data simulations community challenges stephan birkmann jeff valenti n.
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Data simulations / Community challenges Stephan Birkmann / Jeff Valenti. Simulator uses. Create simulator. Performance Description. Release simulated data. Organize data challenge. Release simulator. Agree on simulation g uidelines. Science inputs

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Data simulations / Community challenges Stephan Birkmann / Jeff Valenti


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Presentation Transcript
simulator uses
Simulator uses

Create

simulator

Performance

Description

Release

simulated

data

Organize

data

challenge

Release

simulator

agree on simulation g uidelines
Agree on simulation guidelines
  • Science inputs
    • e.g., simulated spectrum, parameter space
  • Operational assumptions (the “rules”)
    • e.g., reset, read, read
  • Instrumental effects to consider
    • e.g., photon noise, read noise, intra-pixel, …
  • Presentation of results
    • e.g., PPM vs. wavelength
performance d escription examples
Performance description examples

PPM vs. wavelength

6-hr clock time  1 hr

R=700 bin  R=100

how to agree on simulation guidelines
How to agree on simulation guidelines?
  • (Very) small working group?
    • 1-2 participants per IDT
    • when?
types of data challenges
Types of data challenges
  • Types of simulated data
    • Raw images
      • Instrument artifacts
    • Reduced spectroscopy/photometry
      • Model constraints
  • Types of analyses
    • Recover inputs with knowledge of input
    • Recover inputs from blind analysis
benefits of data challenges
(Benefits of data challenges)
  • (Build community support)
    • We are beyond this point
  • (List key factors that affect experiment)
    • Data quality issues
    • Model parameters
    • Product of simulation step
  • (Build familiarity with ground system)
    • Standard data products
    • Observing templates
    • Product of simulation step
benefits of data challenges1
Benefits of data challenges
  • Formulate observing strategy based on...
    • Ability to remove known instrumental effects
      • e.g., persistence, ghosts, jitter
      • Only useful until real data are released
    • Ability to recover input model parameters
      • e.g., composition, thermal structure
      • Useful throughout mission lifetime
  • Inform TAC
    • Allocate observing time wisely
  • Facilitate pipeline algorithm development
participation in data challenges
Participation in data challenges
  • Advantages
    • Craft better proposals
    • Become a recognized expert
    • Advertise instrument capabilities
    • (Obtain funding)
  • Disadvantages
    • May help competing proposals
    • Requires significant effort
which must be done would you participate
Which must be done? Would you participate?

Create

simulator

Performance

Description

Release

simulated

data

Data

challenge

Release

simulator