The Physics of Solar Prominences: an AI/ML approach (Advert Reference: STFC22/EE/MPEE/REGNIERStephane)

Solar prominences are observed as large amount of cool material suspended high into the solar atmosphere. There is a large variety of structures and evolution from short-lived erupting prominences to long-standing prominences encircling the poles. Prominences are commonly observed on the limb of the Sun and have an important role in the injection of mass in the interplanetary medium through Coronal Mass Ejections (CMEs); their causal relation with solar flares is unclear. You will use the capabilities of the Solar Dynamics Observatory (SDO) Atmospheric Imaging Assembly (AIA) to observe and analyse the properties of prominences in time. SDO/AIA observations have now covered a full solar cycle (about 11 years) allowing us to provide both short-term and long-term evolutions of solar prominences. You will address the following scientific questions that have been puzzling solar physicist for decades but that the newly available instrumentation could help to answer:

- What is the magnetic structure of prominences? Since the 1980s, there is a debate in the community regarding the distinction between normal or inverse polarity magnetic configuration, which nowadays translates into the vertical or horizontal direction of the magnetic field.

- How do the location and structures of prominences vary during a solar cycle? What is the implication for the solar dynamo models?

- Is there a single mechanism characterising the prominence eruption? What is the origin of prominence eruption and their consequences?

The aim is to produce a comprehensive survey of solar prominences, assimilating their physical properties into an open-access database. The project is three-fold:

(i)                 benchmarking the detection algorithm based on an AI/ML method based on a sample of NASA SDO/AIA data (Solar Dynamics Observatory/Atmospheric Imaging Assembly), and thus building the physical properties of prominences into an open-access database relying on AI/ML methods

(ii)               performing a statistical analysis of prominences properties to determine the mechanism(s) of eruptions at short-time scale, and the variations during the solar cycle at long-time scales.

To tackle the scientific questions above, we derive a series of structural and time-varying parameters (e. g., vertical/horizontal size, height, intensity, latitude/longitude, area), which will constitute the basic query parameters of the prominences. The time evolution of those parameters will be derived to obtain flows, lifetime, directionality, acceleration in case of erupting prominences.

As a potential PhD candidate, you will have a background knowledge of solar/plasma physics, and a basic understanding of AI/ML. You will be responsible to develop the algorithm to detect prominences and extract their properties, as well as making the scientific statistical analysis of the processed data.  

The principal supervisor for this project is Dr. Stephane Regnier (E-mail: [Email Address Removed]).

Please note eligibility requirement:

·      Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.

·      Appropriate IELTS score, if required.

·      Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere of if they have previously been awarded a PhD.

 For further details of how to apply, entry requirements and the application form, see

https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/  

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. STFC22/EE/MPEE/REGNIERStephane) will not be considered.

Deadline for applications: 1 March 2022

Start Date: 1 October 2022

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