Gaussian Random Measures Generated by Berry’s Nodal Sets

We consider vectors of random variables, obtained by restricting the length of the nodal set of Berry’s random wave model to a finite collection of (possibly overlapping) smooth compact subsets of R2. Our main result shows that, as the energy diverges to infinity and after an adequate normalisation, these random elements converge in distribution to a Gaussian vector, whose covariance structure reproduces that of a homogeneous independently scattered random measure. A by-product of our analysis is that, when restricted to rectangles, the dominant chaotic projection of the nodal length field weakly converges to a standard Wiener sheet, in the Banach space of real-valued continuous mappings over a fixed compact set. An analogous study is performed for complex-valued random waves, in which case the nodal set is a locally finite collection of random points

Signatures of Star-planet interactions

Planets interact with their host stars through gravity, radiation and magnetic fields, and for those giant planets that orbit their stars within $\sim$10 stellar radii ($\sim$0.1 AU for a sun-like star), star-planet interactions (SPI) are observable with a wide variety of photometric, spectroscopic and spectropolarimetric studies. At such close distances, the planet orbits within the sub-alfv\'enic radius of the star in which the transfer of energy and angular momentum between the two bodies is particularly efficient. The magnetic interactions appear as enhanced stellar activity modulated by the planet as it orbits the star rather than only by stellar rotation. These SPI effects are informative for the study of the internal dynamics and atmospheric evolution of exoplanets. The nature of magnetic SPI is modeled to be strongly affected by both the stellar and planetary magnetic fields, possibly influencing the magnetic activity of both, as well as affecting the irradiation and even the migration of the planet and rotational evolution of the star. As phase-resolved observational techniques are applied to a large statistical sample of hot Jupiter systems, extensions to other tightly orbiting stellar systems, such as smaller planets close to M dwarfs become possible. In these systems, star-planet separations of tens of stellar radii begin to coincide with the radiative habitable zone where planetary magnetic fields are likely a necessary condition for surface habitability.Comment: Accepted for publication in the handbook of exoplanet

Stellar Coronal and Wind Models: Impact on Exoplanets

Surface magnetism is believed to be the main driver of coronal heating and stellar wind acceleration. Coronae are believed to be formed by plasma confined in closed magnetic coronal loops of the stars, with winds mainly originating in open magnetic field line regions. In this Chapter, we review some basic properties of stellar coronae and winds and present some existing models. In the last part of this Chapter, we discuss the effects of coronal winds on exoplanets.Comment: Chapter published in the "Handbook of Exoplanets", Editors in Chief: Juan Antonio Belmonte and Hans Deeg, Section Editor: Nuccio Lanza. Springer Reference Work

UVMag: stellar formation, evolution, structure and environment with space UV and visible spectropolarimetry

Important insights into the formation, structure, evolution and environment of all types of stars can be obtained through the measurement of their winds and possible magnetospheres. However, this has hardly been done up to now mainly because of the lack of UV instrumentation available for long periods of time. To reach this aim, we have designed UVMag, an M-size space mission equipped with a high-resolution spectropolarimeter working in the UV and visible spectral range. The UV domain is crucial in stellar physics as it is very rich in atomic and molecular lines and contains most of the flux of hot stars. Moreover, covering the UV and visible spectral domains at the same time will allow us to study the star and its environment simultaneously. Adding polarimetric power to the spectrograph will multiply tenfold the capabilities of extracting information on stellar magnetospheres, winds, disks, and magnetic fields. Examples of science objectives that can be reached with UVMag are presented for pre-main sequence, main sequence and evolved stars. They will cast new light onto stellar physics by addressing many exciting and important questions. UVMag is currently undergoing a Research and Technology study and will be proposed at the forthcoming ESA call for M-size missions. This spectropolarimeter could also be installed on a large UV and visible observatory (e.g. NASA's LUVOIR project) within a suite of instruments.Comment: Accepted in ApSS's special volume on UV astronom

FCNN-based axon segmentation for convection-enhanced delivery optimization

Purpose: Glioblastoma multiforme treatment is a challenging task in clinical oncology. Convection- enhanced delivery (CED) is showing encouraging but still suboptimal results due to drug leakages. Numerical models can predict drug distribution within the brain, but require retrieving brain physical properties, such as the axon diameter distribution (ADD), through axon architecture analysis. The goal of this work was to provide an automatic, accurate and fast method for axon segmentation in electronic microscopy images based on fully convolutional neural network (FCNN) as to allow automatic ADD computation. Methods: The segmentation was performed using a residual FCNN inspired by U-Net and Resnet. The FCNN training was performed exploiting mini-batch gradient descent and the Adam optimizer. The Dice coefficient was chosen as loss function. Results: The proposed segmentation method achieved results comparable with already existing methods for axon segmentation in terms of Information Theoretic Scoring (0.98 %) with a faster training (5 h on the deployed GPU) and without requiring heavy post-processing (testing time was 0.2 s with a non-optimized code). The ADDs computed from the segmented and ground-truth images were statistically equivalent. Conclusions: The algorithm proposed in this work allowed fast and accurate axon segmentation and ADD computation, showing promising performance for brain microstructure analysis for CED delivery optimization