Context Navigation

← Previous Change
Next Change →

ippSRS.tex

Timestamp:

Oct 29, 2004, 12:01:49 PM (22 years ago)

Author:

eugene

Message:

updated PSDC numbers

File:

: 1 edited

trunk/doc/design/ippSRS.tex (modified) (17 diffs)

Legend:

: Unmodified
: Added
: Removed

trunk/doc/design/ippSRS.tex

-              r2192
+              r2241
  %%% $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}
 …
 \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}
 …
 \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
 …
 \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}
 …
 \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
 …
 \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
 …
 \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
 …
 \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
 …
 \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
+- 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}
 …
 %% 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
 …
 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}
 …
 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
+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}
 …
 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}
 …
   time. \VER{TEST}{TLR:17}
 \item completeness?
 \item contamination?
+\item \tbd{completeness}
+\item \tbd{contamination}
 \end{enumerate}
 …
 \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
-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}
 …
 \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
 …
 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

Note: See TracChangeset for help on using the changeset viewer.

Context Navigation

Changeset 2241 for trunk/doc/design/ippSRS.tex

Legend:

trunk/doc/design/ippSRS.tex

Download in other formats: