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20182021
most citedExploring mutual information between IRIS spectral lines. II. Calculating the most probable response in all spectral windows

14 citations · 14 across the 1 of their papers we have counts for

collaborators

5 papers

astro-ph.SR202114 cited

Exploring mutual information between IRIS spectral lines. II. Calculating the most probable response in all spectral windows

Brandon Panos, Lucia Kleint

A three-dimensional picture of the solar atmosphere's thermodynamics can be obtained by jointly analyzing multiple spectral lines that span many formation heights. In paper I, we f…

astro-ph.SR2021

Exploring mutual information between IRIS spectral lines. I. Correlations between spectral lines during solar flares and within the quiet Sun

Brandon Panos, Lucia Kleint, Sviatoslav Voloshynovskiy

Spectral lines allow us to probe the thermodynamics of the solar atmosphere, but the shape of a single spectral line may be similar for different thermodynamic solutions. Multiline…

astro-ph.SR2021

A comparison of the active region upflow and core properties using simultaneous spectroscopic observations from IRIS and Hinode

Krzysztof Barczynski, Louise Harra, Lucia Kleint +2

The origin of the slow solar wind is still an open issue. It has been suggested that upflows at the edge of active regions (AR) can contribute to the slow solar wind. Here, we comp…

astro-ph.SR2019

Real-time flare prediction based on distinctions between flaring and non-flaring active region spectra

Brandon Panos, Lucia Kleint

With machine learning entering into the awareness of the heliophysics community, solar flare prediction has become a topic of increased interest. Although machine learning models h…

astro-ph.SR2018

Identifying typical Mg II flare spectra using machine learning

B. Panos, L. Kleint, C. Huwyler +4

IRIS performs solar observations over a large range of atmospheric heights, including the chromosphere where the majority of flare energy is dissipated. The strong Mg II h&k spectr…