Modules} @@ -1794,5 +1128,5 @@ \item IPP Controller - Analysis Tasks. The IPP Controller shall -initiate the Analysis Tasks and monitor their output and exit + initiate the Analysis Tasks and monitor their output and exit status.\TASK @@ -1835,5 +1169,5 @@ The report, `The Pan-STARRS Image Processing Pipeline Computational -Challange' (PSDC-4xx-xx) discusses the assumptions and measurements +Challenge' (PSDC-400-006) discusses the assumptions and measurements made to determine the IPP computing requirements, for both the PS-1 configuration and the PS-4 configuration, under multiple assumptions