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Project area/S

  • Accretion physics and slow transients

Project Details

Detailed studies of variable radio emission from stars can illuminate the processes driving stellar magnetic activity. These processes can have important implications for properties of the stellar wind, magnetic dynamos and the space weather environment around these active stars.

Early low-frequency radio observations using single-dish tele-scopes detected bright bursts that occurred reasonably frequently from active stars. These initial observations implied that observing such bursts is relatively easy with many detections expected for modern low-frequency radio interferometers, like the Murchison Widefield Array (MWA). However, long observational campaigns using modern telescopes have not reproduced these early detections.

To better constrain stellar burst rates at MHz-frequencies, several magnetically active stars were observed with the MWA. This project will involve using radio astronomy tools to identify burst emission in this archive of MWA images. The student will characterise any detected emissions (frequency structure, polarisation, etc.) to determine how the star produced the observed emission. Additionally, the student will calculate burst rates for MHz-emission to compare to rates at higher frequencies. These calculations are essential for estimating how many stellar bursts will be detectable with the future Square Kilometre Array.

Student Attributes

Academic Background

Basic physics background, some astronomy but not necessary (can learn during project).

Computing Skills
Programming skills any language but would be good to include some basic Unix commands (create new folders, change directories, copy files, etc.). Python would be preferable but not necessary (can be learned during project).

Training Requirement
LaTex, python if necessary, radio astronomy software (casapy)

Project Timeline

  • Week 1 Inductions and project introduction
  • Week 2 Initial Presentation
  • Week 3 Training in python and/or casapy
  • Week 4 Training in python and/or casapy
  • Week 5 Write burst detection code
  • Week 6 Test and run detection code
  • Week 7 Analysis of detected bursts
  • Week 8 Analysis of detected bursts
  • Week 9 Final Presentation
  • Week 10 Final Report

Co-Supervisors

Dr Jack Line

Research Associate

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