Matthew Docherty
Reconstructing a model atmosphere from observations opens up an exciting new medium for solar chromospheric analysis. Despite numerous publications on other solar phenomena, a distinct lack of such analysis has been focused on solar filaments. As such, the thermodynamics and energy-transfer mechanisms of these complex plasma arcs are not currently well understood. Presented is an inaugural thermodynamic state diagnostic for a solar filament observation. This was achieved using a model atmosphere synthesised by inverting optically thick chromospheric Mg II profiles from Nasa's Interface Region Imaging Spectrograph (IRIS), using the IRIS2 non-LTE inversion code (presented in 2019). We present temperature and electron density progressions for varying optical depths and corresponding chromospheric altitudes within a quiet sun filament observation (IRIS OBS 360010604, DATE 2018-05-22). These progressions allow the altitude of the filament to be estimated; its thermodynamic state to be compared to the quiet sun background; as well as the ability of IRIS2 to handle filament data to be qualitatively analysed through comparisons to theoretical radiative-transfer predictions. This first-of-its-kind quiet sun filament diagnostic project is evolving rapidly and, with a new version-release of IRIS2 expected late-September 2020, this cutting-edge project and source-code is currently being developed with a focus on future versatility to be able to probe a broad range of filament observations (not necessarily quiet sun), furthering the understanding of these complex phenomena.
KEYWORDS: solar physics, chromosphere, IRIS, inversion code, model atmosphere, Mg II, filament, thermodynamics.
Figure1: Image of Solar filament with a mask border surrounding the dark features
Introduction: Introduces what a filament is, what an inversion code is and why using IRIS2 is useful
Project Aims: Use IRIS2 to diagnose filament observations whilst simultaneously analysing if IRIS2 is suitable for further filament work
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Method: Runs through overall data reduction of my Python code pipeline ending on data visualisation
Figure 2: 3 part subplot. Middle plot is a binary mask from Python code. Other 2 codes are the thermodynamic progressions for each pixel overlaid on top. Colour-coded for quiet sun and filament. The spread of the data can be visualised by the thickness of the trend.
Results: Start discussing this plot and how the Temperature in the filament is in general lower than quiet sun after a threshold altitude (which we expect from empirical results)
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Figure 3: Same as Figure 2 but now an average has been taken and the overall trend is much clearer and the spread is quantified with errorbars.
Figure 4: Model atmosphere images of temperature and electron density and we can see the filament as darker on the colourmap as it’s at a high enough altitude (above threshold)
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Conclusions: Somewhat successfully ticked off every Project aim from page 1
Further Work: Lots of good things have been achieved, but lots more to do before I can release it as a supplementary software to IRIS2 (including automate mask extraction and altitude conversion)
References: List the 4 refs I used in my main body of poster (IRIS2, STiC, Levens et al for filament Temp range and Wittman for old equation of state for altitude conversion)
Contact me: Listing ways to get in touch, both emails and twitter