Stokes Inversion based on Convolutional Neural Networks

Spectropolarimetric inversions are routinely used in the field of Solar Physics for the extraction of physical information from observations. The application to two-dimensional fields of view often requires the use of supercomputers with parallelized inversion codes. Even in this case, the computing time spent on the process is still very large. Our aim is to develop a new inversion code based on the application of convolutional neural networks that can quickly provide a three-dimensional cube of thermodynamical and magnetic properties from the interpretation of two-dimensional maps of Stokes profiles. We train two different architectures of fully convolutional neural networks. To this end, we use the synthetic Stokes profiles obtained from two snapshots of three-dimensional magneto-hydrodynamic numerical simulations of different structures of the solar atmosphere. We provide an extensive analysis of the new inversion technique, showing that it infers the thermodynamical and magnetic properties with a precision comparable to that of standard inversion techniques. However, it provides several key improvements: our method is around one million times faster, it returns a three-dimensional view of the physical properties of the region of interest in geometrical height, it provides quantities that cannot be obtained otherwise (pressure and Wilson depression) and the inferred properties are decontaminated from the blurring effect of instrumental point spread functions for free. The code is provided for free on a specific repository, with options for training and evaluation.Comment: 18 pages, 14 figures, accepted for publication in Astronomy & Astrophysic

Enhancing SDO/HMI images using deep learning

The Helioseismic and Magnetic Imager (HMI) provides continuum images and magnetograms with a cadence better than one per minute. It has been continuously observing the Sun 24 hours a day for the past 7 years. The obvious trade-off between full disk observations and spatial resolution makes HMI not enough to analyze the smallest-scale events in the solar atmosphere. Our aim is to develop a new method to enhance HMI data, simultaneously deconvolving and super-resolving images and magnetograms. The resulting images will mimic observations with a diffraction-limited telescope twice the diameter of HMI. Our method, which we call Enhance, is based on two deep fully convolutional neural networks that input patches of HMI observations and output deconvolved and super-resolved data. The neural networks are trained on synthetic data obtained from simulations of the emergence of solar active regions. We have obtained deconvolved and supper-resolved HMI images. To solve this ill-defined problem with infinite solutions we have used a neural network approach to add prior information from the simulations. We test Enhance against Hinode data that has been degraded to a 28 cm diameter telescope showing very good consistency. The code is open source.Comment: 13 pages, 10 figures. Accepted for publication in Astronomy & Astrophysic

Non-LTE inversions of a confined X2.2 flare: I. Vector magnetic field in the photosphere and chromosphere : I. The vector magnetic field in the photosphere and chromosphere

Obtaining the magnetic field vector accurately in the solar atmosphere is essential for studying changes in field topology during flares and to reliably model space weather. We tackle this problem by applying various inversion methods to a confined X2.2 flare in NOAA AR 12673 on September 6, 2017, comparing the photospheric and chromospheric magnetic field vector with those from two numerical models of this event. We obtain the photospheric field from Milne-Eddington (ME) and (non-)local thermal equilibrium (non-LTE) inversions of Hinode SOT/SP Fe I 6301.5Å and 6302.5Å. The chromospheric field is obtained from a spatially-regularised weak field approximation (WFA) and non-LTE inversions of Ca II 8542Å observed with CRISP at the Swedish 1-m Solar Telescope. The LTE- and non-LTE-inferred photospheric field components are strongly correlated throughout the atmosphere, with stronger field and higher temperatures in the non-LTE inversions. For the chromospheric field, the non-LTE inversions correlate well with the spatially-regularised WFA. We find strong-field patches of over 4.5 kG in the photosphere, co-located with similar concentrations exceeding 3 kG in the chromosphere. The obtained field strengths are up to 2-3 times higher than in the numerical models, with more concentrated and structured photosphere-to-chromosphere shear close to the polarity inversion line. The LTE and non-LTE Fe I inversions yield essentially the same photospheric field, while ME inversions fail to reproduce the field vector orientation where Fe I is in emission. Our inversions confirm the locations of flux rope footpoints that are predicted by numerical models. However, pre-processing and lower spatial resolution lead to weaker and smoother field in the models than what the data indicate. This emphasises the need for higher spatial resolution in the models to better constrain pre-eruptive flux ropes.Peer reviewe

Preoperative cytological and histological diagnosis of breast lesions: A critical review.

Item does not contain fulltextBACKGROUND: Non-operative pathology diagnoses constitute an essential part of the work-up of breast lesions. With fine needle aspiration (FNA) and core needle biopsy (CNB) both having unique advantages, there is an increasing acceptance of CNB. This paper aims to outline the scientific basis of this trend. Additionally, we provide an update on novel techniques that derive cytological specimens from CNB (i.e., touch imprint (TI) and core wash (CW) cytology) in an attempt to get the best of both worlds. METHODS: In addition to using the authors' experience, we performed a search of the Medline database combining the search terms "breast cancer diagnosis", "core needle biopsy", "fine needle aspiration", "touch imprint cytology", "core wash cytology" and "complications". We defined a conclusive non-operative diagnosis as "malignant" in lesions that were malignant on follow-up and "benign" in lesions that were benign on follow-up. RESULTS: CNB was more often conclusive than FNA in benign and malignant lesions in 4 prospective studies. Although the more rapid diagnoses by FNA result in less patient anxiety during diagnostic work-up, CNB allows for fairly reliable estimation of invasion, histological type, grade, and receptor expression. CW and TI cytology seem promising techniques with conclusiveness rates that are roughly comparable to that of FNA. CONCLUSIONS: All new suspicious breast lesions require careful non-operative investigation by CNB. However, additional cytological assessment by FNA can still be useful as a same-day diagnosis decreases patient anxiety and facilitates surgical treatment planning. TI and CW cytology techniques are promising same-day diagnosis modalities.1 oktober 20107 p