Sparse inversion of Stokes profiles. I. Two-dimensional Milne-Eddington inversions

Inversion codes are numerical tools used for the inference of physical properties from the observations. Despite their success, the quality of current spectropolarimetric observations and those expected in the near future presents a challenge to current inversion codes. The pixel-by-pixel strategy of inverting spectropolarimetric data that we currently utilize needs to be surpassed and improved. The inverted physical parameters have to take into account the spatial correlation that is present in the data and that contains valuable physical information. We utilize the concept of sparsity or compressibility to develop an new generation of inversion codes for the Stokes parameters. The inversion code uses numerical optimization techniques based on the idea of proximal algorithms to impose sparsity. In so doing, we allow for the first time to exploit the presence of spatial correlation on the maps of physical parameters. Sparsity also regularizes the solution by reducing the number of unknowns. We compare the results of the new inversion code with pixel-by-pixel inversions, demonstrating the increase in robustness of the solution. We also show how the method can easily compensate for the effect of the telescope point spread function, producing solutions with an enhanced contrast.Comment: 13 pages, 8 figures, accepted for publication in A&

Connection between electrical conductivity and diffusion coefficient of a conductive porous material filled with electrolyte

The paper focuses on the cross-property connection between the effective electrical conductivity and the overall mass transfer coefficient of a two phase material. The two properties are expressed in terms of the tortuosity parameter which generalized to the case of a material with two conductive phases. Elimination of this parameter yields the cross-property connection. The theoretical derivation is verified by comparison with computer simulation

Real-time multiframe blind deconvolution of solar images

The quality of images of the Sun obtained from the ground are severely limited by the perturbing effect of the turbulent Earth's atmosphere. The post-facto correction of the images to compensate for the presence of the atmosphere require the combination of high-order adaptive optics techniques, fast measurements to freeze the turbulent atmosphere and very time consuming blind deconvolution algorithms. Under mild seeing conditions, blind deconvolution algorithms can produce images of astonishing quality. They can be very competitive with those obtained from space, with the huge advantage of the flexibility of the instrumentation thanks to the direct access to the telescope. In this contribution we leverage deep learning techniques to significantly accelerate the blind deconvolution process and produce corrected images at a peak rate of ~100 images per second. We present two different architectures that produce excellent image corrections with noise suppression while maintaining the photometric properties of the images. As a consequence, polarimetric signals can be obtained with standard polarimetric modulation without any significant artifact. With the expected improvements in computer hardware and algorithms, we anticipate that on-site real-time correction of solar images will be possible in the near future.Comment: 16 pages, 12 figures, accepted for publication in A&

Shape evolution and shape coexistence in Pt isotopes: comparing interacting boson model configuration mixing and Gogny mean-field energy surfaces

The evolution of the total energy surface and the nuclear shape in the isotopic chain $^{172-194}$Pt are studied in the framework of the interacting boson model, including configuration mixing. The results are compared with a self-consistent Hartree-Fock-Bogoliubov calculation using the Gogny-D1S interaction and a good agreement between both approaches shows up. The evolution of the deformation parameters points towards the presence of two different coexisting configurations in the region 176 $\leq$ A $\leq$ 186.Comment: Submitted to PR

Comparison of thermal performance of 3D printer liquefiers through finite element models

Open source 3D printers have experienced an intense expansion during the last years, mainly because of their accessibility and the vast availability of information thanks to user communities. This fact presents researchers with a perfect context for hardware innovation, by improving the overall printing process, also in terms of durability of the printing machine. A 3D printer liquefier must transmit heat to the thermoplastic material in order to extrude it, reaching temperatures above 200 degrees for some materials like ABS on the tip of the nozzle. The design of the heating process must comply with keeping the balance between proper heating of the material and controlling the temperature along the extruding body, so that the printer itself is not harmed for overtemperature. On the other hand, the design must guarantee that the melting front is located in an intermediate point between the nozzle tip and the entrance of the raw material, to minimize pressure drops in the system, and so decreasing the demanding energy to the feeding motors. An alternative design of the heating system, Twist3D, is proposed in this paper.Peer ReviewedPostprint (published version