POSSUM: analysis for early science and beyond
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1 POSSUM: analysis for early science and beyond Cormac Purcell, Bryan Gaensler and the POSSUM team ASKAP 2016 askap.org/possum
2 Rotation 1 Rotation 2 Figure: O'Sullivan et al POSSUM-12 versus POSSUM-36 AGN
3 Figure: O'Sullivan et al POSSUM-12 versus POSSUM-36 ASKAP-36 ASKAP-36 Figure: O'Sullivan et al MHz 1130 MHz
4 Figure: O'Sullivan et al H II region around ζ Oph (Harvey-Smith, Madsen & BMG 2011) POSSUM-12 versus POSSUM-36 ASKAP-36 ASKAP-36 Figure: O'Sullivan et al MHz 1130 MHz POSSUM-36: Detect simple Faraday rotating screens Taylor,Stil&Sunstrum 2009 RM Grid
5 Figure: O'Sullivan et al H II region around ζ Oph (Harvey-Smith, Madsen & BMG 2011) POSSUM-12 versus POSSUM-36 ASKAP-36 ASKAP-12 ASKAP-36 ASKAP-12 Figure: O'Sullivan et al MHz 700 MHz 1430 MHz 1130 MHz POSSUM-36: Detect simple Faraday rotating screens Taylor,Stil&Sunstrum 2009 RM Grid
6 Figure: O'Sullivan et al Fletcher et al 2004 POSSUM-12 versus POSSUM-36 ASKAP-36 ASKAP-12 ASKAP-36 ASKAP-12 Figure: O'Sullivan et al MHz 700 MHz 1430 MHz 1130 MHz POSSUM-36: Detect simple Faraday rotating screens POSSUM-12: Detect complex polarisation mechanisms
7 POSSUM Polarisation Catalogues Validation Report POSSUM team defines 3 different catalogues:
8 POSSUM Polarisation Catalogues Validation Report POSSUM team defines 3 different catalogues: POSSUM Polarisation Catalogue (PPC) ASKAP-36 RM-Synthesis & simple modelling
9 POSSUM Polarisation Catalogues Validation Report POSSUM team defines 3 different catalogues: POSSUM Polarisation Catalogue (PPC) POSSUM Broad-Band Catalogue (PBCat) ASKAP-36 ASKAP-12 RM-Synthesis & simple modelling Complex Modelling
10 POSSUM Polarisation Catalogues Validation Report POSSUM team defines 3 different catalogues: POSSUM Polarisation Catalogue (PPC) POSSUM Broad-Band Catalogue (PBCat) POSSUM Value Added Catalogue (PBCat) ASKAP-36 ASKAP-12 ASKAP-12 & 36 RM-Synthesis & simple modelling Complex Modelling Complex Modelling (x, y z, φ) including other sources of information, e.g., synchrotron intensity.
11 ASKAP & POSSUM uv-data Implement for ASKAP Calibration & Imaging Image Data Source finding, & measurement CSIRO Stokes I Catalogue Secondary processing Polarisation Catalogue Advanced data products POSSUM
12 ASKAP & POSSUM uv-data Calibration & Imaging Image Data Source finding, & measurement Stokes I Catalogue Secondary processing Polarisation Catalogue Advanced data products Implement for ASKAP CSIRO POSSUM Design Phase CSIRO / Other POSSUM
13 ASKAP & POSSUM uv-data Calibration & Imaging Image Data Source finding, & measurement Stokes I Catalogue Secondary processing Polarisation Catalogue Advanced data products Implement for ASKAP CSIRO POSSUM Design Phase CSIRO / Other POSSUM
14 ASKAP & POSSUM Implement for ASKAP Design Phase Prototype Pipeline Goals: Develop Algorithms uv-data Calibration & Imaging Image Data Source finding, & measurement CSIRO CSIRO / Other RM-determination. Physical model fitting Degeneracy / model choice End-to-end Integration Catch 'edge cases' data Useful catalogue flags Analysis workflow Stokes I Catalogue Develop Quality Control Secondary processing Pre-release quality report Data quality metrics Granular data selection Polarisation Catalogue Advanced data products POSSUM POSSUM Explore Existing Surveys ATCA test fields, GALFACTS Documentation by code
15 Implementing the Prototype Dedicated USyd
16 Implementing the Prototype Dedicated USyd half of an astronomer
17 Implementing the Prototype Dedicated USyd half of an astronomer
18 Implementing the Prototype Dedicated USyd half of an astronomer Portable, modular, easy to install, easy to run, easy to modify and applicable to current real-world data.
19 Implementing the Prototype Dedicated USyd half of an astronomer Portable, modular, easy to install, easy to run, easy to modify and applicable to current real-world data. Processing Tasks: Python / Numpy Modules Visualisation: Mathplotlib & Tk GUI (Meta)data Storage Images & Spectra: FITS files (1 per source) Catalogue tables: SQLite3 Database File
20 Implementing the Prototype Dedicated USyd half of an astronomer Portable, modular, easy to install, easy to run, easy to modify and applicable to current real-world data. Processing Tasks: Python / Numpy Modules Visualisation: Mathplotlib & Tk GUI (Meta)data Storage Images & Spectra: FITS files (1 per source) Catalogue tables: SQLite3 Database File numpy tkinter sqlite3 mpfit & emcee astropy.io.fits astropy.io.wcs calculations visualisation... local database for model fitting FITS file I/O WCS processing Standard Python Library Standard Astronomy Library Distributed with Pipeline
21 Workflow Pipeline Tasks: 0_gen_model_images.py Input Sensitivity curve
22 Workflow Pipeline Tasks: 0_gen_model_images.py Input Sensitivity curve Input model
23 Workflow Pipeline Tasks: 0_gen_model_images.py Session Directory 1_verify_image_data.py 2_create_image_session.py Source finder catalogue or FITS mask Pipeline supports 'sessions' to facilitate different processing pathways on large datasets Source finding an external step: input can be catalogue or a FITS mask. Flexible catalogue ingestion via SQL CREATE Link
24 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py Robust spectral extraction, noise estimation & postage-stamp 'cublet' creation U Q 1D & 3D versions
25 Workflow Pipeline Tasks: 0_gen_model_images.py Fourier Transform 1_verify_image_data.py 2_create_image_session.py U Q 3_extract_spectra.py 4_do_RM-synthesis.py Operate on Fourier transformed data Wavelength to Faraday Depth
26 Workflow Pipeline Tasks: 0_gen_model_images.py Deconvolve FDF 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py
27 Workflow Pipeline Tasks: 0_gen_model_images.py Faraday Thin FDF 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py Detect peak, subtract thin model & measure residual Residual 6_assess_complexity.py
28 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py KS-test 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py Sigma Sigma Residual 6_assess_complexity.py Skewness KS-test Anderson-Darling test
29 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py Clean components 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py Residual 6_assess_complexity.py 2 nd moment of Clean component spectrum
30 Workflow Pipeline Tasks: 0_gen_model_images.py Faraday Thick FDF 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py Residual Residual 6_assess_complexity.py
31 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py Residual Residual 6_assess_complexity.py
32 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py Clean components 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py Residual Residual 6_assess_complexity.py
33 Workflow Pipeline Tasks: 0_gen_model_images.py Sun et al _verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py χ2 5_do_RM-clean.py 6_assess_complexity.py 7_do_QUfit_MCMC.py Scheme QU-fitting
34 Workflow One rotating screen + foreground depolarisation: Two rotating screens Depolarisation Rotation within the beam: N screens with RM-gradients: Rotation 1 Rotation 2
35 Workflow Current work focused on testing robust code to fit models to fractional polarisation data. Foreman-Mackey et al Convergence can be a problem: Robust MCMC fitting code (Purcell et al. in prep) Exploration Burn-in Convergence
36 Workflow N RM-gradient screens Scary: 2-3 component models can fit almost any observed spectrum!
37 Workflow N RM-gradient screens Scary: 2-3 component models can fit almost any observed spectrum! Very high S/N needed across broad band to dissentangle
38 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py 6_assess_complexity.py 7_do_QUfit_MCMC.py rmpipeviewer.py
39 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py 5_do_RM-clean.py 6_assess_complexity.py 7_do_QUfit_MCMC.py rmpipeviewer.py
40 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py Source summary table 4_do_RM-synthesis.py 5_do_RM-clean.py Common plotting actions 6_assess_complexity.py 7_do_QUfit_MCMC.py rmpipeviewer.py
41 Workflow Pipeline Tasks: 0_gen_model_images.py 1_verify_image_data.py 2_create_image_session.py 3_extract_spectra.py 4_do_RM-synthesis.py SQL Query Interface 5_do_RM-clean.py 6_assess_complexity.py 7_do_QUfit_MCMC.py rmpipeviewer.py
42 Summary Goal: Build a prototype pipeline for the POSSUM project Easy to deploy and use Well commented & documented for CSIRO Framework for testing and integrating algorithms Robust enough to use on existing datasets.
43 Summary Goal: Build a prototype pipeline for the POSSUM project Easy to deploy and use Well commented & documented for CSIRO Framework for testing and integrating algorithms Robust enough to use on existing datasets.
44 Summary Goal: Build a prototype pipeline for the POSSUM project Easy to deploy and use Well commented & documented for CSIRO Framework for testing and integrating algorithms Robust enough to use on existing datasets.
45 Summary Goal: Build a prototype pipeline for the POSSUM project Easy to deploy and use Well commented & documented for CSIRO Framework for testing and integrating algorithms Robust enough to use on existing datasets.
46 Summary Goal: Build a prototype pipeline for the POSSUM project Easy to deploy and use Well commented & documented for CSIRO Framework for testing and integrating algorithms Robust enough to use on existing datasets.
47 Summary Goal: Build a prototype pipeline for the POSSUM project Easy to deploy and use Well commented & documented for CSIRO Framework for testing and integrating algorithms Robust enough to use on existing datasets. Code release in two tranches: 1D & 3D RM-synthesis, RM-clean & QU-fitting modules + demonstration code Will be released on GitHub soon (announcement to POSSUM list): POSSUM pipeline code to make specific PPC and PBCat catalogues Contact cormac.purcell@sydney.edu.au
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