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Program

Collin Capano edited this page May 9, 2019 · 53 revisions

NOTE: SCHEDULE AND TOPICS SUBJECT TO CHANGE

Tuesday 14 May

Day's goal: Understand how to do a parameter estimation analysis and how to interpret results.

Morning: Foundational concepts of gravitational-wave parameter estimation

9:00 - 9:10: Welcome [Collin Capano & Ian Harry]

9:10 - 9:50: Intro to parameter estimation in gravitational wave astronomy [Matthew Pitkin]

  • Basics of Bayesian Inference
  • Application to gravitational-wave astronomy

9:50 - 10:30: Gravitational waves from compact binary coalescence [Sebastian Khan]

  • Physics, parameters, and degeneracies

10:30 - 11:00: Break

11:00 - 11:45: Markov-chain Monte Carlo (MCMC) [Vivien Raymond]

  • Basic theory
  • Ensemble sampling
  • Parallel tempering
  • Thermodynamic integration
  • Implementations
  • Practical considerations: convergence tests, thinning

11:45 - 12:30: Nested sampling [John Veitch]

  • Basic theory
  • Implementations
  • Practical considerations: choosing number of live points, tolerance; ...

12:30 - 14:00: Lunch

Afternoon: How to use PyCBC Inference 1

14:00 - 15:00: Introduction to PyCBC [Alex Nitz] [Tutorial]

  • Tutorial covering basics of waveform generation, matched filtering
  • Data conditioning
  • PSD estimation
  • Practical considerations: wrap around, inverse spectrum truncation, etc.

15:00 - 15:15: Break

15:15 - 16:15: Introduction to PyCBC Inference [Collin Capano]

  • Code overview
  • How to set up a simple test run
  • How to set up a CBC analysis
  • Output file format
  • Plotting results

16:15 - 16:30: Break

16:30 - 17:15: Defining priors and parameters [Collin Capano]

  • Variable vs sampling vs waveform parameters
  • The distributions module
  • Using transforms

17:15 - 18:00: Using the workflows [Chris Biwer]

  • Standard workflow
  • Injection (percentile-percentile test) workflow

Wednesday 15 May

Day's goal: Understand how the code works and how to modify it for new projects.

Morning: How to use PyCBC Inference 2 / How the code works

9:00 - 9:45: MCMC implementations and settings [Collin Capano]

  • Emcee/EmceePT
  • Epsie

9:45 - 10:30: Nested sampling implementations and settings [Sumit Kumar]

  • CPNest
  • PyMultiNest

10:30 - 11:00: Break

11:00 - 11:45: A primer on python classes [Collin Capano] [Tutorial]

  • What is a class
  • Class inheritance
  • Abstract base classes

11:45 - 12:30: Code road map [Collin Capano] [Tutorial]

  • What's called where
  • Module structure

12:30 - 14:00: Lunch

Afternoon: How the code works

14:00 - 15:30: Available models and their use [Alex Nitz] [Tutorial]

  • Basic API
  • Available models
  • How to add a new model

15:30 - 16:00: Break

16:00 - 16:45: LIGO/Virgo Collaboration development: Bilby [Vivien Raymond]

16:45 - 17:15: Parallelization [Alex Nitz]

  • Multiprocessing
  • MPI

17:15 - 17:30: How to contribute using github [Ian Harry]

Thursday 16 May

Day's goal: Establish improvements to work on for future.

Morning: Future development

9:00 - 9:45: Evidence calculation with parallel tempering: pitfalls, tips, and improvements [Steven Reyes]

9:45 - 10:00: Break

10:00 - 10:45: Web-based tools for workflow visualization [Chris Biwer]

10:45 - 11:00: Break

11:00 - 12:00: PESummary [Charlie Hoy]

12:00 - 13:30: Lunch

Afternoon

The afternoon will mostly be unstructured project and discussion time, giving people a chance to ask questions about anything they found unclear from the first two days. Multiple parallel discussions may occur. Possible discusions points:

  • What can be improved?
  • How to implement on a cluster? Continue to use Condor? Slurm? Other options?

The ICG is committed to fostering an environment of dignity and respect. We ask that all speakers and participants read the ICG's code of conduct to help ensure that the workshop is friendly and welcoming to all participants.

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