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Training the Trap

transientskp
January 09, 2014

Training the Trap

Antonia Rowlinson

transientskp

January 09, 2014
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  1. Training

    the

    TraP
    Antonia Rowlinson

    University of Amsterdam

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  2. Antonia Rowlinson University of Amsterdam [email protected]
    Swinbank (2011)

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  3. Antonia Rowlinson University of Amsterdam [email protected]
    Swinbank (2011)

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  4. Antonia Rowlinson University of Amsterdam [email protected]
    Swinbank (2011)

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  5. Antonia Rowlinson University of Amsterdam [email protected]
    High Bound Noise Threshold:
    Radio Sky Monitor dataset

    average RMS noise ~ 24 mJy

    (11 min snapshot images)

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  6. Antonia Rowlinson University of Amsterdam [email protected]
    Quality Control:
    Script to create Quality Control plots is available to TraP
    commissioners here (new version in development):

    !
    !
    This script needs running on each new dataset to
    determine the optimum thresholds for the flux ratio high
    bound, ellipticity and minimum A-Team separation
    https://github.com/transientskp/scripts/tree/master/TraP_QC_plots

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  7. Antonia Rowlinson University of Amsterdam [email protected]
    Transient search parameters
    After each new data point is inserted into the database we
    calculate:

    Variability Index:

    !
    !
    !
    Weighted Chi-squared:

    !
    !
    !
    !

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  8. Antonia Rowlinson University of Amsterdam [email protected]
    Transient Search Parameters:
    All newly detected sources are inserted into transient list

    However, the list is dominated by sources hovering at/near
    the source extraction detection threshold

    Will be resolved in Release 2 of the TraP

    Script providing temporary (approximate) fix available here:
    https://github.com/transientskp/scripts/tree/master/TraP_sort_transients

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  9. Antonia Rowlinson University of Amsterdam [email protected]
    2.7 sigma
    threshold

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  10. Antonia Rowlinson University of Amsterdam [email protected]

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  11. Antonia Rowlinson University of Amsterdam [email protected]
    Bright sources -
    statistical flux
    errors very small,
    systematic errors
    dominating

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  12. Antonia Rowlinson University of Amsterdam [email protected]
    Faint sources - likely
    imaging artefacts
    Bright sources -
    statistical flux
    errors very small,
    systematic errors
    dominating

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  13. Antonia Rowlinson University of Amsterdam [email protected]
    Dataset overview
    Script to create these plots is available to TraP commissioners
    here:

    !
    !
    Also, this script identifies transient candidates for a given
    sigma threshold:
    https://github.com/transientskp/scripts/tree/master/TraP_source_overview
    https://github.com/transientskp/scripts/tree/master/TraP_anomaly_detection

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  14. Antonia Rowlinson University of Amsterdam [email protected]
    Antonia Rowlinson University of Amsterdam [email protected]
    Simulated Datasets:
    Simulation technique enhanced and standardised

    Gives a set of known stable sources and known transients

    Further information available on LOFAR wiki:
    Take existing
    measurement set
    Delete contents
    of data columns
    Use BBS to insert sources
    using a sky model
    Insert Gaussian noise
    Calibrate and image using
    standard pipeline
    http://www.lofar.org/operations/doku.php?id=tkp:simulateddata

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  15. Antonia Rowlinson University of Amsterdam [email protected]
    Simulated datasets

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  16. Antonia Rowlinson University of Amsterdam [email protected]

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  17. Antonia Rowlinson University of Amsterdam [email protected]
    Transients which were undetected at quiescent flux but
    are stable after they turn on.

    !
    N.B. if maximum flux is comparable to detection
    threshold, they are undistinguishable from faint stable
    sources (this will be rectified in release 2 of TraP)

    !

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  18. Antonia Rowlinson University of Amsterdam [email protected]

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  19. Antonia Rowlinson University of Amsterdam [email protected]
    Can we do better?
    Logistic Regression
    (a linear classifier)

    4 features for each source:

    !
    !
    Trained using simulated transients
    and ‘stable’ sources from the Radio
    Sky Monitor dataset

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  20. Antonia Rowlinson University of Amsterdam [email protected]
    Precision ~ 99%
    (probability that
    identified
    transients are
    real)

    Recall ~ 80%
    (probability that
    all transients are
    identified)

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  21. Antonia Rowlinson University of Amsterdam [email protected]

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  22. Antonia Rowlinson University of Amsterdam [email protected]
    Conclusions:
    TraP works!

    However transient list dominated by fake “new” sources
    close to source detection threshold - to be resolved in TraP
    Release 2 (temporary fix available)

    Choose quality control parameters and transient thresholds
    very carefully to avoid spurious transients

    Tools to help available on GitHub (frequently improved)

    Transients can be identified in several ways such as:

    Identify anomalous transient parameters: ideally using a sigma
    threshold (~2.7 sigma for the Radio Sky Monitor dataset)

    Classify using multiple features and logistic regression (Preliminary)

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  23. Antonia Rowlinson University of Amsterdam [email protected]
    Min Separation from A-Team:
    Significant
    deviation starts
    from ~10 degrees

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  24. Antonia Rowlinson University of Amsterdam [email protected]
    Restoring Beam Ellipticity:

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  25. Antonia Rowlinson University of Amsterdam [email protected]
    Current caveat:

    The sky is not well known
    at LOFAR frequencies

    Extrapolating fluxes to
    LOFAR bands using poorly
    constrained spectra

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  26. Antonia Rowlinson University of Amsterdam [email protected]

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  27. Antonia Rowlinson University of Amsterdam [email protected]

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