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LISA Science Data Analysis Planning

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6.1 Compact binaries in our and nearby galaxies. 6.2 Diffuse galactic background ... Periodic sources in the galaxy: Develop and test detection and parameter ... – PowerPoint PPT presentation

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Title: LISA Science Data Analysis Planning


1
LISA Science Data Analysis Planning in the
U.S. Bonny Schumaker, JPL (NASA) bonny.schumake
r_at_jpl.nasa.gov 818-281-5146 10 Jul 2005 Bern,
Switzerland LISA LIST Meeting
2
  • U.S. Project Schedule provides framework for
    Formulation-phase planning.
  • Near-term planning aims for Mission Definition
    Review Feb 2007
  • MDR Objectives have clear implications for LISA
    Science Data Analysis
  • (see Moonis viewgraphs on MDR NASA Success
    Criteria)
  • Responsibilities (in the U.S.) during
    Formulation
  • Shared among NASA HQ, LIST, NASA Mission Science
    Office (MSO) , and other areas of the U.S.
    Project (Mission Systems Engineering MSE,
    Mission Ops MO).
  • Products (official Project documents) and
    Activities are stipulated with timelines,
    designated roles for lead responsibility, input,
    review, approval, concurrence.
  • Formulation Products (draft planning in
    progress)
  • Currently seven proposed documents provided to
    NASA HQ or NASA LISA Project Management (PM),
    from LIST or NASA MS with support from other
    Project Offices
  • Some have precedent from previous NASA missions,
    some are unique to LISA.
  • Formulation Activities (draft planning in
    progress)
  • Proposed near-term activities in support of
    these products. So far proposal is for work by
    Project MSO. TBD proposals from LIST and LISA
    science community

3
  • NASA Mission Definition Review (Feb 2007,
    draft products by Oct 2006)
  • Objectives (highlights added)
  • … to confirm that
  • (a) science objectives are fully understood and,
    if feasible, prioritized so as to define
    acceptable descope options,
  • (b) the conceptual system design is tailored to
    efficiently and effectively meet science
    objectives,
  • (c) system-level requirements are traceable to
    science objectives and are clearly and logically
    allocated amongst the independent system
    elements,
  • (d) the operations concept clearly supports
    achievement of science objectives,
  • (e) technology dependencies are fully defined
    with risks and viable mitigation plans
    identified, and
  • (f) successful execution of the project can be
    reasonably expected within imposed constraints
    and available cost and schedule resources.   "

4
  • Proposed Formulation Products from Mission
    Science Office
  • Seven official documents
  • 1--3 are standard (with NASA mission
    precedents),
  • 4--5 are new and involve the LIST, and
  • 6--7 are not near-term or not LIST-intensive.
  • 1. Science Requirements Document (SRD)
  • 2. Science Management Plan (SMP)
  • 3. Science Data Management Plan (SDMP)
  • 4. Science Data Flow Architecture Document
    (SDFAD)
  • 5. Science Data Analysis Methods (AMIGOS)
    Development Plan
  • 6. AMIGOS Implementation Plan
  • 7. Education Public Outreach Plan (EPOP)
  • AMIGOS Analysis Methods for Interferometric
    Gravitational-wave Observations in Space

5
  • Science Requirements Document (SRD)
  • Prepared by the LIST, NASA MSO, ESA PM/MSO.
  • Held by the Project (MSO), Approved by the LIST.
  • Used by the Project to establish the Mission
    Requirements Document (MRD) and impose
    performance requirements on design of the
    constellation and subsystems.
  • Used by HQ as input for the Level One
    Requirements (LOR). HQ provides draft LOR to the
    Project prior to MDR, final LOR prior to SRR/PDR.
    Project must accept final LOR to proceed from
    SRR/PDR. The SRD is revised to reflect the final
    LOR, then accepted by the Project and retained in
    the Project library for reference.
  • 20050801 Review/feedback from LIST
  • 20051001 Working group reports on progress (to
    MSO)
  • 20051115 Draft of proposed update to LIST (from
    MSO)
  • 20051210 LIST meeting
  • 20060115 Approved update submitted to Project
  • Lead responsibility LIST (Prince, Danzmann).
  • Inputs from LIST, NASA ESA MSOs.
  • Status v3.0 (200505) posted on
    http//pmis.esa.int http//www.srl.caltech.edu/l
    isa.

6
  • 2. Science Management Plan (SMP)
  • Prepared by the LIST, NASA MSO, ESA PM/MSO.
  • Modeled after those prepared for other
    successful science missions.
  • Approved by PM LIST, Concurred by MSE.
  • Revised approved by NASA ESA HQ, given to
    Project pre- PDR (end Phase B).
  • Critical dependence on LIST and European
    coordination. May require formal agreement
    between ESA NASA HQ approving this plan.
  • Non-technical agreements regarding organizational
    structure -- constitution and activities of the
    Science Team, locations and organization of the
    Data Centers, proprietary data, AOs for guest
    investigators, roles and responsibilities of the
    NASA ESA Mission Scientists and Project
    Scientists, etc.
  • Pre-MDR draft due Oct 2006.
  • 20050801 LIST, MSO, ESA to resolve issues and
    commit to completion schedule
  • 20051001 Report on writing process (from MSO to
    Project)
  • 20051115 Section drafts provided by MSO to LIST
    for review
  • 20060101 LIST feedback due to MSO, including
    schedule for next six months
  • Lead responsibility Prince (NASA MSO)
  • Status Outline exists from Jul 2003, posted on
    http//www.srl.caltech.edu/lisa .

7
  • Science Data Flow Architecture Document (SDFAD)
  • Prepared by MSO w/ input from LIST, MSE, MO,
    concurrence from MSE and MO. Uses info from other
    documents (SRD, SMP, SDMP).
  • Held (configuration-controlled) by MSE
  • Gives big picture of the science data flow,
    from onboard receipt of all science data
    (including science housekeeping) to output of
    scientific information. (Not HW design!)
    Describes major phases of science data
    processing, including functional performance of
    the different operations, their sequence, and
    relations among each other.
  • See slides below for examples of previous work
    relevant to both the SDFAD and the SDMP
    (Hellings, Prince, etc.)
  • Pre-MDR draft (Oct 2006)
  • 20050901 Scope outline circulated (Schumaker)
  • 20050908 Meet at GSFC to discuss, propose
    writing team
  • 20051115 First draft to Project (Schumaker)
  • 20051201 Comments on draft returned from writing
    team to B. Schumaker
  • 20060115 Second draft to Project and to
    designated LIST members

8
  • 4. Science Data Management Plan
  • Prepared by MS with input from MSE, MO, the LIST,
    and general LISA science community. Coordinated
    with analogous ESA plan. Held by the LISA
    Project
  • The science systems implementation plan
    Describes the people, facilities, processes, and
    data distribution flow for science data analysis,
    from ground receipt of the data stream (Level-0
    data, i.e., decoded and unpacked time-series)
    through to production of scientific information,
    including science data reduction, archiving,
    disseminating, and scientific analysis by guest
    investigators..
  • Describes the structures associated with
    implementation of the science data analysis
    methods developed under the AMIGOS Development
    Plan, e.g., the organization, responsibilities,
    and operation of US and European LISA Data
    Centers.
  • Pre-MDR Draft (Oct 2006)
  • 20050801 Circulate existing draft to writing
    team (Schumaker)
  • 20050901 Comments on existing draft returned
    from writing team to J. Kwok (MO)
  • 20051001 Circulate new draft to writing team
    (Kwok)
  • 20051101 First draft to Project (Kwok)
  • Lead responsibility MS MO Offices (Prince,
    Kwok).
  • Status Draft exists (W. Green, Jul 2003).

9
LISA Science Data Flow from Ron Hellings, Golm
2004 (starts with data received on ground)
10
Previous work relevant to SDFAD SDMP -1
LISA Science Data Flow from Tom Prince, 2004
LISA Symposium
Data Products
S/C Data Systems
Level 0 data 18 data
streamshousekeeping
Calibration/Instrument Signature Removal
Level 1 data 12 data streams
TDI Variable Construction
TDI data 3 data streams
Science Products
Source Detection Parameter Estimation
Source List
Source Subtraction Data Model Generation
Data Model
Diffuse Source Model
Diffuse Source Modeling
11
LISA Data Flow High-level (superficial)
Brainstorming June 2005, Stebbins et al.
In-flight processing
In-flight assessment
Operations Center (Ground)
Science data Correction
Ground Quality Assessment
Science Command
Calibration/Units
Sources
Distribution
12
  • Science Data Analysis Methods (AMIGOS)
    Development Plan
  • Prepared by the MSO w/ input from LIST and LISA
    science community coordinated with parallel
    plans by ESA..
  • Approved by the LIST. Held by the NASA LISA
    Project.
  • Describes work areas, priorities, levels of
    effort, and timelines for development of methods
    for analyzing LISA data to produce scientific
    information.
  • Pre-MDR draft, LIST-approved, by Oct 2006.
  • 20050801 Draft to Project, TBD US LIST TBD
    Europeans (Schumaker)
  • 20050915 Comments returned from Project and
    LIST
  • 20051001 Science community meeting in US to
    review and discuss
  • 20051101 New Draft to Project, TBD US LIST, TBD
    Europeans (Vallisneri)
  • 20061201 Comments returned to M. Vallisneri
  • Lead responsibility MSO
  • Status Draft submitted to PM April 2005
    (available on request new draft due
  • 01 Aug 2005)

13
AMIGOS Development Plan -2 (draft v0.1Rc 20050503)
  • 1. Introduction
  • 1.1 Data analysis for the LISA Mission
  • 1.2 Challenges unique to LISA data analysis
  • 1.3 Overview of technical objectives
  • 2. Background
  • 2.1 Comparison with ground-based
  • GW data analysis
  • 2.2 Efforts underway in the U.S. and Europe
  • 3. Risk assessment and management
  • 4. High-level gates
  • 5. Major milestones
  • Technical approach 1
  • Scientific and Technical Drivers
  • 6.1 Compact binaries in our and nearby galaxies
  • 6.2 Diffuse galactic background
  • 6.3 Supermassive intermediate-mass
  • black hole (SMBH IMBH) binaries
  • 6.4 Extreme-mass-ratio inspirals (EMRIs)
  • Technical approach 2
  • Analysis methods development areas
  • 7.1 Characterization of instrument science
  • operation and performance
  • 7.2 Computational infrastructure for
  • data analysis
  • 7.3 Data analysis algorithms
  • 7.4 Astrophysical models
  • 7.5 General Relativity
  • 8. Management Plan
  • 9. References 
  • Acronyms
  • Appendices
  • A. Other LISA Mission Science planning documents
  • B. Observational and Measurement
  • requirements for LISA science sources (from
    SRD-20050512-v3.0)

14
  • AMIGOS DP structure is analogous to that of US
    LISA Technology Development Plan. Includes Risk
    assessment and management, High-level gates,
    Major milestones, Technical Approach(es),
    Management Plan, etc.
  • It is undergoing changes currently to support a
    common technical organizational structure with
    ESA planning documents. (B.Schumaker, B. Schutz)
  • Technical portion uses dual approach for clarity
    and for strong link to SRD
  • Describes for each SRD science source category
    the key data-analysis challenges, requirements,
    high-level milestones, status, development areas
    risks, technical approach, development
    verification plans, roles responsibilities.
  • 2) Defines categories of analysis methods to be
    developed, e.g., characterization of instrument
    science performance, computational
    infrastructure, analysis algorithms,
    astrophysical models, and general relativity
    problems. Cuts across all sources.

15
Near-Term AMIGOS Development Activities -1 (from
AMIGOS Development Plan)
n.b. This is brainstorming material presented
for discussion purposes only!
1. Science Data analysis development
activities 1a. Characterization of instrument
science operation and performance 1a1. Develop
procedure(s) for combining multiple TDI
observables to isolate noise contributors 1a2.
Develop test methods to characterize as-flown
instrument noise as it impacts data-analysis,
based on sciencecraft subsystems operations
(levels, spectral shapes, nonstationarity,
non-Gaussian properties). 1a3. Catalog
instrumental noise transfer functions to detect
noise signatures unambiguously in the data. 1b.
Computational infrastructure for data
analysis (Needed for implementation and final
phases and to verify all data-analysis major
milestones.) 1b1. Data storage and delivery
Develop lightweight libraries for use in testing
in final infrastructures. 1b2. Data reduction
and conditioning Implement theoretical model of
low-level measurement in lightweight libraries
for reduction of data sets to level 1B. 1b3.
Source and noise simulators Develop and
validate simulators of LISA science process,
including low-level instrument behavior (gaps,
glitches), and extensive model of the mission
orbits and operations. 1b4. File formats and
data structures Develop extensible data formats
for storage of measured data and for
representation of candidate catalogs of
detections. (continued next slide)
16
Near-Term AMIGOS Development Activities -2 (from
AMIGOS Development Plan)
  • 1b. Computational infrastructure for data
    analysis (continued)
  • 1b5. Data-analysis application guidelines
    Develop recommendations for LISA application
    software, to enforce traceability and (when
    possible) formal verification.
  • 1b6. Computational resources Develop plan for
    in-house and outsourced capabilities (grid
    integration, etc.).
  • 1b7. Guidelines and protocols for extensive
    testing of data-analysis capabilities and
    milestones This will be accomplished through
    simulation and mock-data challenges. Will
    include evaluation criteria for success of
    contracted activities.
  • 1c. Algorithms and data analysis methods
  • 1c1. Verification binaries Develop and test
    detection and parameter-estimation algorithms for
    known foreground sources. (Algorithms well known
    from LIGO practice.)
  • 1c2. Verification binaries Develop and test
    detection and parameter-estimation algorithms for
    moderately large sets of overlapping but
    resolvable sources. (Algorithms not well
    understood Markov Chain Monte Carlo, Maximum
    Entropy, CLEAN-like algorithms, multitapers
    should be investigated.)
  • 1c3. Verification binaries Develop algorithm to
    infer polarization of gravitational waves from
    multiple TDI observables. (Not known whether 5
    or 6 links are needed,for direct inference.
    Also, TBD whether the "minimum mission" would
    accept polarization inferred over the course of
    one year.
  • 1c4. Periodic sources in the galaxy Develop and
    test detection and parameter-estimation algorithm
    for previously unknown sources in a strong
    background of similar signals.

17
Near-Term AMIGOS Development Activities -3 (from
AMIGOS Development Plan)
2. Theoretical research activities 2a.
Relativity 2a1. Mergers Develop accurate and
efficiently-computed templates for the inspiral
and ringdown phase of detection 2a2. Mergers
Develop framework to compare the results of
numerical-relativity merger simulations to
measured data, and to create parametrized
families of approximate merger waveforms 2a3.
EMRIs Develop accurate and efficiently computed
signal templates requires practical scheme to
integrate the radiation-reaction equations 2b.
Astronomy 2b1. Verification binaries Update
and expand catalog of candidate sources 2b2.
Verification binaries Assess, quantify and model
propagation effects of galactic halos on
GWs 2b3. Verification binaries, other periodic
sources, and mergers Assess prospects and plan
for simulations EM and GW observations 2c.
Astrophysics and cosmology (TBD)
(continued next slide)
18
Proposed High-priority Near-term MS Activities
(FY06)
(continued next slide)
19
Proposed High-priority Near-term MS Activities
(FY06) (continued)
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