Training the Trap

Antonia Rowlinson

Transcript

1. Training the TraP Antonia Rowlinson University of Amsterdam
2. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Swinbank (2011)
3. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Swinbank (2011)
4. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Swinbank (2011)
5. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl High Bound Noise Threshold: Radio Sky Monitor dataset average RMS noise ~ 24 mJy (11 min snapshot images)
6. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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
7. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Transient search parameters After each new data point is inserted into the database we calculate: Variability Index: ! ! ! Weighted Chi-squared: ! ! ! !
8. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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
9. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 2.7 sigma threshold
10. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl
11. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Bright sources - statistical flux errors very small, systematic errors dominating
12. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Faint sources - likely imaging artefacts Bright sources - statistical flux errors very small, systematic errors dominating
13. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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
14. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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
15. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Simulated datasets
16. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl
17. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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) !
18. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl
19. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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
20. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Precision ~ 99% (probability that identified transients are real) Recall ~ 80% (probability that all transients are identified)
21. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl
22. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl 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)
23. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Min Separation from A-Team: Significant deviation starts from ~10 degrees
24. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Restoring Beam Ellipticity:
25. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl Current caveat: The sky is not well known at LOFAR frequencies Extrapolating fluxes to LOFAR bands using poorly constrained spectra
26. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl
27. Antonia Rowlinson University of Amsterdam b.a.rowlinson@uva.nl