Periodic Reporting for period 1 - STORM-CHASER (Chasing plasma storms on exoplanets)
Período documentado: 2022-06-01 hasta 2024-11-30
The calibration and imaging software developed by a PhD student working on the project already goes significantly beyond the state-of-the-art because it can make images at frequencies as low as 15 MHz which was not possible before. Data processing is very challenging at such low frequencies because the Earth's own atmospheric layer called the ionosphere severely distorts cosmic signals at these low frequencies but it is at these low frequencies that we expect to find signals from exoplanets.
The software to search for peculiar signals was developed by another PhD student working on the project. It looks for so-called type-II bursts that are generated when plasma is ejected from a star. These plasma ejection events can be devastating for exoplanets but they are rare and occur unpredictably. So we have developed software that can sift through thousands of hours of telescope observational data to locate these smoking-gun signatures.
In the coming months we will publish these software and papers on the methodology behind them. Then begins the work of applying the software to a large fraction of data in the telescope archive to make the discoveries.
In parallel with the postdoc on the project, we are developing techniques to look for signals that are produced from the interactions between the stellar plasma ejection and the planet. We have broadened our search from our original plan to use radio observations to now using both radio and optical observations. This interaction signature will appear as a periodic signal in the data modulated at the orbital period of the exoplanet. We have now also developed a methodology to detect the presence of this periodicity in a statistically robust way.
Further uptake by the broader radio astronomy community requires that the algorithm and code-base we have developed are integrated into standard workflows used by the community and the software made freely available. We are now doing so by integrating our modifications into the standard pipelines that are being widely used in the low-frequency radio astronomical community while also providing our codes freely via GitHub (see for e.g. https://github.com/cristina-low/lofar-low-pipelines(se abrirá en una nueva ventana))
Stellar plasma ejection detection efforts: Current state-of-the-art to detect stellar plasma ejection events used dedicated observations of one or a few stars covering just tens of hours. However these events are rare which needs thousands of hours of coverage. This means that manual searching for these bursts is no longer possible and we must develop new algorithms to automate the search. The project has done just that. We now have an initial implementation of such an algorithm that is showing promise. We have been able to use this algorithms to detect stellar bursts (not necessary related to coronal mass ejections). We are now deploying the algorithms on over 0.5 millions hours worth of data on nearby stars. Some aspects of the algorithms that reject artifacts in the data such as radio frequency interference and interference from unrelated nearby sources are more broadly applicable to any transient detection in radio interferometric data. This gives the algorithms a broader applicability. It is still early days to know what modifications may be necessary to ensure wider uptake (it depends on the nature of the artifacts we have top reject for our project and how general they are).