DM Science User Interface UML Use Case Model Handle Latest Revision Date 10/17/2013
Large Synoptic Survey Telescope (LSST)
Data Management Science User Interface UML Use Case Model
Schuyler Van Dyk, Jeff Kantor
LDM-244
Latest Revision Date: October 17, 2013
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DM Science User Interface UML Use Case Model Handle Latest Revision Date 10/17/2013
Change Record
Version / Date / Description / Owner name0 / 10/18/2013 / Initial installation (EA DM Apps: rev 1.154) / R Allsman
Table of Contents
Change Record i
1 Introduction 1
2 Science Usage and Analysis 1
2.1 Representative Science Use Cases 2
2.1.1 Science User 6
2.1.2 Determine the Properties of a Luminous Red Nova at Redshift 0.02 6
2.1.3 Find Signature of Baryon Acoustic Oscillations 9
2.1.4 Locate RR Lyrae Stars in a Galactic Halo Stream 13
2.1.5 Study the Formation Mechanisms of SDOs versus KBOs 15
2.1.6 Analyze Color-Color Diagram 18
2.1.7 Analyze Color-Magnitude Diagram 19
2.1.8 Analyze Light Curve of Luminous Red Nova 20
2.1.9 Cleanse the color-magnitude diagrams 20
2.1.10 Compute Auto Power Spectrum 21
2.1.11 Compute Cross Power Spectrum 22
2.1.12 Correct for Survey Systematics 23
2.1.13 Create Cleaned Color-Magnitude Diagram 23
2.1.14 Create Color-Color Diagram 24
2.1.15 Create Color-Magnitude Diagram 25
2.1.16 Create Corrected Color-Magnitude Diagram 26
2.1.17 Create Diagram of One Property Versus Another 27
2.1.18 Create Histogram 27
2.1.19 Create Power Spectrum Template 28
2.1.20 Determine Angular Diameter Distance As a Function of Redshift 28
2.1.21 Examine Coadd Image of Host Galaxy of Transient Event 29
2.1.22 Federate Cleaned Catalog Query with External Catalog 30
2.1.23 Filter out AstroObjects with proper motion 30
2.1.24 Fit Auto Power Spectrum 31
2.1.25 Fit Phase Function to Sources 31
2.1.26 Obtain photometry from the AstroObject Catalog 32
2.1.27 Perform Fitting of Object Color Distribution 33
2.1.28 Select AstroObjects of Given Period 33
2.1.29 Separate Sample Into Photometric Redshift Bins 34
2.1.30 Visualize Sample by Photometric Redshift 34
2.1.31 Visualize and Analyze Cleaned Color-Magnitude Diagram 34
2.1.32 Will the AstroObject Catalog have a column flag for AstroObjects with proper motion? 35
2.2 Science User Interface 35
2.2.1 Basic Archive Access 35
2.2.2 Data Analysis and Visualization 44
2.2.3 Alert Subscription 52
2.2.4 User Assistance/Help Desk 57
2.2.5 User Workspace Management 57
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DM Science User Interface UML Use Case Model Handle Latest Revision Date 10/17/2013
Data Management Science User Interface UML Model
1 Introduction
The Purpose of this Document is to define the Use Case Model for the LSST Data Management System (DMS) Science User Interface. This document is generated from Enterprise Architect.
2 Science Usage and Analysis
WBS 02C.05 Science User Interface and Analysis Tools
This WBS element is a summary element that contains the software, tools, and user interfaces specifying the Science User Interface and Analysis Tools which will support the following features:
- Provide coherent and intuitive mechanisms for scientists to access the data products (images, catalogs, alerts),
- Provide mechanisms for scientist to analyze and visualize the data sets and identify data subsets of interest
- Provide mechanisms for scientists to download, export or import data subsets of interest to alternative storage locations or into analysis environments
- Provide a mechanism for scientists to store, manage and manipulate large data subsets of interest using Data Center resources
- Facilitate federation of the data products with external data;
- Facilitate federation of the data products with external data;
- Serve documentation about the DMS and data products
- Provide automated and human assistance in working with the DMS and data products;
- Enable scientists to develop analytical codes by reusing existing DMS codes and integrating externally developed codes;
- Execute the analytical codes on local or external platforms;
- Capture and analyze the results of those codes.
NOTE: The UML for this WBS element is in development at this time.
Figure 1: Science Usage and Analysis Use Case Packages
2.1 Representative Science Use Cases
Figure 2: Determine the Properties of a Luminous Red Nova at Redshift 0.02
Figure 3: Find Signature of Baryon Acoustic Oscillations
Figure 4: Locate RR Lyrae Stars in a Galactic Halo Stream
Figure 5: Study the Formation Mechanisms of SDOs versus KBOs
2.1.1 Science User
2.1.2 Determine the Properties of a Luminous Red Nova at Redshift 0.02
Determine the Properties of a Luminous Red Nova at Redshift 0.02Description:
The scientific goal is to discover the properties and nature of a luminous red nova at redshift 0.02 discovered by LSST. This use case is from one of the four main Science Themes for LSST, Exploring the Transient Optical Sky. Luminous red novae (LRNe) are rare and currently not well understood in the local Universe. They typically have absolute magnitudes in the range of about -10 to -14. It is currently unknown what are the progenitors of these objects as a class, although it is speculated that at least one member of this class may have come about from a stellar merger. LRNe "fill the gap" between classical novae and faint core-collapse supernovae. They tend to vary in brightness over tens to hundreds of days. LSST should discover up to about 3400 such events per year.
This particular LRN first appears as Transient Alert. The Science User subscribes to the Alert Category including LRNe. It is at a distance of nearly 100 Mpc (redshift ~ 0.02), putting it near the faint limit at r of an individual calibrated exposure. The Science User wants to obtain all of the limits on detection of the DIA Source prior to discovery from the Forced Source Catalog and then obtain from the Source Catalog all of the available photometry in all bands for the LRN, in order to develop light and color curves for the object. These curves will be analyzed using several models for the properties of LRNe, in order to reveal the object's true nature.
The Science User will also retrieve the time sequence of calibrated exposures in order to display a movie of the time sequence and the apparitions of the DIA Source in the exposures.
The Science User will also examine the deep coadded exposure to study the nature of the host galaxy of the LRN.
The Science User will subsequently annotate the history of this Transient Alert.
Basic Course:
User Invokes: 'Retrieve Alerts' to obtain the Transient Alert of the newly-discovered LRN. The alert will consist of a data stream providing positional and brightness information on the new DIASource. The system will also provide a postage stamp image of the source.
System Invokes: 'Retrieve Postage Stamp'
User Invokes: 'Extract Time Series for Objects' to obtain all apparitions of the new source at its reported sky coordinates from both the SourceCatalog and ForcedSource Catalog, in all available bands.
System invokes: 'Query Source Catalog'.
System invokes: 'Query ForcedSource Catalog'.
User invokes: 'Save Query Result to User Workspace' to save the resulting data for further analysis.
User Invokes: 'Analyze Light Curve of Luminous Red Nova.' The Science User analyzes the query result saved to the User Workspace by displaying the light curve for the source.
User Invokes: 'Display Light Curve for Object' to view the 2D representation of brightness (magnitude) versus time for the new DIASource in each of the available bands, in order to study the nature of the variability for the new source.
User Invokes: 'Examine Coadd Image of Host Galaxy of Transient Image'. The Science User will examine the position of the new DIASource in a deep Coadd exposure, in order to determine where the source is relative to physical features (spiral arms, dust lanes, star-forming regions, etc.) in its host galaxy, to attempt to place constraints on the nature of the source's precursor star.
User Invokes: 'Query Image Archive' and the system returns the Deep Coadd Exposure
User Invokes: 'Extract Time Sequence of Exposures'. The Science User wishes to view a 'movie' of all of the calibrated exposures in which the new DIASource is detected, as a 2D representation of the previously-viewed light curve.
System Invokes: 'Query Image Archive' and returns the Time sequence of calibrated exposures for the DIASource.
User Invokes: 'Blink/Display Movie of Multiple Images' to view this time sequence as a 'movie'.
The Science User will then write an oft-cited manuscript on the results for the luminous red nova.
Alternate Course: N/A.
2.1.3 Find Signature of Baryon Acoustic Oscillations
Find Signature of Baryon Acoustic OscillationsDescription:
The scientific goal is to find the signature of baryon acoustic oscillations (BAO) in the entire LSST dataset. This use case is from one of the four main Science Themes for LSST, Constraining Dark Energy and Dark Matter. LSST will observe ~1000 Gpc3 of the universe, nearly a factor of 100 more than SDSS. Detection of BAO is "the new precision cosmology probe," allowing accurate and robust measurement of the properties of Dark Energy. Specific properties include Omega_matter, baryon fraction, sigma_8, and galaxy bias factor, based on the observed angular power spectrum, for a fixed Hubble constant and scalar index of primordial fluctuations. This is an ambitious, but supportable, project using the LSST data.
This use case emulates what Blake et al. (2007, MNRAS, 374, 1527) did with SDSS, and what Seo et al. (2012, ApJ, 761, 13), and Ho et al. (2012, ApJ, 761, 14) did with SDSS-III, using a sample based on photometric redshifts.
In this use case, the Science User performs a query of the AstroObject Catalog, extracting AstroObjects that meet specifications based on magnitude and color, primarily in gri, and star-galaxy separation, within a limited photometric redshift range, e.g., 0.45 < z < 0.65. The aim is to isolate luminous red galaxies, which possess the most robust photo-z's, due to the simplicity of their spectral energy distributions. Due to the uncertainties in the photo-z's, one cannot recover the evolution of the Hubble constant with z, H(z); there is also additional damping of the BAO, due to projection effects and difficulty in applying BAO reconstruction.
Once the query results are finely honed based on the color, magnitude, and star-galaxy separation, the Science User attempts to correct for the survey systematics, including residual stellar contamination, sky brightness variations, seeing variations,any color and magnitude offsets within the survey, extinction along the line-of-sight, and survey coverage, for which available survey coverage/depth masks need to be employed. Then, the sample is separated into bins by photo-z. Since LSST photo-z precision is to be 1%, the bin z-intervals can be quite small, e.g., Delta(z)=0.01 or 0.02. The slices or bins of the sample can be visualized in 3D to see the actual clustering of the galaxies.
Next, the auto and cross angular power spectra are computed using, e.g., quadratic estimators. One could combine the auto power spectra between z bins using covariance matrices. The cross power spectrum determines the covariance between different z bins and provides a useful analytical cross-check. An auto power spectrum template is then created, as a 2D projection of the 3D power spectrum, and is corrected for redshift-space distortions, assuming a galaxy bias; this is generally done using a "training set" based on spectroscopic z's. One needs to mimic within the template the nonlinear evolution of the BAO due to structure growth.
The Science User then measures the location of the BAO features by fitting the auto power spectrum with the template power spectrum. The observed locations of the BAO peaks in the power spectrum are determined by the angular diameter distance at each z, i.e., D_A(z), which is where the cosmological factors exist.
Basic Course:
User Invokes: 'Obtain photometry from the AstroObject Catalog', specifying appropriate ranges in magnitude, color, photometric redshift, and star-galaxy separation, and extracting AstroObjects that meet these specific ranges in properties.
User Invokes: 'Extract Objects with User-Specified Properties'.
System invokes: 'Query AstroObject Catalog' in order to acquire the dataset matching the Science User's specification which return AstroObjects and number of AstroObjects.'
User invokes: 'Save Query Result to User Workspace' to save the resulting data for further analysis.
User invokes: 'Create Color-Magnitude Diagram' specifying the data saved in the workspace and appropriate setup options in order to display the query results in both color and magnitude.
User invokes: 'Create 2D Display of Catalog Query Result'.
User invokes: 'Analyze Color-Magnitude Diagram' to select interactively with the graphical display AstroObjects in a certain color range that are also within a certain magnitude range. The aim is to isolate luminous red galaxies which are in a limited magnitude and color range.
User invokes: 'Save Subset of Query Result to User Workspace'
User invokes: 'Create Color-Color Diagram' specifying the data in the workspace and appropriate setup options in order to display the query results in one color versus another color.
User invokes: ' Create 2D Display of Catalog Query Result'.
User invokes: 'Analyze Color-Color Diagram' to further refine interactively with the graphical display the color selection of the AstroObjects of interest, i.e., luminous red galaxies, which exist only in a limited color range in the combinations of the various bands. The Science User then saves the result of this analysis to the User Workspace.
User invokes: 'Save Subset of Query Result to User Workspace' to save result of this analysis.
User invokes: 'Correct for Survey Systematics' to correct the query result subset for effects, such as residual stellar contamination, sky brightness variations, seeing variations, any color and magnitude offsets within the survey, extinction along the line-of-sight, and survey coverage, for which available survey coverage/depth masks need to be employed.
User invokes: 'Use Survey Coverage Masks'.
User invokes: 'Separate Sample Into Photometric Redshift Bins' to arrange the query result subset either into separate files representing each bin or by sorting the subset in order of photometric redshift.
User invokes: 'Visualize Sample by Photometric Redshift' to view the binned sample in 3D (sky position versus photometric redshift), which would reveal the clustering of the galaxies.