Local Hamiltonians for Maximally Multipartite Entangled States

We study the conditions for obtaining maximally multipartite entangled states (MMES) as non-degenerate eigenstates of Hamiltonians that involve only short-range interactions. We investigate small-size systems (with a number of qubits ranging from 3 to 5) and show some example Hamiltonians with MMES as eigenstates.Comment: 6 pages, 3 figures, published versio

Magma and fluid migration at Yellowstone Caldera in the last three decades inferred from InSAR, leveling and gravity measurements

We studied the Yellowstone caldera geological unrest between 1977 and 2010 by investigating temporal changes in differential Interferometric Synthetic Aperture Radar (InSAR), precise spirit leveling and gravity measurements. The analysis of the 1992–2010 displacement time series, retrieved by applying the SBAS InSAR technique, allowed the identification of three areas of deformation: (i) the Mallard Lake (ML) and Sour Creek (SC) resurgent domes, (ii) a region close to the Northern Caldera Rim (NCR), and (iii) the eastern Snake River Plain (SRP). While the eastern SRP shows a signal related to tectonic deformation, the other two regions are influenced by the caldera unrest. We removed the tectonic signal from the InSAR displacements, and we modeled the InSAR, leveling, and gravity measurements to retrieve the best fitting source parameters. Our findings confirmed the existence of different distinct sources, beneath the brittle-ductile transition zone, which have been intermittently active during the last three decades. Moreover, we interpreted our results in the light of existing seismic tomography studies. Concerning the SC dome, we highlighted the role of hydrothermal fluids as the driving force behind the 1977–1983 uplift; since 1983–1993 the deformation source transformed into a deeper one with a higher magmatic component. Furthermore, our results support the magmatic nature of the deformation source beneath ML dome for the overall investigated period. Finally, the uplift at NCR is interpreted as magma accumulation, while its subsidence could either be the result of fluids migration outside the caldera or the gravitational adjustment of the source from a spherical to a sill-like geometr

Deriving High-Precision Radial Velocities

This chapter describes briefly the key aspects behind the derivation of precise radial velocities. I start by defining radial velocity precision in the context of astrophysics in general and exoplanet searches in particular. Next I discuss the different basic elements that constitute a spectrograph, and how these elements and overall technical choices impact on the derived radial velocity precision. Then I go on to discuss the different wavelength calibration and radial velocity calculation techniques, and how these are intimately related to the spectrograph's properties. I conclude by presenting some interesting examples of planets detected through radial velocity, and some of the new-generation instruments that will push the precision limit further.Comment: Lecture presented at the IVth Azores International Advanced School in Space Sciences on "Asteroseismology and Exoplanets: Listening to the Stars and Searching for New Worlds" (arXiv:1709.00645), which took place in Horta, Azores Islands, Portugal in July 201

Binary mixtures of condensates in generic confining potentials

We study a binary mixture of Bose-Einstein condensates, confined in a generic potential, in the Thomas-Fermi approximation. We search for the zero-temperature ground state of the system, both in the case of fixed numbers of particles and fixed chemical potentials.Comment: 20 pages, 2 figure

Towards agent-based crowd simulation in airports using games technology

We adapt popular video games technology for an agent-based crowd simulation in an airport terminal. To achieve this, we investigate the unique traits of airports and implement a virtual crowd by exploiting a scalable layered intelligence technique in combination with physics middleware and a socialforces approach. Our experiments show that the framework runs at interactive frame-rate and evaluate the scalability with increasing number of agents demonstrating navigation behaviour

Surface deformation of active volcanic areas retrieved with the SBAS-DInSAR technique: an overview

This paper presents a comprehensive overview of the surface deformation retrieval capability of the Differential Synthetic Aperture Radar Interferometry (DInSAR) algorithm, referred to as Small BAseline Subset (SBAS) technique, in the context of active volcanic areas. In particular, after a brief description of the algorithm some experiments relevant to three selected case-study areas are presented. First, we concentrate on the application of the SBAS algorithm to a single-orbit scenario, thus considering a set of SAR data composed by images acquired on descending orbits by the European Remote Sensing (ERS) radar sensors and relevant to the Long Valley caldera (eastern California) area. Subsequently, we address the capability of the SBAS technique in a multipleorbit context by referring to Mt. Etna volcano (southern Italy) test site, with respect to which two different ERS data set, composed by images acquired both on ascending and descending orbits, are available. Finally, we take advantage of the capability of the algorithm to work in a multi-platform scenario by jointly exploiting two different sets of SAR images collected by the ERS and the Environment Satellite (ENVISAT) radar sensors in the Campi Flegrei caldera (southern Italy) area. The presented results demonstrate the effectiveness of the algorithm to investigate the deformation field in active volcanic areas and the potential of the DInSAR methodologies within routine surveillance scenario

Integrating Superconductive and Optical Circuits

We have integrated on oxidized silicon wafers superconductive films and Josephson junctions along with sol-gel optical channel waveguides. The fabrication process is carried out in two steps that result to be solid and non-invasive. It is demonstrated that 660 nm light, coupled from an optical fibre into the channel sol-gel waveguide, can be directed toward superconducting tunnel junctions whose current-voltage characteristics are affected by the presence of the radiation. The dependence of the change in the superconducting energy gap under optical pumping is discussed in terms of a non-equilibrium superconductivity model.Comment: Document composed of 7 pages of text and 3 figure

Change Detection Techniques with Synthetic Aperture Radar Images: Experiments with Random Forests and Sentinel-1 Observations

This work aims to clarify the potential of incoherent and coherent change detection (CD) approaches for detecting and monitoring ground surface changes using sequences of synthetic aperture radar (SAR) images. Nowadays, the growing availability of remotely sensed data collected by the twin Sentinel-1A/B sensors of the European (EU) Copernicus constellation allows fast mapping of damage after a disastrous event using radar data. In this research, we address the role of SAR (amplitude) backscattered signal variations for CD analyses when a natural (e.g., a fire, a flash flood, etc.) or a human-induced (disastrous) event occurs. Then, we consider the additional pieces of information that can be recovered by comparing interferometric coherence maps related to couples of SAR images collected between a principal disastrous event date. This work is mainly concerned with investigating the capability of different coherent/incoherent change detection indices (CDIs) and their mutual interactions for the rapid mapping of "changed" areas. In this context, artificial intelligence (AI) algorithms have been demonstrated to be beneficial for handling the different information coming from coherent/incoherent CDIs in a unique corpus. Specifically, we used CDIs that synthetically describe ground surface changes associated with a disaster event (i.e., the pre-, cross-, and post-disaster phases), based on the generation of sigma nought and InSAR coherence maps. Then, we trained a random forest (RF) to produce CD maps and study the impact on the final binary decision (changed/unchanged) of the different layers representing the available synthetic CDIs. The proposed strategy was effective for quickly assessing damage using SAR data and can be applied in several contexts. Experiments were conducted to monitor wildfire's effects in the 2021 summer season in Italy, considering two case studies in Sardinia and Sicily. Another experiment was also carried out on the coastal city of Houston, Texas, the US, which was affected by a large flood in 2017; thus, demonstrating the validity of the proposed integrated method for fast mapping of flooded zones using SAR data

Renormalization of Coulomb interactions in s-wave superconductor Nax_xCoO2_2

We study the renormalized Coulomb interactions due to retardation effect in Na$_x$CoO$_2$. Although the Morel-Anderson's pseudo potential for $a_{1g}$ orbital $\mu^*_{a1g}$ is relatively large because the direct Coulomb repulsion $U$ is large, that for interband transition between $a_{1g}$ and $e_g'$ orbitals $\mu^*_{a1g,eg'}$ is very small since the renormalization factor for pair hopping $J$ is square of that for $U$. Therefore, the s-wave superconductivity due to valence-band Suhl-Kondo mechanism will survive against strong Coulomb interactions. The interband hopping of Cooper pairs due to shear phonons is essential to understand the superconductivity in Na$_x$CoO$_2$.Comment: 2pages, 2figures, Proceedings of ICM in Kyoto, 200

Detection of activity and position of speakers by using deep neural networks and acoustic data augmentation

The task of Speaker LOCalization (SLOC) has been the focus of numerous works in the research field, where SLOC is performed on pure speech data, requiring the presence of an Oracle Voice Activity Detection (VAD) algorithm. Nevertheless, this perfect working condition is not satisfied in a real world scenario, where employed VADs do commit errors. This work addresses this issue with an extensive analysis focusing on the relationship between several data-driven VAD and SLOC models, finally proposing a reliable framework for VAD and SLOC. The effectiveness of the approach here discussed is assessed against a multi-room scenario, which is close to a real-world environment. Furthermore, up to the authors’ best knowledge, only one contribution proposes a unique framework for VAD and SLOC acting in this addressed scenario; however, this solution does not rely on data-driven approaches. This work comes as an extension of the authors’ previous research addressing the VAD and SLOC tasks, by proposing numerous advancements to the original neural network architectures. In details, four different models based on convolutional neural networks (CNNs) are here tested, in order to easily highlight the advantages of the introduced novelties. In addition, two different CNN models go under study for SLOC. Furthermore, training of data-driven models is here improved through a specific data augmentation technique. During this procedure, the room impulse responses (RIRs) of two virtual rooms are generated from the knowledge of the room size, reverberation time and microphones and sources placement. Finally, the only other framework for simultaneous detection and localization in a multi-room scenario is here taken into account to fairly compare the proposed method. As result, the proposed method is more accurate than the baseline framework, and remarkable improvements are specially observed when the data augmentation techniques are applied for both the VAD and SLOC tasks