The Subaru 8.2m Telescope Control System






Contract 02/0043 – 009771






24 February 2003





Rutherford Appleton Laboratory

Space Science & Technology Department








Reason for change


24 February, 2003

First Draft












1      Introduction.. 5



2      The Subaru Computer Architecture. 6

2.1        HARDWARE. 6

2.2        SYSTEM SOFTWARE. 7


3      The Subaru Software Subsystems.. 7

3.1        TSC.. 7

3.2        SOSS. 9

3.3        DASH.. 10

3.4        STARS/MASTARS/SMOKA.. 11

3.5        GENERAL. 11

4      Future Observing Scenarios.. 12

4.1        INTRODUCTION.. 12

4.2        NOD & SHUFFLE. 12

4.3        SERVICE OBSERVING.. 12

4.4        ADAPTIVE OPTICS. 12

5      Recommendations.. 13

5.1        TSC.. 13

5.2        SOSS. 13

5.3        STARS/MASTARS/SMOKA.. 14

5.4        DASH.. 14

6      TSC Improvement.. 14



7      Concluding Remarks.. 16

7.1        OVERVIEW... 16




8      APPENDIX.. 19

Observatory Control Systems in General.. 19

8.1        Observation Control System... 19

8.2        Telescope Control System... 20

8.3        Instrument Control System... 22

8.4        Quick-Look facilities. 22

8.5        Data Handling System... 23

8.6        Logging and Fault Reporting.. 23

8.7        Data Reduction Pipeline. 23


1          Introduction



1.1.1        In this report we examine the control system software of the National Observatory of Japan’s 8.2 metre Subaru telescope and compare it with the equivalent systems used by other similar telescope projects such as Gemini, ESO VLT and Keck. We have paid particular attention to areas in which changes might result in significant improvements in observing efficiency and where the existing Subaru systems might struggle to support future instruments and observing modes.


1.1.2        The study was carried out during February 2003. The authors spent about a week on the Big Island, received a series of presentations and observed the operation of the telescope with SUPRIMECAM, FOCAS_MOS and ICRS (both with and without the adaptive optics systems).


1.1.3        The systems directly involved in observing, namely the telescope control system and observatory control system, were examined in some detail, the data archive and data analysis system less so and the instrument control systems—which are different for each instrument—not at all.


1.1.4        The report begins by identifying the main elements of the Subaru software, mainly for background but also with some general comments. It then goes on to look at the architecture of the system—the various levels of computer and networking—before dealing with the software in detail. A section on future trends introduces a set of suggestions and recommendations for change, and the report concludes with a summary of the possible ways forward.


1.1.5        A checklist of the main features needed in observatory control software is given in an appendix and referred to at various points in the report.



1.2.1        The telescope control system (TSC) is in direct control of the telescope; it makes the telescope and enclosure slew and track, controls the instrument and image rotators, guides the telescope, and maintains the figure and alignment of the telescope optics. It also handles the many engineering data logging and maintenance functions required to operate the telescope hardware.


1.2.2        The Instrument Control Software controls the instrument hardware and detectors. Each instrument has its own control system and, apart from using a common toolkit for the interface to the observatory control system, does not have any software in common with other instruments.


1.2.3        The Observation Control System (SOSS) coordinates the operation of the telescope and instrument in order to collect astronomical data. It has an interface with both the TSC and the instrument control software.


1.2.4        The Data Archive (STARS/MASTARS/SMOKA) stores all astronomical data and provides facilities for searching for and retrieving the data and implements the observatory’s data access policies. There are three archives, one in Hilo (STARS), a copy in Mitaka (MASTARS), and the archive of publicly available data (SMOKA).


1.2.5        The Data Analysis System (DASH) is a system for implementing automatic data reduction pipelines and providing offline data analysis facilities to users.


1.2.6        The principal deficiencies reported by Subaru management and staff were:

·        Software maintenance, outsourced to Mitsubishi and Fujitsu, is expensive and response to change requests is slow.

·        Observing efficiency is poor, at least for some instruments; dithering performance is especially slow.

·        Users find observing preparation arcane and the online user interfaces too complicated and inconsistent.

·        DASH is complex and little used.


2          The Subaru Computer Architecture

2.1         HARDWARE

2.1.1        The computer hardware chosen for workstations (SUN sparc except for the TSC workstation which is a DEC alpha) and mid-level processors (DEC alpha VME) are all widely deployed across the computing industry and are unlikely to cause maintenance problems in the foreseeable future. Replacement with more powerful or cheaper-to-maintain systems should be relatively easy.


2.1.2        The local control units are based on industry standard processors (Motorola 68030 and PowerPC) but are in any case unlikely to need upgrading and replacements for failed units will be readily available.


2.1.3        The overall hardware architecture is similar to other 8 metre telescopes, the only unusual features being the use of RS422 for communications between the MLPs and LCUs and the location of the MLPs and LCUs in a computer room rather than on the telescope structure. The number of VxWorks systems is rather smaller than on other comparable telescopes (e.g. more than ten on Gemini and hundreds on each VLT unit telescope).


2.2.1        The operating systems used on workstations (SUN Solaris except for the TSC workstation which runs DEC OSF/1) and mid-level processors (VxWorks) are all widely used in astronomy and elsewhere and enable easy migration to new hardware (e.g. to Intel PCs for workstations and PowerPC for MLPs) if this becomes desirable for price/performance reasons. Migration to another Unix workstation operating system (e.g. Linux) would probably also be possible with too much difficulty.


2.2.2        The inter-processor communication protocol (except between the MLPs and LCUs) is the SUN RPC (Remote Procedure Call) which is in widespread use, is fully documented in publicly available documents and is implemented on most operating systems.


2.3.1        The network infrastructure is all IEEE 802.3 (ethernet) and can be readily and cheaply upgraded to higher bandwidth without impacting the rest of the system.


3          The Subaru Software Subsystems

3.1         TSC

3.1.1        The TSC performs its primary role of tracking the telescope and enclosure, controlling instrument and image rotators and auto-guiding competently. It is helped in this task by the excellent performance of the telescope itself, which points well and has exceptionally good open-loop tracking. However, some important features (see Section 8.2 in the Appendix) are absent, and certain aspects of the TSC are slower than they should be; we concluded that software improvements are needed in a number of areas, as follows.


3.1.2        The mid-level processor passes mount and rotator tracking demands to the corresponding LCUs every 2 seconds. This results in a delay of up to 2 seconds before the telescope responds changes in target position. This is a serious limitation and is implicated in the present unacceptably slow dithering performance (cf. 8.2.24).


3.1.3        The TSC has no provision for automatically placing the target object at nominated coordinates in the focal plane (cf. 8.2.15) other than the optical axis (normally coincident with the image or instrument rotator axis). This means that the only mechanism for “offsetting” the telescope—for example to centre the object on a spectrograph slit—is to describe the offset in right ascension and declination. This has a number of undesirable consequences:


§         The object position reported by the telescope, and possibly recorded with the data, will be incorrect.


§         The necessary offset can be awkward to calculate. For example, offsetting by a specified number of pixels on the detector requires a calculation involving the (α,δ) of the target, the rotator position angle and the orientation of the instrument with respect to the rotator; furthermore the result is time dependent.


§         Subsequent adjustment of the field orientation will cause the object to move on the instrument, necessitating re-acquisition and hence costing time.


3.1.4        Trailing of images due to field rotation occurs when tracking within 5 degrees of the zenith. The telescope should be capable of maintaining accurate field orientation to within 0.5 degrees of the zenith, so this problem may be a software issue probably related to the influence of the telescope pointing model on the field orientation (cf. 8.2.13).


3.1.5        The TSC should warn the observer when the object being observed will pass through the zenith blind spot. We noted that while tracking through the zenith region not only was no warning given but the reported limits were at times erroneous (cf. 8.2.13).


3.1.6        There is no provision for taking account of a difference in effective wavelength between the guider and science instrument (cf. 8.2.6). This causes trailing of images during long exposures due to changes in refraction. This “atmospheric dispersion” or “chromatic differential refraction” effect can amount to several arcseconds.


3.1.7        The auto-guider supports just one guide star acquisition mode (cf8.2.14): when guiding is turned on the guide star is “frozen” at its current position. This means that blind acquisition of invisible objects relies on the (exceptionally good) open loop tracking of the telescope. This may not be adequate for the very small slit sizes made possible by adaptive optics and in any case requires that a nearby visible object is acquired first, a potentially time-consuming operation. An acquisition mode where the guide star is pulled to a position on the guider CCD calculated from the guide star catalogue position would enable acquisition in a single operation, with an accuracy limited only by the quality of the guide-star and science-target coordinates and the precision of the guide probe positioning (the latter is not very exacting given the large plate scale on an 8 metre telescope).


3.1.8        Pointing-test observations are logged in a “relative” form that means that analysis requires knowledge of the pointing model installed at the time the test was run. This can cause difficulties when analysing historical data to detect long-term trends; it would be better to log absolute position and time information (cf8.2.17).


3.1.9        We saw maps of pointing calibration stars on a regular (α,δ) grid. This biases the pointing model to the region around the pole, which is not desirable. Test points that are equally dense all over the sky would be better (cf. 8.2.17).


3.1.10    Adding new terms to the telescope pointing model requires modifying, or adding to, code in the TSC. This is a problem for Subaru because of the long turn-around for software modifications by Mitsubishi. Also, it has led to an approach where azimuth track effects are treated with a separate model; a single pointing model that includes both these effects and the conventional geometrical terms could deliver better results.

3.2         SOSS

3.2.1        The SOSS skeleton files implement an exceptionally powerful and flexible language for sequencing concurrent operations on the telescope and instruments (cf. 8.1.3). The code is not particularly elegant, but probably does the job of controlling the telescope and instrumentation as well as anything that could replace it.


3.2.2        However, there is a lack of “astronomer friendly” tools for generating observing scripts (cf. 8.1.1), and this has given SOSS a bad name with users. Preparing for an observing run is a laborious and error prone process for the astronomer (and the support scientist as well). As well as preparation tools, script validation tools are also needed to avoid errors that waste telescope time.


3.2.3        The user interface presented to the support scientist running the observations is at heart a command line system, supplemented by a rather crude GUI. The observers find the GUI unwieldy and prefer to use the command line interface even though the only editing facility for the rather long and complex command lines is to cut-and-paste from previously executed commands. What would be better is a set of graphical interfaces organized with the observer in mind, with commands grouped by function and reflecting frequency of use.


3.2.4        The skeleton files (for ICRS at least) contain numerous “sleeps” (interval waits), typically of 1 second. This is a bad sign and may be one reason for the very slow performance of the system. Better understanding of the real-time properties of the system is needed.

3.3         DASH

3.3.1        We did not examine DASH in detail so these remarks are based solely on material presented to us. We noted that the system is comprehensive and uses modern software techniques. It is forward-looking and should blend well with future “Virtual Observatory” efforts.


3.3.2        DASH has not been much used so far in its offline data analysis role, because astronomers find it difficult and complicated in comparison with well-established and familiar interactive data reduction tools such as IRAF.


3.3.3        However, its intended role in providing an automated data reduction pipeline is another matter. Although little used at present, this pipeline function will increase in importance as the observatory moves away from “classical” observing, where the astronomer is present at the telescope, and moves towards queue mode and service observing where the telescope is operated by Subaru staff on behalf of the astronomer. The ability to do at least preliminary data reduction in some automated way will become essential in order to ensure that the data provided to the astronomer are of the highest quality.


3.3.4        In short, we believe that an automated data reduction pipeline is an essential ingredient of a successful service observing operation and there is no reason why DASH should not fulfil this requirement. Writing the necessary data reduction procedures will require significant effort but will result in savings in the long term.


3.4.1        We did not examine the data archive systems in detail so these remarks are based solely on material presented to us.


3.4.2        The Subaru data archives compare well with the archive systems being used by other optical/infra-red observatories. The support staff have a clear vision of where improvements are needed and how these can be achieved.


3.5         GENERAL

3.5.1        Subaru is a good example of what can be achieved by the Japanese government’s policy of forming collaborations between industry and academia: Mitsubishi and Fujitsu have done an excellent job of implementing what the Subaru designers asked for. However, the consequent outsourcing of software maintenance to Mitsubishi and Fujitsu has become a serious limitation on what the Observatory can do and in what timescales. It is essential to bring about circumstances such that (i) Subaru has full access to source code for all the non-industry-standard software it uses, and (ii) the Observatory can make its own revisions and bring them into use without delay.


4          Future Observing Scenarios

4.1         INTRODUCTION

4.1.1        In this section we discuss a number of observing modes that are likely to become important in the future and that illustrate how some of the deficiencies outlined in Section 3 could adversely affect future development of the Observatory.

4.2         NOD & SHUFFLE

4.2.1        Nod and Shuffle[1] is a technique recently developed for improving sky subtraction on optical detectors limited by readout noise. It involves simultaneously moving the telescope and the charge on the detector. Implementation of this technique requires that the telescope offsets exactly match the pixels on the detector. This is extremely difficult to achieve if the telescope does not support offsetting in the focal plane, as is the case at present with Subaru.


4.3.1        It is generally accepted that making the most efficient use of today’s large telescopes means moving away from the traditional mode of operation where individual astronomers are allocated a fixed period of telescope time towards “service observing” where astronomers apply for data rather than telescope time. The observations themselves are carried out by staff astronomers, who make decisions about which programs to execute, and when, in order to maximize efficient use of the telescope and make best use of the prevailing conditions.


4.3.2        In order to run such an operation efficiently it is essential that observing proposals contain all the detail necessary to allow the observations to be carried out without reference to the requesting astronomer. This can only be achieved if the astronomer has access to easy-to-use tools for generating the observing proposal.


4.3.3        Efficient operation is only possible if observing programs are free from errors at the point that they are executed on the telescope. This requires that the support scientists have tools available to them for validating programs against the currently available instrument configurations (available filters, gratings etc.)  before placing them in the queue for possible execution.


4.4.1        The telescope control system must take account of the astrometric changes introduced by AO systems, such as the effects of atmospheric dispersion compensators and, in the multi-conjugate case[2], the need to predict changes in the relative positions of three natural guide stars to better than the diffraction limit.


5          Recommendations

5.1         TSC

5.1.1        The protocol for sending tracking data from the MLP to the mount and rotator LCUs should be redesigned to eliminate the 2-second latency. The present rigid “timing diagram” view should be replaced with a flexible approach where determining the next demand is decoupled from “just in time” samples of the tracking locus. The aim should be to make the full control bandwidth of the telescope mechanics accessible to instrument applications.


5.1.2        The TSC should be upgraded to support an integrated approach to rotator and guider control and focal plane management such as that provided in the Gemini TCS and in the TCSpk pointing kernel[3]. How to go about this is complicated by contractual issues with Mitsubishi and the possible non-availability of the source code of the current system; possible ways forward are discussed in Section 6.

5.2         SOSS

5.2.1        High priority should be given to the creation of an observation preparation tool, because neither writing a tool from scratch nor adapting an existing tool from another observatory to support Subaru’s instruments will be a rapid process. The output from such a tool would be the observing scripts that are currently generated by hand; this means that the interface to SOSS is already defined and consequently it would be feasible to contract out the development work. Section 8.1.1 in the Appendix lists some of the functions required.


5.2.2        The cost of developing a preparation tool is hard to estimate because it depends so much on the level of functionality required. A simple but nonetheless useful  “form-filling” GUI could be developed for perhaps as little as 1 staff year plus 0.25 SY per instrument. On the other hand a fully featured tool such as the Gemini Observing Tool could cost 20 SY.


5.2.3        Before embarking on development, we recommend that Subaru examines a representative sample of the preparation tools in use by other observatories and explores the possibility of adopting an existing tool. Gemini, the Joint Astronomy Center (JAC) and ESO are all candidates. If feasible this approach could yield considerable cost savings.


5.2.4        The problem of the slow operation of SOSS needs to be addressed by a programme of measurement and analysis in order to understand where improvements are both needed and possible. There is unlikely to be one single cause so early dramatic improvements are unlikely. In particular we would not expect CPU speed or network bandwidth to be a primary limitation, and advise against any plan to upgrade hardware before the real causes of the slow performance have been identified.


5.2.5        The SOSS software is maintained by Fujitsu, leading to high cost and slow response to change requests. However, most of it functions well, and a complete rewrite would probably not be cost-effective. What is needed is acquisition of the source code and the development of a Subaru in-house capability to maintain and enhance the system. Developing new user interfaces to meet the needs of Subaru support astronomers would be one such enhancement; it is essential to get into the position where good ideas can quickly be put into practice and new observing modes tried out as the need arises.



5.3.1        The current archives appear to be well able to support the requirements of the observatory and we see no need for any changes in this area (cf. 8.5.1).

5.4         DASH

5.4.1        Future development of DASH should be focused on the needs of service observing, including the development of the pipeline data reduction capabilities (cf. 8.7). It would also be useful to look into the JAC ORAC-DR system as an example of what can be achieved in this area.


6          TSC Improvement


6.1.1        The biggest single improvement to the current system would be to increase the degree of automation of the TSC, offering a smarter interface to instruments. We have confidence in the astrometric accuracy of the present TSC, but it is clear that moving certain associated computations, in particular the (x,y) to (α,δ) transformations, out of the higher level software and instruments and into the TSC will pay dividends, delivering pointing integrity and making slick and accurate instrument applications possible.


6.1.2        A TSC upgrade of this sort could be done so as to preserve the existing command interface, offering all the current (low-level) capabilities. Consequently the upgrade would be transparent to SOSS, which could use the new TSC without change. New commands would be added to the TSC interface in order to give access to the new functionality, and SOSS could be modified to take advantage of these as required.


6.1.3        The cost of upgrading the TSC with a new, integrated, pointing kernel is hard to estimate since it depends a great deal on the internal architecture of the current system; it might, for example, be equivalent to 2-3 staff years to provide TCSpk and the associated RAL kernel software[4] and develop interfaces to the Subaru systems. The work would require cooperation from Mitsubishi, including disclosure of TSC source code.



6.2.1        Replacing the TSC entirely would be more expensive and take longer but could, if necessary, be done without access to the source code of the existing system. It would of course mean abandoning a large amount of perfectly satisfactory code and replacing it with new code with no improvement in performance except in specific areas.


6.2.2        We would expect such a plan to involve replacing the code that currently runs in the TSC workstation and the MLPs but not the code in the LCUs (except perhaps in order to implement new guide star acquisition modes). This means that the interface between the MLPs and the LCUs would have to be disclosed—and documented—by Mitsubishi.


6.2.3        The cost of writing a new TSC is probably of the order of 12 staff years assuming that existing astrometric software such as the TCSpk kernel was used.


7          Concluding Remarks

7.1         OVERVIEW

7.1.1        Subaru’s computing infrastructure is in good shape. It uses mainstream components, standard in industry and astronomy, which can readily be maintained and which offer relatively inexpensive future upgrade paths.


7.1.2        The TSC competently realizes the superb optical and mechanical capabilities of the Subaru telescope, but lacks important high-level interfaces and has some serious speed problems.


7.1.3        The SOSS skeleton file system is powerful and flexible. Although the scripting language itself is rather old-fashioned in style, any replacement would look just as arcane.


7.1.4        The interactions between SOSS and TSC seem to involve significant latencies that could explain some of the slow performance. This and the way the TSC tracking demands are managed are a more likely explanation of the slowness than hardware limitations such as the speed of CPUs and LANs.


7.1.5        Friendlier interfaces between end-users and SOSS are required.


7.1.6        DASH is a good system with much in common with other such systems being developed elsewhere. However, its immediate importance lies in supporting pipelines at the telescope more than in offline data analysis.


7.1.7        The data archive facilities appear competent and the plans for future development sound.


7.1.8        Future observing modes will stretch the system unless it is enhanced in certain ways.


7.1.9        The present outsourcing of software maintenance is holding Subaru back (as well as being expensive).



7.2.1        After first looking at what other observatories have done, Subaru should develop an astronomer-friendly observation preparation tool to front-end SOSS. This should support classical observing, with the telescope user participating, but should be aiming towards a future where service observing is the norm.


7.2.2        The present extremely slow interaction between SOSS and the telescope must be properly diagnosed and then put right. It will not be enough to upgrade the computers and networks involved.


7.2.3        A smart interface to the telescope should be developed, providing full pointing integrity and fully automatic acquisition of faint objects onto instrument slits.


7.2.4        The most difficult task facing Subaru is the transition from entirely outsourced software maintenance to an in-house capability. At an early stage these long-term possibilities must be discussed with Mitsubishi and Fujitsu with the intention of securing their cooperation and optimizing their future roles. Some detailed points concerning management of in-house software activities are given in the next section.



7.3.1        Forming a Subaru in-house software team will require a wide spectrum of people from astronomers to software specialists. The team members must work together (i.e. not just hierarchically), with flexibility and discipline carefully balanced. Knowledge must be shared freely, and single points of failure guarded against.


7.3.2        Individual engineers should develop expertise in particular techniques (e.g. real-time control, user interfaces, data formats and world coordinate systems, documentation and version control) rather than be allocated to specific items of hardware (e.g. telescope, autoguiders, individual instruments), and there ideally should be considerable overlap so that no-one is indispensable.


7.3.3        To tackle major new developments, we counsel Subaru against the orthodox “big design up-front” by astronomers followed by a long implementation phase by software engineers; this is rarely successful in practice simply because the first design is never the right one. But the other extreme, namely ad hoc and uncontrolled development in response to the most recent operational pressures, is equally dangerous. In practice, the most successful projects involve all the team members in a thorough initial design, focusing on interfaces between subsystems, followed by rapid prototyping and then a long iteration phase with both the end user and the software engineer in the loop at all times. It is helpful throughout the development phase to have a programme of actual deliverables so that progress can be assessed. The existing Subaru preference for using industry-standard tools in commonsense ways should be preserved, given the long service life of the systems concerned.


7.3.4        Strict control over versions is vital, and documentation must be kept up to date. To maintain standards, all code and documentation must be checked for quality by someone other than the author.



7.4.1        The authors would like to thank Hiroshi Karoji for the opportunity to study the Subaru systems and for his hospitality and encouragement. We greatly appreciated Mark Weber’s meticulous preparations for our visit, which meant that the limited time available was used very efficiently. Finally we would like to thank all the speakers for their detailed  presentations and for their openness and insight, and the observers, instrument scientist and telescope operators for their patience in answering our many questions.



8          APPENDIX


Observatory Control Systems in General


In this appendix we itemise the functions required of a modern observatory’s software systems (but excluding finance and “office-automation” functions, and data analysis software used by observatory staff for personal astronomical research).

8.1         Observation Control System


8.1.1        An Observation Preparation Tool that provides

§         Access to catalogues of stars and other astronomical objects
§         An exposure calculator for estimating exposure times
§         A way of selecting suitable guide stars
§         A way of selecting instrument configurations (filters, gratings etc.)
§         An interface for defining patterns for telescope offsets
§         An interface for defining the instrument orientation
§         End-user-friendly


8.1.2        Observing Database that


§         Tracks status of observations

§         Support usage accounting

§         Records configuration of actual observations

§         Keeps observer informed of progress

§         Supports scheduling decisions

§         Generates observation descriptions to be executed on telescope


8.1.3        Observation Sequencer


§         Steps through the operations needed to carry out the observation.

§         Allows appropriate operator intervention during execution.

§         Enables last-minute modification of observation.

§         Updates observing database with status of observations

§         Updates observing database with actual configuration


8.2         Telescope Control System

8.2.1        Accepts celestial targets in a variety of forms:

§         ICRS coordinates

§         FK5 mean place

§         FK4 mean place

§         Apparent place (geocentric and topocentric, equinox and CEO)

§         Proper motion, parallax and radial velocity


8.2.2        Slews efficiently:

§         Points accurately

§         Exploits full performance of mount, rotator and enclosure

§         Settles promptly

§         Does not disturb optics


8.2.3        Tracks smoothly and with long-term accuracy limited only by the pointing model


8.2.4        Rotator stabilizes field orientation to place a specified instrument direction at a specified position angle with respect to a specified celestial coordinate system


8.2.5        Enclosure follows telescope


8.2.6        Rigorous astrometry including refraction and colour dependence


8.2.7        Total pointing integrity—all components are part of one pointing context


8.2.8        ADC and AO integrated


8.2.9        Fully corrected pointing transparently delivered


8.2.10    Tracks solar-system objects

§         differential rates

§         osculating elements


8.2.11    Active Optics

§         Oversees maintenance of optical alignment

§         Open loop models for M2 position and M1 figure

§         Closed loop control with wave-front sensors


8.2.12    Time

§         Leap seconds properly handled

§         Current UT1-UTC & polar motion taken account of


8.2.13    Zenith handling

§         Accurate maintenance of field orientation

§         Warns operator if current objects will track through “at risk” region

§         Mechanism demands do not become undefined in inaccessible region

§         Azimuth and rotator demands have “sensible” trajectory when transiting near zenith


8.2.14    Guiding

§         Automatic acquisition of catalogue guide stars

§         Automatic selection of guide stars

§         Guiding when guide star coordinates not accurately known

§         Solar-system objects as guide stars

§         Guiding while performing differential motions

§         Windshake rejection through M2 and autoguiding

§         Blind offset guiding using astrometric guide star


8.2.15    Management of focal plane

§         Pointing refers to nominated “hotspot”, not just the rotator axis

§         Quick selection of hotspot

§         Hotspot calibration procedures

§         When instrument is rotated, field rotates about hotspot

§         World coordinate system delivered to instruments linking pixels to RA,Dec


8.2.16    Operator interface

§         Ability to adjust pointing, target and hotspot as appropriate

§         Feedback on what the telescope is doing

§         Fault alerts

§         Display of times to wrap and other mechanism limits

§         Ephemeris information

o       Sunset/Sunrise

o       Moon set/rise

o       Moon proximity

§         Environment monitoring

o       Wind speed and direction

o       Humidity and dew-point


8.2.17    Pointing tests

§         Automated pointing tests

§         Sky sampled evenly

§         Logging of pointing-test data

o       log everything needed for re-analysis

o       data independent of model in use during test

§         "Mini-test" procedure for start-of-night refinement

§         Pointing analysis and modelling

§         Alternate pointing models for different telescope configurations


8.2.18    Management of cable wrap

§         Selection of wrap state when slewing

§         Calculation of times to limits.


8.2.19    Rotators at different foci


8.2.20    Chopping and nodding

§         Multiple ways to specify chop configuration

§         Instrument synchronised with M2


8.2.21    Bandwidth splitting between mount and M2


8.2.22    “Dawdle” mode, to dither without losing AO lock


8.2.23    Management of offsets from base


8.2.24    Scan and dither patterns

§         Give access to full bandwidth of telescope mechanics

§         Can be synchronised with instrument



8.3         Instrument Control System

8.3.1        Configures instrument


8.3.2        Takes data

§         Data can be recovered after error conditions

8.4         Quick-Look facilities

8.4.1        Displays data as soon as available from instrument.


8.4.2        Displays Context

§         RA/Dec

§         Wavelength

§         Background subtraction


8.4.3        Enables preliminary measurements

§         Flux

§         Line widths

§         Image quality

§         Astrometry

8.5         Data Handling System

8.5.1        Archives all data collected by instruments


8.5.2        Associates data with ancillary information from:

§         Telescope

§         Weather server

§         Facility adaptive optics


8.5.3        Associates science data with appropriate calibration data


8.5.4        Respects observatory data access policy


8.6         Logging and Fault Reporting

8.6.1        Collect performance data.

§         Measure “in service” performance.

§         Detect trends to pre-empt faults.


8.6.2        Time-stamped events

§         Analyse operational efficiency


8.6.3        Log fault conditions

§         Assist night time fault diagnosis by operators and support engineers

§         Assist fault diagnosis by day crew

§         Analyse statistics to identify weak components


8.7         Data Reduction Pipeline

8.7.1        Shares data analysis applications with those available offline


8.7.2        Assists immediate data quality assessment


8.7.3        Produces standard data products suitable for archive


8.7.4        Efficient generation of publication-quality data


8.7.5        Requires minimal operator intervention


8.7.6        Robust error detection and handling







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[2] Rigaut, F.J, Ellerbroek, B.L. and Flicker R., Principles, Limitations and Performance of Multi-Conjugate Adaptive Optics, Proc.SPIE 4007, 1022-1031 (2001).

[3] Wallace, P.T., A rigorous algorithm for telescope pointing, Proc.SPIE 4848, 125-136, 2002.

[4] Terrett, D.L., Tcl as a Software Environment for a TCS, Proc.SPIE 4848, 251-260, 2002.