Deep solar ALMA neural network estimator for image refinement and estimates of small-scale dynamics by Henrik Eklund. on Monday 28 November

The contrasts and magnitude of observable signatures of small-scale features

degrade as angular resolution decreases. High-cadence time-series of synthetic

observable maps at 1.25 mm were produced from 3D magnetohydrodynamic Bifrost

simulations of the solar atmosphere and degraded to the angular resolution

corresponding to observational data with the Atacama Large

Millimeter/sub-millimeter Array (ALMA). The Deep Solar ALMA Neural Network

Estimator (Deep-SANNE) is an artificial neural network trained to improve the

resolution and contrast of solar observations. This is done by recognizing

dynamic patterns in both the spatial and temporal domains of small-scale

features at an angular resolution corresponding to observational data and

correlated them to highly resolved nondegraded data from the

magnetohydrodynamic simulations. A second simulation, was used to validate the

performance. Deep-SANNE provides maps of the estimated degradation of the

brightness temperature, which can be used to filter for locations that most

probably show a high accuracy and as correction factors in order to construct

refined images that show higher contrast and more accurate brightness

temperatures than at the observational resolution. Deep-SANNE reveals more

small-scale features and estimates the excess temperature of brightening events

with an average accuracy of 94.0% relative to the highly resolved data,

compared to 43.7% at the observational resolution. By using the additional

information of the temporal domain, Deep-SANNE can restore high contrasts

better than a standard two-dimensional deconvolver technique. Deep-SANNE is

applied on observational solar ALMA data. The Deep-SANNE refined images are

useful for analysing small-scale and dynamic features. They can identify

locations in the data with high accuracy for an in-depth analysis and allow a

more meaningful interpretation of solar observations.

arXiv: http://arxiv.org/abs/http://arxiv.org/abs/2211.13629v1