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ESA's Herschel Space Observatory to be launched in 2007 with a planned lifetime of three years, is the first space observatory covering the full far-infrared and submillimetre waveband (60 -670 microns). By probing so much further into the infrared than any other space telescope, it will have the potential to discover the earliest proto-galaxies and to clarify how they evolved.
Herschel's 3.5 metre mirror will also make it the largest telescope to be sent into space.
The Photodetector Array Camera & Spectrometer (PACS) is one of the three science instruments. It employs two Ge:Ga photoconductor arrays and two bolometer arrays to perform imaging line spectroscopy and imaging photometry in the 60 - 210 micron wavelength band.
The HERSCHEL Ground Segment is based on a common, object oriented database system - the Herschel Common Science System (HCSS), implemented using JAVA technology.
We present the PACS Common Software System as part of the common Ground Segment. The PACS Common Software System (PCSS) base on the HERSCHEL Common Software System (HCSS) written in a common effort by the HERSCHEL Science Center and the three instrument teams.
To demonstrate the use of PCSS as data reduction system we will outline the data reduction from Telemetry Ingestion onward; considering different processing steps like automatic processing and interactive processing.
We will describe the design of the Quick Look Analysis and Interactive Analysis system used for HK and Science Data Analysis. This system base on JAVA, technology using JYTHON as scripting environment.
We will specifically highlight the DataModel which we use within the interactive JYTHON/JAVA environment as framework for operations and visualization of data.
A data reduction software package is developed to reduce data of the near-IR integral field spectrometer SPIFFI built at MPE. The basic data reduction routines are coded in ANSI C. The high level scripting language PYTHON is used to connect the C-routines allowing fast prototyping. Several PYTHON scripts are written to produce the needed calibration data and to generate the final result, a wavelength calibrated data cube with the instrumental signatures removed.
ROOT is a C++ framework developed at CERN, Geneva. It was designed for high energy physics to handle and analyze large amounts of data in a very efficient way. Its main features are an object I/O - system, graphical tools and a C++ - interpreter. The INTEGRAL Science Data Centre (ISDC) is using ROOT as a graphical tool and as scripting language in the off-line analysis. But to use the full capability of ROOT for astronomical data analysis a link is required. Therefore we complete this system with a library called AstroROOT. With AstroROOT we can store astronomical data organized in tables and images in ROOT - files using the efficient I/O system of ROOT. We are developing a new astronomical image display for the ROOT framework. Finally we can use the build-in C++ interpreter as scripting language in an interactive session to analyze and to display astronomical data. I will present the usage of ROOT in an astronomical environment.
TERAPIX (Traitement Elementaire, Reduction et Analyse des PIXels de megacam) is an astronomical data reduction centre dedicated to the processing of extremely large data flows from digital sky surveys.
TERAPIX has developped a reduction pipeline, named SPICA, to produce calibrated images and catalogues of wide-field images, not exclusively MegaCam ones. This tool is freely available on the TERAPIX web site.
SPICA chains astrometry-photometry, images coaddition and quality control internal software. Through the images processing procedure, it builds a database which keeps a record of all monitoring information. This database can then be used for history requests.
The final images are sent back to the Canadian Astronomical Data Centre for archiving purposes.
The acquisition, pre-processing, analysis, archiving as well as the distribution of the INTEGRAL data are performed by the ISDC system at the Integral Science Data Centre (ISDC) in Versoix, Geneva.
The PreProcessing sub-system is one of the most critical components of the ISDC system. It continuously processes the entire INTEGRAL raw telemetry, science and housekeeping data. It sorts, decomutes,decompresses and reorganises data into time slices providing the first ISDC data level. This data level is directly usable by the scientists. The PreProcessing component implements all requirements defined by the scientists and it is able to face all artefacts that may occur in the telemetry such as telemetry gaps, duplicate packets, corrupted data, clock reset etc...
The originality of PreProcessing is its design. Indeed, the object oriented approach makes the program's core very flexible and independant from the INTEGRAL telemetry (reusable software).
The convenient of such conceptual model is the facility for the implementation of any new type of telemetry packet with absolutely no change to the architecture. This can be easily and quickly done by adding a new parser (inheritence and overloading concepts). The good results and performance obtained with the processing of INTEGRAL data encouraged us to reuse the same software for the PLANCK mission with minimum of changes. With the experience from the INTERGRAL and PLANCK missions, we are now building a software development kit of the PreProcessing software for future satellite missions.
The data from instruments of the Very Large Telescope (VLT) are automatically processed for standard basic data-reductions and artefact removal within instrument specific pipelines, which are operation-critical since all further data processing is based on their results. Currently, such pipelines are operational for seven instruments (excluding the VLT Interferometer), and have been written on the basis of three different software packages leading to considerable overlap and duplication of functionality.
Since 2001, the Data Flow System group of ESO has been working on a Common Pipeline Library (CPL) which is based on code already developed and used at ESO. The software is written in standard ANSI-C, employing object-oriented techniques, and uses the QFITS library (also from ESO) for data I/O. The CPL is intended to serve as the basis for all future instrument pipelines of the VLT.
The goals we want to achieve with CPL are: to streamline the code for different pipelines, to provide templates for standard algorithms, to support reuse of code, to eliminate, as much as possible, code duplication in different pipelines, to reduce the development time of pipeline-construction for new instruments, and to ease the maintenance and portability of the code.
The CPL is currently being used to build the operational pipeline for the GIRAFFE instrument which shall be released in December 2003.
We describe the roots of the CPL code, the development process of the CPL and the problems we had to overcome to reach the current stable alpha-release of CPL .
ESO is developing a number of Web-based applications, aimed at distributing proposal preparation information to operations teams located in Europe and Chile. Development started in 3Q02 with a tool to publish the results of the proposal submission and review cycle, and continued with an application centered around the review process itself, supporting the panel members (referees) and operations teams. The Moor project was recently launched to offer Web-based navigation from the submitted proposals to the approved observing runs to the corresponding archived frames, including all auxiliary and support information. Based on relational databases, JSPs and Servlet technology, the Moor will serve ESO operations teams as well as external users, integrating existing Web tools and offering controlled, end-to-end read/write access to Data Flow information, any time and anywhere.
LFI is one of the two instruments installed on board Planck, the M3 mission of ESA's Horizon 2000+ programme. Data reduction and analysis will be performed in pipeline mode at the Data Processing Center (DPC). The development of the DPC software is being performed in a collaborative way across a consortium spread across over 20 institutes in a dozen countries.
Individual scientists belonging to a Software Prototyping Team develop prototype code, which is then delivered to the LFI DPC Team. The latter is responsible to integrate the code, so as to produce the pipeline software to be used during operations. Integrated source code is fed back to the originators. This development takes advantage of tools defined within the Planck IDIS collaboration. A software policy has been defined, with the aim of allowing the DPC to run the best possible algorithms within its pipeline, while fostering collaboration inside the LFI Consortium and across Planck, and preserving at the same time the intellectual property of the code authors on the processing algorithms devised.
Dynamic data distribution is key factor in Grid computing. The DMC project aiming at improving collaborative research by allowing data to be shared more easily across applications cooperating within a federated environment is described. Beating heart of the IDIS information system, DMC is the data management system chosen by the Planck Satellite Survey Community, and specifically by the two Data Processing Centres, as a common infrastructure for the data handling applications being developed. Particular reference is here made to the design of the model, the data structures and to the portability of the Planck experience to other pipeline-oriented distributed environments.
Sherpa is the fitting application of the Chandra Interactive Analysis of Observations (CIAO) package. In this paper, we discuss how we have extended the capabilities of Sherpa in CIAO3.0 with the S-Lang programming language. Users are now able to load Sherpa data sets into S-Lang variables, and vice versa. Users also now have access to many new S-Lang functions which are the equivalents of Sherpa commands. Thus, it is now possible for users to write their own S-Lang scripts that load data into Sherpa, perform fits, and then copy the fit results out to S-Lang variables for further analysis in their scripts. Such scripts can be run from within Sherpa; it is also possible to load a Sherpa runtime module into another S-Lang application, and then run the same scripts in that application. We have also made it possible for users to run S-Lang scripts that modify the appearance of plots generated by Sherpa's plotting commands. Finally, settings that affect the execution of many Sherpa commands can be changed via S-Lang variables. These settings can be stored and read back in at the start of a Sherpa session. These extensions to Sherpa follow from our efforts to embed S-Lang in CIAO, first described in Doe et al. (2001). (This project is supported by the Chandra X-ray Center under NASA contract NAS8-39073.)
The SLANG/CIAO Synergy: Using S-Lang within CIAO
G. Germain, W. Mclaughlin, R. Milaszewski, J. Miller
Harvard-Smithsonian Center for Astrophysics, MS-81 60 Garden Street, Cambridge,Ma. 02138. gregg@head-cfa.harvard.edu
ABSTRACT. The S-Lang interpreted scripting language has been integrated in the CIAO infrastructure. This integration has transformed the capabilities of CIAO, and the CIAO infrastructure, and gives users and developers a means to integrate their own S-Lang functions wherever and whenever they wish, in a seamless manner.
Users and developers have several options available to them with regard to enhancing their analytical capabilities using S-Lang. One is to write a S-Lang function which can be called from CIAO applications such as CHIPS, PRISM or SHERPA, or any S-Lang prompt. Another is writing a C or C++ program which is made into a S-Lang intrinsic. This intrinsic can then be called directly from a CIAO prompt that is S-Lang-capable, or a S-Lang prompt, and, of course, from any other S-Lang program. A key element is that a a CIAO application can call a S-Lang function/intrinsic, and that a S-Lang function/intrinsic can call a CIAO application.
This paper describes the mechanisms available which can be used to integrate S-Lang functions, or C/C++ based S-Lang intrinsics, within CIAO applications, such as CHIPS or PRISM, or applications outside CIAO. Two classic applications will be described: A histogram plotting function and UNIVAR - a C++ univariate table lookup program. Both of these can be called from within PRISM, CHIPS or a S-Lang prompt. Each show different methods of getting data to and from the functions, the design choices one makes in deciding whether to write the function in C/C++ or S-Lang, and how CIAO functions, such as the CHIPS plotting routine, can be called from within S-Lang applications.
This work was done as part of CXC contract (NAS8-39073).
Recent developments in the AST library for managing WCS information are described. These include support for spectral coordinate systems, and compliance with FITS WCS papers I, II and III.
The goal of the Astronomer's Proposal Tool (APT) project was to improve the Hubble Space Telescope proposal preparation process, in order to provide users with a more intuitive, visual, and interactive experience by means of state of the art technology. The APT is an integrated tool suite for the Hubble Space Telescope (HST) proposal preparation, replacing the current systems used for HST proposal preparation.
The HST proposal process consists of two phases. In Phase 1, astronomers provide scientific motivation and enough detail about the proposed observations that the feasibility can be assessed and the requested amount of telescope time can be justified. Successful Phase 1 proposers then provide a Phase 2 proposal. A Phase 2 proposal contains a complete specification of the observations which when processed allows the observations to execute onboard the telescope. Both of these tasks require software support to help the user meet scientific and technical goals, and provide feedback on what has been requested.
APT was released and used by the HST community for the first time this past year. This paper will discuss the APT Toolkit, including both the Phase 1 and Phase 2 tools. This paper will also discuss feedback received on APT from the HST user community.
GILDAS and MIRIAD are two state-of-the-art data reduction packages for the current generation of millimeter instruments. GILDAS is used daily at the Plateau de Bure Interferometer as well as several single dish telescopes (e.g. IRAM-30m, CSO) while MIRIAD is used at BIMA, ATCA, OVRO and WSRT. Although the core functionalities needed to reduce millimeter interferometry data are well covered in both packages, it has recently been recognized that the strength of both packages are complementary. GILDAS has good data analysis programs while MIRIAD has a complete set of calibration and imaging algorithms in particular to handle polarization. It is thus interesting to study the possibility of interoperating both packages in a user-friendly way. Both packages have pretty different implementation philosophy: GILDAS is principally made of large stand-alone programs while MIRIAD is built around a large collection of individual tasks. Moreover, they use different command line interfaces and, in detail, data models. In a first step toward interoperability, we decided to run both packages under python and to exchange data using FITS. This poster describes the porting of both packages under python. It also shows an example where data from Plateau de Bure interferometer has been calibrated inside GILDAS and imaged inside MIRIAD, both packages being called from the same python process.
Efforts are underway at the Chandra X-ray Center to develop a new level of data processing capability which will result in the creation of a source catalog spanning the full set of Chandra observations. Level 3 processing will include detailed source properties derived from all available Chandra data. The resulting catalog will provide easy access to Chandra data for an expanded number of astronomers, particularly those less familiar with analysis in the X-ray regime. It will allow easy searching of the archive for specific sources or for statistical properties of different classes of targets. In addition, consistent sets of data products along with all relevant calibrations will be available for detailed analyses.
Work has begun on developing a preliminary data processing pipeline, combining existing processing tools and identifying functionality which needs to be developed. Some effort has been made to identify a quick source detection algorithm which can work in the presence of the low-count background and source photons typical of Chandra X-ray data, and also be robust enough to find multiple or extended sources. Eventual goals of Level 3 processing include refining source detection and properties by simultaneously fitting multiple observations, and cross-matching identified sources with other catalogs. In this paper we present the current design, challenges, and discuss the various analysis tradeoffs. This project is supported by the Chandra X-ray Center under NASA contract NAS8-39073.
The Flexible Image Transport System (FITS) is a powerful and widely adopted means of exchanging Astronomical Data. There are also a great number of tools and libraries available on many platforms to facilitate working with FITS.
We present the Fits.Net, A library written to facilitate development of astronomical data analysis tools on the Microsoft.Net Platform. This has been developed as a wrapper over one of the very popular and time tested FITS libraries, CFITSIO. The Fits.Net library merges the advantages of speed and ruggedness of CFITSIO with the language independence of the Microsoft.Net technology and a simple Document Object Model (DOM). We believe this library will be intuitive for .NET programmers.
We present the design and usage patterns of the library in C#. We also discuss performance issues of the library. Finally we present a number of applications and web services, which are currently running on this library.
SCUBA-2, scheduled for delivery in late 2005, will be the largest submillimetre bolometer array ever built. Data from this instrument are stored at a rate of 200Hz generating approximately 0.5TB per night; unheard of for a submillimetre array. This paper will discuss the unique algorithmic processing challenges of this instrument and the overall design of the planned pipeline.
An overview of the INTEGRAL operations and ground segment will be presented with an emphasis on the INTEGRAL Science data center.
The INTEGRAL data organisation, the main technical choices and the performance of the downlink system (from TM receipt to standard products distribution) will be reviewed, illustrated by a selection of scientific results of the mission.
This contribution will give an overview of the operational software for the data processing and handling at the INTEGRAL Science Data Centre (ISDC).
The ISDC's main tasks are real-time detection of Gamma Ray Bursts and new or varying sources. In addition standard products like images, light curve and spectra are to be generated, stored in the INTEGRAL data archive and distributed to the community.
The overall ISDC system is broken down into sub-systems for which we will briefly present the main characteristics like functionality and operational performance.
In a second part further details will be provided on specific parts of the ISDC software that are of interest for other projects. Among those are re-useable software libraries, an application for TM deconvolution, as well as interactive analysis tools for data reduction and visualisation.
The know-how and the tools developed at the INTEGRAL Science Data Centre (ISDC) can also serve other scientific space missions. This is clearly illustrated by Geneva's contribution to the level 1 data processing for the Low-Frequency Instrument (LFI) of ESA's Planck mission. We will present here the tools being developed for Planck with emphasis on the efficient reuse of the work invested for the INTEGRAL mission.
We are developing an automated image reduction and analysis pipeline for WFI (mounted on the 2.2-m MPG/ESO telescope at La Silla) images to complement Querator, the custom search-engine which accesses the astronomical image archives based at the ST-ECF/ESO centre in Garching, Germany. The image reduction and analysis is performed using an 40-processor Origin SGI based at NUI, Galway. To increase our dataset we complement the reduction and analysis of WFI archival images with the analysis of pre-reduced co-spatial HST/WFPC2 images, and hope to include other archives as data sources. Our pipeline includes image reduction, registration, astrometry and photometry stages. We describe how we overcome such problems as missing or incorrect image meta-data, interference fringing, poor image calibration files, etc, and we discuss how such a pipeline can benefit astrophysical research, specifically the long-term optical variability of Brown Dwarfs. The pipeline was written using tasks contained in the IRAF environment, and linked together with Unix Shell Scripts and Perl.
I describe the design of a simple IRAF-based reduction and analysis pipeline, developed for the BFOSC instrument on the 1.52m Cassini Telescope at Loiano, run by the Osservatorio Astronomico di Bologna. The original motivation for this was pedagological: to enable our NUIG undergraduate students to quickly process their observations while still 'at the telescope', thus enriching their learning experience during their annual field-trip to Loiano. However, the current and future development of the pipeline is also being driven by our research programmes involving BFOSC data. On the basis of header keywords, raw frames are automatically grouped and processed (CCD reduction, coaddition, photometry, deconvolution, RGB-tricolour representation, and basic astrometry, with spectroscopy partially implemented as of now). Of particular interest is that the xFOSC family of instruments produced by the Astronomical Observatory of Copenhagen, which includes BFOSC, share identical design and operation. This should make it simple to adapt the pipeline to any of the ten FOSC instruments: ALFOSC on the Nordic Optical Telescope, DFOSC on the ESO/Danish 1.54m, and so on.
MAXI is an X-ray all-sky monitor which will be loaded onto the Japanese Experiment Module of the International Space Station (ISS) in 2008. With a high X-ray sensitibity of two kinds of detectors (Gas Slit Camera, GSC and Solid-state Slit Camera, SSC), MAXI monitors more than 1,000 X-ray sources, and provides quasi-real-time data of, for instance, AGN variability and X-ray Novae through the internet.
X-ray event data processed by the onboard data processor (DP) are downloaded through the 1553b and ether networks on the ISS to the NASDA and NASA ground stations. All the data are once stored to a database in the Operations Control System (OCS) at NASDA in Tsukuba, and transferred to our MAXI database.
Since the FOVs of the detectors change every moment, all the X-ray event data with 16--64 bit each are stored into the MAXI database event by event. As a result, the database has 10--100 Giga records (events) and ¥sim 0.1--1 TB in size in 2 years (mission life). We have just built this huge 'photon event' database for the 1553b data. The brief introduction of all the MAXI software system from the DP to the internet access and the first performance test of the MAXI database using Sybase, Oracle and PostgreSQL will be presented.
The Little Template Library is an expression templates based C++ library for array processing, image processing, FITS and ASCII I/O, and linear algebra. It is released under the GNU Public License (GPL). Although the library is developed with application to astronomical image and data processing in mind, it is by no means restricted to these fields of application. In fact, it qualifies as a fully general array processing package. Focus is laid on a high abstraction level regarding the handling of expressions involving arrays or parts thereof and linear algebra related operations without the usually involved negative impact on performance. The price to pay is dependence on a compiler implementing enough of the current ANSI C++ specification, as well as significantly higher demand on resources at compile time. The LTL provides dynamic arrays of up to 5 dimensions, subarrays and slicing, support for fixed size vectors and matrices including basic linear algebra operations, expression templates based evaluation, and I/O facilities for columnar ASCII and FITS format files. In addition it supplies utility classes for statistics, linear and non-linear least squares fitting, and command line and config file parsing. YODA (Drory 2002) and all elements of the WeCAPP reduction pipeline (Riffeser et al. 2001, Goessl & Riffeser 2002, 2003) were implemented using the LTL.
ORAC-DR---a flexible reduction pipeline---was originally developed by the Joint Astronomy Centre for real-time inspection of reduced data at its telescopes. Starlink is extending ORAC-DR to process at home institutions data from other observatories, notably ESO, whose instruments make no provision for ORAC-DR. This poster outlines the problems encountered and solutions implemented or proposed, illustrated with reduced data from a selection of instruments. The poster also describes new facilities needed for tailoring of recipes by users.
The data streams expected from the SuperAGILE instrument (SA), onboard the AGILE gamma-ray mission, are continuous and massive flows (20 kb/s) of raw information sent to ground for a minimum of 3 years, plus a larger rate during ground tests. Data coming from the detector concern physical measurements and equipment housekeepings. We developed an information system to handle and archive the data produced at first by the prototypes and later on by the flight model. A big effort in the design phase has led us to achieve an integrated modular software system responding to most of the functions needed to extract knowledge among SA archives. We will present the formal description of the data, the relations among them and the operations applied on data with the aid of formal instruments such as Entity-Relationship and UML diagrams. We will also show an implementation of the system with functions of reception, pre-processing, archiving and analysis developed with Object Oriented and DBMS open source software instruments.
The AIPS++ (Astronomical Information Processing System) Project has developed a codebase of libraries, tookits, and applications for the analysis of radio astronomical data. We discuss the overall architecture and core components of this package along with the current technologies in use. The existing package features many innovative applications which are required for the next generation telescopes under development (e.g., multi-field, multi-scale, and wide field imaging algorithms, full primary beam Stokes I,Q,U,V imaging, automated and interactive statistical data editing, flexible calibration and self-calibration based on the telescope measurement equation (Hamaker, Bregman and Sault, 1996)); we highlight some of this functionality and discuss the efforts underway in performance improvements needed for the high data rates of current and future instruments (e.g. ALMA). Future directions for both applications and technology upgrades are also discussed.
We present a comprehensive scientific data model for the Virtual Observatory. This is a logical model designed to describe the scientific process and results in a uniform fashion; it is not a physical data model one would implement directly. Rather, the design goal is to be able to transform a user data model into this logical model for exchange with other users (for inter-data-centre exchange, for example). The data model is composed of several packages (Experiment, Value, Standards, and Phenomenology) which we describe in detail.
The science team for the Advanced Camera for Surveys has developed a data analysis pipeline to automatically process GTO program observations. This pipeline is composed of modular, object-oriented software that communicates with the ACS Archive via XML messages. It can be used interactively by users for targeted analysis or as a completely automated analysis run on logically grouped data. The processing steps include: empirical determination of image offsets and rotation, cosmic ray rejection, image combination, object detection and photometry, photometric redshift estimation.
The NOAO Mosaic Pipeline is a fully distributed and parallel system able to efficiently process and reduce mosaic imaging data. While being developed with the NOAO Mosaic Imagers in mind, it is general enough that it could be easily customized to handle other mosaic imagers as well.
Its salient characteristics include: * Science driven development. * Based on a comprehensive Data Model. * High degree of modularity and code reuse. * Support for a non static, freely variable number of computing nodes. * Dynamic, XML based configuration of modules and pipelines. * Dynamic master-slave hierarchy among the nodes. * Dynamic routing of data through available nodes. * Sophisticated predictive load balancing. * Database based calibration file management. * High degree of abstraction from the underlying implementation.
The present paper describes: * How single modules are dynamically organized in processing pipelines. * How the different pipelines are dynamically chained together. * How pipelines running on different nodes interact with each other. * How predictive load balancing is implemented in our System. * How data flow and processing are controlled.
The NOAO Mosaic Pipeline processes observations from the NOAO Mosaic Imagers. It provides immediate feedback on the quality of the data shortly after collection. The pipeline makes use of distributed and parallel computing to achieve high throughput and a degree of fault tolerance. The target computing platform is a cluster of commodity off the shelf processors. The NOAO Mosaic Pipeline provides a number of Graphical User Interfaces (GUIs) for controlling and monitoring different aspects of the pipeline including data management. Through the use of the control GUIs, an operator can start and stop the pipeline, diagnose problems in the pipeline, and correct and restart stalled observations. Scientists can enter calibrations to the data manager using the Data Manager GUI. In addition, scientists can monitor data quality and the progress of pipeline processing through the use of monitoring GUIs. Multiple instances of monitoring GUIs for one pipeline may exist simultaneously, thus facilitating collaboration between scientists. The pipeline functions independently of the GUIs, allowing GUIs to connect and disconnect without interrupting processing. Finally, customized GUIs may be easily interchanged and utilized within the pipeline framework.
We have developed a modular image analysis pipeline which carries out end-to-end analysis of CCD data, beginning with raw frames off the telescope and resulting in identification of interesting optical transients. Frames are debiased, flattened, cross-talk corrected and astrometrically calibrated. Template images of the field are then brought into alignment with the new frames, convolved to match point spread functions and subtracted from the new data (using the algorithm of Alard and Lupton). Object detection is performed on the resulting difference frames and a series of tests are carried out to suppress false positives. The pipeline consists of a backbone written in Perl which does book-keeping and process management, and a set of programs written in C which do the actual operations on the data. Results are then passed to an SQL database. The pipeline is readily adjusted to accommodate images from diverse telescopes and instruments, and has been successfully used for a variety of ongoing surveys, including the ESSENCE supernova search, the SuperMacho microlensing survey, the Sloan survey, and the LONEOS solar system survey. This work was supported by funding from the McDonnell Foundation.
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