Hidden orders and (anti-)Magnetoelectric Effects in Cr2_2O3_3 and α\alpha-Fe2_2O3_3

We present ab initio calculations of hidden magnetoelectric multipolar order in Cr$_2$O$_3$ and its iron-based analogue, $\alpha$-Fe$_2$O$_3$. First, we discuss the connection between the order of such hidden multipoles and the linear magnetoelectric effect. Next, we show the presence of hidden antiferroically-ordered magnetoelectric multipoles in both the prototypical magnetoelectric material Cr$_2$O$_3$, and centrosymmetric $\alpha$-Fe$_2$O$_3$, which has the same crystal structure as Cr$_2$O$_3$, but a different magnetic dipolar ordering. In turn, we predict anti-magnetoelectric effects, in which local magnetic dipole moments are induced in opposite directions under the application of an external electric field, to create an additional antiferromagnetic ordering. We confirm the predicted induced moments using first-principles calculations. Our results demonstrate the existence of hidden magnetoelectric multipoles leading to local linear magnetoelectric responses even in centrosymmetric materials, where a net bulk linear magnetoelectric effect is forbidden by symmetry

A three-order-parameter bistable magnetoelectric multiferroic metal

Using first-principles calculations we predict that the layered-perovskite metal Bi5Mn5O17 is a ferromagnet, ferroelectric, and ferrotoroid which may realize the long sought-after goal of a room-temperature ferromagnetic single-phase multiferroic with large, strongly coupled, primary-order polarization and magnetization. Bi5Mn5O17 has two nearly energy-degenerate ground states with mutually orthogonal vector order parameters (polarization, magnetization, ferrotoroidicity), which can be rotated globally by switching between ground states. Giant cross-coupling magnetoelectric and magnetotoroidic effects, as well as optical non-reciprocity, are thus expected. Importantly, Bi5Mn5O17 should be thermodynamically stable in O-rich growth conditions, and hence experimentally accessible

A New Monitor and Control Power Supply PCB for Biasing LNAs of Large Radio Telescopes Receivers

The biasing of low noise amplifiers (LNA) is of paramount importance for the receivers of large radio telescopes. High stability, optimal trade-off between gain and noise figure, remote control, and mitigation of the radio frequency interferences (RFIs) are all desirable features in the choice of the electronic board devoted to power supply the LNAs. In this paper, we propose the design and characterization of a multilayer printed circuit board (PCB), named GAIA, able to meet all the aforementioned requirements. The GAIA board is a 3-Unit, four-layer, rack-mountable, programmable PCB for the remote biasing of the LNAs, with monitor and control capabilities, specifically designed to operate in the receivers of the 64-m diameter Sardinia Radio Telescope (SRT). We describe the architecture, layout, and measurements of the GAIA board. Our results show that the GAIA power supply provides high stability of the output bias voltages and, in comparison with the old analogic biasing board used so far in the SRT receivers, it shows comparable or better frequency stability, other than a remarkable mitigation of the RFIs

Space Debris Detection in Low Earth Orbit with the Sardinia Radio Telescope

Space debris are orbiting objects that represent a major threat for space operations. The most used countermeasure to face this threat is, by far, collision avoidance, namely the set of maneuvers that allow to avoid a collision with the space debris. Since collision avoidance is tightly related to the knowledge of the debris state (position and speed), the observation of the orbital debris is the key of the problem. In this work a bistatic radar configuration named BIRALET (BIstatic RAdar for LEO Tracking) is used to detect a set of space debris at 410 MHz, using the Sardinia Radio Telescope as the receiver antenna. The signal-to-noise ratio, the Doppler shift and the frequency spectrum for each debris are reported

On the sign of the linear magnetoelectric coefficient in Cr2_2O3_3

We establish the sign of the linear magnetoelectric (ME) coefficient, $\alpha$, in chromia, Cr$_2$O$_3$. Cr$_2$O$_3$ is the prototypical linear ME material, in which an electric (magnetic) field induces a linearly proportional magnetization (polarization), and a single magnetic domain can be selected by annealing in combined magnetic (H) and electric (E) fields. Opposite antiferromagnetic domains have opposite ME responses, and which antiferromagnetic domain corresponds to which sign of response has previously been unclear. We use density functional theory (DFT) to calculate the magnetic response of a single antiferromagnetic domain of Cr$_2$O$_3$ to an applied in-plane electric field at 0 K. We find that the domain with nearest neighbor magnetic moments oriented away from (towards) each other has a negative (positive) in-plane ME coefficient, $\alpha_{\perp}$, at 0 K. We show that this sign is consistent with all other DFT calculations in the literature that specified the domain orientation, independent of the choice of DFT code or functional, the method used to apply the field, and whether the direct (magnetic field) or inverse (electric field) ME response was calculated. Next, we reanalyze our previously published spherical neutron polarimetry data to determine the antiferromagnetic domain produced by annealing in combined E and H fields oriented along the crystallographic symmetry axis at room temperature. We find that the antiferromagnetic domain with nearest-neighbor magnetic moments oriented away from (towards) each other is produced by annealing in (anti-)parallel E and H fields, corresponding to a positive (negative) axial ME coefficient, $\alpha_{\parallel}$, at room temperature. Since $\alpha_{\perp}$ at 0 K and $\alpha_{\parallel}$ at room temperature are known to be of opposite sign, our computational and experimental results are consistent.Comment: 11 pages, 5 figure

Imaging of SNR IC443 and W44 with the Sardinia Radio Telescope at 1.5 GHz and 7 GHz

Observations of supernova remnants (SNRs) are a powerful tool for investigating the later stages of stellar evolution, the properties of the ambient interstellar medium, and the physics of particle acceleration and shocks. For a fraction of SNRs, multi-wavelength coverage from radio to ultra high-energies has been provided, constraining their contributions to the production of Galactic cosmic rays. Although radio emission is the most common identifier of SNRs and a prime probe for refining models, high-resolution images at frequencies above 5 GHz are surprisingly lacking, even for bright and well-known SNRs such as IC443 and W44. In the frameworks of the Astronomical Validation and Early Science Program with the 64-m single-dish Sardinia Radio Telescope, we provided, for the first time, single-dish deep imaging at 7 GHz of the IC443 and W44 complexes coupled with spatially-resolved spectra in the 1.5-7 GHz frequency range. Our images were obtained through on-the-fly mapping techniques, providing antenna beam oversampling and resulting in accurate continuum flux density measurements. The integrated flux densities associated with IC443 are S_1.5GHz = 134 +/- 4 Jy and S_7GHz = 67 +/- 3 Jy. For W44, we measured total flux densities of S_1.5GHz = 214 +/- 6 Jy and S_7GHz = 94 +/- 4 Jy. Spectral index maps provide evidence of a wide physical parameter scatter among different SNR regions: a flat spectrum is observed from the brightest SNR regions at the shock, while steeper spectral indices (up to 0.7) are observed in fainter cooling regions, disentangling in this way different populations and spectra of radio/gamma-ray-emitting electrons in these SNRs.Comment: 13 pages, 9 figures, accepted for publication to MNRAS on 18 May 201

The Sardinia Space Communication Asset: Performance of the Sardinia Deep Space Antenna X-Band Downlink Capability

The Sardinia deep space antenna (SDSA), managed by the Italian Space Agency (ASI) has started its operations in 2017 aiming to provide tracking and communication services for deep space, near earth, and lunar missions, and to support new and challenging radio science experiments. The SDSA shares with the Sardinia Radio Telescope (SRT) a part of the system and infrastructure, but has its own specific equipment and a dedicated control center. The current SDSA capabilities involve the X-band (8.4 GHz-8.5 GHz) reception of telemetry from deep space probes within interplanetary missions. In this work we describe the development and performance of the X-band receiving system. It was designed and assembled with the cooperation of both the NASA-Jet Propulsion Laboratory (JPL) and the European Space Agency (ESA). Specifically, NASA-JPL provided the X-band feed and the cryogenic receiver installed in a suitable focus of the SRT devoted to space applications, and ESA provided the intermediate frequency modem system (IFMS) for signal processing. The coupling of the X-band feed with the parabolic reflector of the SRT and the radiating features of the SDSA have been evaluated with simulations performed using CST Studio Suite and GRASP by Ticra. The telecommunication performance of the system has been assessed by measurements and experiments showing a good agreement between estimates and simulations

Quantum ESPRESSO toward the exascale

Quantum ESPRESSO is an open-source distribution of computer codes for quantum-mechanical materials modeling, based on density-functional theory, pseudopotentials, and plane waves, and renowned for its performance on a wide range of hardware architectures, from laptops to massively parallel computers, as well as for the breadth of its applications. In this paper, we present a motivation and brief review of the ongoing effort to port Quantum ESPRESSO onto heterogeneous architectures based on hardware accelerators, which will overcome the energy constraints that are currently hindering the way toward exascale computing

Unsupervised Segmentation of Fetal Brain MRI using Deep Learning Cascaded Registration

Accurate segmentation of fetal brain magnetic resonance images is crucial for analyzing fetal brain development and detecting potential neurodevelopmental abnormalities. Traditional deep learning-based automatic segmentation, although effective, requires extensive training data with ground-truth labels, typically produced by clinicians through a time-consuming annotation process. To overcome this challenge, we propose a novel unsupervised segmentation method based on multi-atlas segmentation, that accurately segments multiple tissues without relying on labeled data for training. Our method employs a cascaded deep learning network for 3D image registration, which computes small, incremental deformations to the moving image to align it precisely with the fixed image. This cascaded network can then be used to register multiple annotated images with the image to be segmented, and combine the propagated labels to form a refined segmentation. Our experiments demonstrate that the proposed cascaded architecture outperforms the state-of-the-art registration methods that were tested. Furthermore, the derived segmentation method achieves similar performance and inference time to nnU-Net while only using a small subset of annotated data for the multi-atlas segmentation task and none for training the network. Our pipeline for registration and multi-atlas segmentation is publicly available at https://github.com/ValBcn/CasReg.Comment: 17 pages, 8 figures, 5 tables, paper submitted to IEEE transaction on medical imagin