- Transient Universe : fast radio bursts (FRBs), pulsars, radio transients
Fast Radio Bursts (FRB) are one of the most fascinating transient phenomena discovered only 15 years ago. Recent localisations and redshift measurements of several FRBs confirmed their extra-galactic origin and extreme energies of the order of 1039 ergs, which are emitted over milli-second intervals. However, full understanding of FRB sources and underlying physical mechanisms powering these extreme events still awaits full explanation. Although FRBs were discovered and initially observed at frequencies around 1.4 GHz, in the last few years several FRBs have been detected down to very low frequencies (even 110-MHz). Multiple detections by Canadian CHIME telescope extending down to 400 MHz, LOFAR detections of repeating FRB 20180916B down to 110 MHz, and Green Bank Telescope discovery of FRB 20200125A at 350 MHz demonstrate that there exists a population of FRBs, which can be detected at frequencies below 350 MHz.
Stations of the low-frequency Square Kilometre Array (SKA-Low) telescope, which is currently being built at the Murchison Radio-astronomy Observatory in Western Australia, open a possibility of all-sky surveys for FRBs and SETI (stands for Searches for Extraterrestrial Intelligence), which both use similar data processing techniques. Predictions based on data from other higher frequency instruments show that just a single station of SKA-Low can detect even hundreds of FRBs per year in all-sky images. Hence, the main goal of this summer project is to perform a pilot FRB search using small amount (from one to few hours of data) of 100ms all-sky images from one of the existing SKA-Low prototype stations, the Engineering Development Array 2 (EDA2). Due to currently limited observing bandwidth of just about 1 MHz, it may not be possible to detect FRBs yet. However, it should be possible to detect pulses from other astrophysical sources, such as pulsars or magnetars. It should also be possible to derive a preliminary upper limit on the FRB rate at frequencies below 240 MHz, which will be further refined as the observing bandwidth of the station is increased.
Preferably astronomy/physics background
Experience with Unix or linux, python, bash scripting, C programing can be useful
Introduction to HPC
- Week 1 Inductions and project introduction
- Week 2 Background reading and Initial Presentation
- Week 3 Get familiar with the data (all-sky images and dynamic spectra from EDA2) and processing software. Execute the processing software on a small portion (few minutes) of data to form dynamic spectra and de-dispersed time series.
Verify that the results are correct and make physical sense before proceeding with the analysis of more data.
- Week 4 Process 1 hour of EDA2 all-sky images, to produce dynamic spectra and de-dispersed time series. Once results are verified and look as expected, proceed to processing a few hours worth of all-sky images. In order to gain basic understanding of the results, perform basic statistical analysis of the identified FRB candidates, for example: number of candidates per 10 min worth of data, distribution of their signal-to-noise (SNR) etc. The list of statistical checks will be decided as we go.
- Week 5 Process a few hours worth of EDA2 all-sky images. Perform statistical analysis on the full dataset to gain basic understanding of the number of candidates etc. Identify various classes of background events, and design filtering criteria (machine learning can be considered) to excise them, while leaving the most promising and significant (high SNR) candidates for events of astrophysical origin (FRBs, pulsars, magnetars etc). The most common classes of background events may be: radio-frequency interference (RFI), noise, satellites/planes, astrophysical etc.
- Week 6 Implement the designed filtering criteria to excise the most typical classes of background events and identify the most promising and significant (high SNR) candidates of astrophysical origin (FRBs, pulsars, magnetars etc).
- Week 7 Continue with filtering and verification of the identified candidates, and iteratively improve the classification criteria. In the end narrow down the list of astrophysical candidates to a short list of 10-20 candidates for a more detail inspection.
- Week 8 Critically evaluate the short list of candidates, and verify if any of them are due to known bright pulsars (like B0950+08), other radio sources, can still be matched to known satellites, other sources of RFI or are of unknown origin. Is there a genuine FRB candidate in the dataset ? If no, derive an upper limit on the FRB rate at the particular observing frequency.
- Week 9 Final Presentation
- Week 10 Final Report
Caption: Example 2-second image of the entire visibie hempisphere (left image) at 160 MHz obatained with the SKA-Low prototype station EDA2