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Merge pull request #592 from LSSTScienceCollaborations/issue/522/influence-subsection
"Influencing the LSST Observing Strategy" text, timeline
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whitepaper/figs/opsim_timeline.pdf

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whitepaper/introduction.tex

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\section{Synoptic Sky Surveying at Universal Cadence}
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\def\secname{intro:baseline}\label{sec:\secname}
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\credit{ivezic},
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\credit{drphilmarshall},
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\credit{michaelstrauss}
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The LSST defined a so-called ``baseline cadence'', described in the
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\href{http://adsabs.harvard.edu/abs/2008arXiv0805.2366I}{LSST overview
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paper} and Chapter 3 of the Science Book. This was used
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\section{Evaluating and Optimizing the LSST Observing Strategy}
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\def\secname{intro:evaluation}\label{sec:\secname}
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The next step is to quantify how well any given realization of the
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LSST observing strategy (i.e., an output of \OpSim) supports the (many)
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\credit{drphilmarshall}
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Given a realization of the LSST observing strategy (i.e., an output of
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\OpSim), our first task is to quantify how well it supports the (many)
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science projects that LSST will enable. As the algorithms controlling
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\OpSim are varied, some projects will benefit, while others may
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suffer. By quantifying this for each projects, we can determine which cadence
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\OpSim are varied, some projects will benefit, while others may suffer.
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By quantifying this for each projects, we can determine which cadence
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maximizes the science potential overall of the project.
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Therefore, we need
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a {\it science-based evaluation of the baseline
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LSST observing strategy and its variants}. After simulating a sample
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Therefore, we need a {\it science-based evaluation of the baseline LSST
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observing strategy and its variants}. After simulating a sample
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observing schedule consistent with this strategy (see
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\autoref{chp:cadexp}), we then need to quantify its value to each
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science team. This is what the LSST Simulations team's ``Metric Analysis
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Framework'' was designed to enable: science case investigators can
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now design quantitative evaluations of the outputs of \OpSim, to answer
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the question, ``how good would that observing strategy be, for my
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science team. This is what the LSST Simulations team's ``Metric
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Analysis Framework'' was designed to enable: science case investigators
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can now design quantitative evaluations of the outputs of \OpSim, to
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answer the question, ``how good would that observing strategy be, for my
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science?'' These ``metrics'' can be coded against the \MAF API, and
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shared among the LSST science community at the
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\href{https://sims-maf.lsst.io/metricList.html#contributed-mafcontrib-metrics}{\simsMafContrib}
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online repository. All of the \MAF metrics described in this paper can be
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found there.
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online repository. All of the \MAF metrics described in this paper can
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be found there.
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Once the fiducial strategy has
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been evaluated in this way, then any other strategy can be evaluated
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in the same terms, using the same code. We will then be able to %start
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optimize the strategy through iterations between \OpSim and \MAF.
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in the same terms, using the same code. We will then be able to iterate towards an
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science-optimized strategy.
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With this program in mind, it makes sense to define {\it one ``Figure
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of Merit'' (FoM) per science project}, that captures the value of the
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the findings presented in this paper be taken forward?
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In this section we describe the mechanisms by which community input to
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the developing observing schedule will be absorbed, and then explain how
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the developing observing schedule will be absorbed, and explain how
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we will distil the vital information that the project needs from our
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\OpSim / \MAF analyses.
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\OpSim / \MAF analyses. We then provide a target timeline for the provision of community input.
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\subsection{How will the results of our analyses be used?}
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\label{sec:\secname:useage}
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% Beth to write this, with Andy Connolly and guidance from
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% Michael Strauss and the SAC.
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\credit{bethwillman}, \credit{connolly}, \credit{ivezic}
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Through the end of construction and commissioning, this community
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Observing Strategy White Paper will remain a living document that is
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{\it the vehicle for the community to communicate to the LSST Project
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regarding the Wide-Fast-Deep and mini-survey observing strategies.}
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{\it The Project Scientist will synthesize and act on the results
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presented in this paper,} with support from the Science Advisory
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Committee and Survey Strategy Committee (see below).
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As described in the LSST Operations Plan (LPM-181), the observing
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strategy will continue to be refined and optimized during operations:
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the Survey Scientist will chair a survey evaluation working group that
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will evaluate quarterly the current and expected performance of the
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survey and scheduler software. This group may include representation
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from the Survey Support Scientist, the Pipelines and Data Products
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group, the Data Processing group, the Camera team, and science
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community. The science community representation may be implemented as a
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sub-group of the Science Advisory Committee.
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\subsection{Science Case Conclusions}
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\subsection{Communicating via Science Case Conclusions}
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\label{sec:\secname:caseConclusions}
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\credit{ivezic}
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In order to consolidate the various constraints on the observing
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strategy by different science cases, and provide high signal to noise
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data for the project to take forward, each science case will answer ten
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\navigationbar
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\subsection{Timeline}
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\label{sec:\secname:timeline}
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\credit{connolly},
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\credit{drphilmarshall}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\begin{figure}[ht!]
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\includegraphics[angle=0,width=0.9\linewidth,clip]{figs/opsim_timeline.pdf}
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\caption{Target timeline for the iterated optimization of the LSST observing strategy through 2020.}
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\label{fig:timeline}
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\end{figure}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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The intersection between the community and the scheduler development,
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and the expected support that can be provided by the Project, is
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outlined in \autoref{fig:timeline}. From the point of view of the community, this timeline contains a number of interesting features:
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\begin{description}
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\item{\textbf{Update of the Baseline Cadence and Exploration of Rolling
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Cadences.}} During development of version 1.0 of this white paper, the
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Project has been developing an enhanced operations simulator code,
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\OpSim~4. This will be used to generate, by September 2017, a new set of
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observing strategies, including some that have a ``rolling cadence''
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component. This is in response to the results presented in the science
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chapters of this paper. Analysis of these simulations would form the
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backbone of an updated, version 2.0 of this white paper, with existing
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science cases being updated to include quantitative assessment of the
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new \OpSim~4 simulations, and new science cases being identified and
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investigated.
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\item{\textbf{The definition of the Deep Drilling Fields (DDFs) and
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associated cadences.}} The September 2017 simulations will all continue
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to use the baseline DDF cadence. However, by September 2017, the LSST
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will issue a call for proposals to define the cadence and properties of
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the currently selected DDFs, and to propose a new set of DDFs. To enable
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this, the project will publish the known boundary conditions for
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additional DDFs (e.g.\ the definition of a DDF, the current division of
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survey time, constraints on the number of filter exchanges that can be
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accomplished within a night, the expected range of integration times).
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This call will include a request to describe the science objectives of
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new DDFs, the position on the sky of these DDFs, the depth required as a
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function of filter, the required cadence of observations, and the
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metrics that will demonstrate that the DDF observations meet their
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science requirements (these metrics do not need to be written within the
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framework of \MAF). Delivery of these white papers by the community will
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expected by the end of 2017. The LSST Observing Strategy GitHub
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repository can support the development and aggregation of these DDF
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white papers. The SAC will be asked to make a recommendation to the
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project by the end of April 2018 on which DDFs and cadences should be
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considered, and the project will respond to these recommendations by
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September 2018. The Project's ``SOCS and Scheduler'' team will support
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this effort by evaluating the proposed cadences and DDFs. This may be in
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the form of simulations (for new cadence proposals) or through an
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evaluation of the visibility and properties of the fields relative to
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the nominal performance of the LSST system.
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\item \textbf{The definition of Figures of Merit (FOMs) for the LSST
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survey strategy}. By September 2018 the project will issue a request to
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to the community to update this Observing Strategy white paper with
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\MAF-coded Figures of Merit, to evaluate both the Wide-Fast-Deep and the
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mini-surveys (Galactic plane, Northern Ecliptic Spur, South Celestial
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Cap) for their impacts on specific science cases. These FOMs will be
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required for the Project to evaluate the efficacy of different survey
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strategies on a range of LSST science (e.g.\ the trade-off between a
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rolling cadence for supernova classification vs transient detection or
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long period variability will need to be explored quantitatively). The
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requested delivery date for these \MAF FOMs into the Observing Strategy
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White Paper will be April 2019. This will leave time for a Survey
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Strategy Committee (see below) to undertake trade studies that
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incorporate the community-provided FOMs. Details of the design of the
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FOMs (including units, thresholds, speed) will be described at a later
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date (prior to September 2018). If Project resources can be allocated to
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the process, then the SOCS and Scheduler team will support the writing
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of the FOMs with advice and tutorials on the use of \OpSim~4~v1.4, but
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the Observing Strategy white paper community will be expected to deliver
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their metrics as \MAF code.
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\item \textbf{Establishment of a Survey Strategy Committee (SSC)}. Given
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the delivery of the FOMs, the project will establish a committee by July
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2019 to evaluate competing survey strategy proposals and to propose a
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survey strategy for commissioning and operation of the full LSST camera.
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This committee will be chaired by the LSST Project Scientist and be
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comprised of project and non-project personnel. The SAC will be asked to
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make recommendations for committee membership. The SSC will report to
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the LSST Director until the end of LSST construction and commissioning.
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In December 2019, based on the recommendation made by the SSC, the
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project will announce an initial survey strategy and publish a baseline
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simulation that reproduces that strategy. If Project resources can be
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allocated to the process, then the SOCS and Scheduler team might support
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the committee by helping to generate the proposed survey strategies.
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\end{description}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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\begin{figure}[t!]
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\includegraphics[angle=0,width=0.9\linewidth,clip]{figs/opsim_timeline.pdf}
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\caption{Target timeline for the iterated optimization of the LSST observing strategy through 2020.}
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\label{fig:timeline}
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\end{figure}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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It's important to note that the dates for this timeline are {\it
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targets}. Since the deliverables are dependent on the availability of
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project resources, these milestones should be considered as those we
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could achieve given our best effort. Likewise, given the limited
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availability of resources in the SOCS and Scheduler engineering team,
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support of community members who wish to use \OpSim v4 will be on a best
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effort basis. \OpSim v4 will be delivered as a Docker container and its
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use and operation will be documented, but there will be no guarantee of
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support for, or timeliness in response to requests for support from,
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community users. The solution to this problem is to work together: the LSST Observing Strategy community, represented here by this white paper, is already developing the skills to perform and analyze LSST operations simulations: by learning from each other, we can produce high quality quantitative conclusions for the Project to act upon.
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\navigationbar
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% --------------------------------------------------------------------
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\section{Guidelines for Contributors}

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