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The aim of the article is to provide a summary of the work carried out in the framework of a research project funded by the Italian Ministry of Research. The main goal of the activity was to introduce multiple tools for reliable, affordable, and high-performance microwave hyperthermia for cancer therapy. The proposed methodologies and approaches target microwave diagnostics, accurate in vivo electromagnetic parameters estimation, and improvement in treatment planning using a single device. This article provides an overview of the proposed and tested techniques and shows their complementarity and interconnection. To highlight the approach, we also present a novel combination of specific absorption rate optimization via convex programming with a temperature-based refinement method implemented to mitigate the effect of thermal boundary conditions on the final temperature map. To this purpose, numerical tests were carried out for both simple and anatomically detailed 3D scenarios for the head and neck region. These preliminary results show the potential of the combined technique and improvements in the temperature coverage of the tumor target with respect to the case wherein no refinement is adopted.

Hypersonic flight regime is conventionally defined for Mach larger than 5; in these conditions, the flying object becomes enveloped in a plasma. This plasma is densest in thin surface layers, but in typical situations of interest it impacts electromagnetic wave propagation in an electrically large volume. We address this problem with a hybrid approach. We employ Equivalence Theorem to separate the inhomogeneous plasma region from the surrounding free space via an equivalent (Huygens) surface, and the Eikonal approximation to Maxwell equations in the large inhomogeneous region for obtaining equivalent currents on the separating surface. Then, we obtain the scattered field via (exact) free space radiation of these surface equivalent currents. The method is extensively tested against reference results and then applied to a real-life re-entry vehicle with full 3D plasma computed via Computational Fluid Dynamic (CFD) simulations. We address both scattering (RCS) from the entire vehicle and radiation from the on-board antennas. From our results, significant radio link path losses can be associated with plasma spatial variations (gradients) and collisional losses, to an extent that matches well the usually perceived blackout in crossing layers in cutoff. Furthermore, we find good agreement with existing literature concerning significant alterations of the radar response (RCS) due to the plasma envelope.

We present a 3D method to numerically design a realizable metasurface, which transforms a given incident field into a radiated field that satisfies mask-type (inequality) constraints. The method is based on an integral equation formulation, with local impedance boundary condition (IBC) approximation. The procedure yields the spatial distribution of the impedance, yet the process involves the synthesis of the equivalent current only. This current is constrained to correspond to a realizable surface impedance, i.e., passive, lossless, and with reactance values bounded by practical realizability limits. The current-based design avoids any solution of the forward problem, and the impedance is obtained from the synthesized current only at the end of the process. The procedure is gradient-based, with the gradient expressed in closed form. This allows handling large metasurfaces, with full spatial variability of the impedance in two dimensions. The method requires no a priori information, and all relevant operations in the iterative process can be evaluated with O(N logN) complexity. Application examples concentrate on the case of on-surface excitation and far-field pattern specifications; they show designs of circular and rectangular metasurface antennas of 20 wavelengths in size, with pencil- and shaped-beam patterns, and for both circular and linear polarization.

Microwave hyperthermia aims at selectively heating cancer cells to a supra-physiological temperature. For non-superficial tumors, this can be achieved by means of an antenna array equipped with a proper cooling system (the water bolus) to avoid overheating of the skin. In patient-specific treatment planning, antenna feedings are optimized to maximize the specific absorption rate (SAR) inside the tumor, or to directly maximize the temperature there, involving a higher numerical cost. We present here a method to effect a low-complexity temperature-based planning. It arises from recognizing that SAR and temperature have shifted peaks due to thermal boundary conditions at the water bolus and for physiological effects like air flow in respiratory ducts. In our method, temperature focusing on the tumor is achieved via a SAR-based optimization of the antenna excitations, but optimizing its target to account for the cooling effects. The temperature optimization process is turned into finding a SAR peak position that maximizes the chosen temperature objective function. Application of this method to the 3D head and neck region provides a temperature coverage that is consistently better than that obtained with SAR-optimization alone, also considering uncertainties in thermal parameters. This improvement is obtained by solving the bioheat equation a reduced number of times, avoiding its inclusion in a global optimization process., Comment: 7 pages, 6 figure, accepted for publication in IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology

Near-field (NF) measurements with NF-to-far-field (FF) transformation are a powerful and standard approach to modern antenna measurements. This approach implies a relatively close distance between device under test (DUT) and probe and, since the latter is rarely an ideal probe, it will introduce effects that have to be removed to obtain a FF which is only expression of the DUT. In this study, the authors introduce a probe compensation technique applicable to a generic scan surface with non-uniform, possibly incomplete sampling. The procedure is based on a hybridisation between simulations and measurements of the DUT, originally devised to achieve a radical undersampling of the NF with respect to the Nyquist criteria, in order to perform fast and accurate measurements. They present results that prove the effectiveness of the proposed approach.

In this paper, we present a fully automated procedure for the direct design of a novel class of single-feed flat antennas with patterning of a conductive surface. We introduce a convenient surface discretization, based on hexagonal cells, and define an appropriate objective function, including both gain and input matching requirements. The reference geometry is constituted by a very thin, single feed-point square panel. It features a backing metal plate (“ground”) and a top conductive layer, which is automatically patterned to achieve the desired radiation and input matching properties. The process employs an evolutionary algorithm combined with a boundary element electromagnetic solver. By applying this method, we designed an antenna tailored to the 2.4 GHz ISM frequency band, with a size of $$24\,\hbox {cm} \times 24\,\hbox {cm}$$24cm×24cm, i.e., $$2 \times 2$$2×2 wavelengths and an height of 4 mm, or 0.03 wavelengths. Measured data confirmed the expected high gain (13 dBi), with a remarkable aperture efficiency (higher than 50%, including losses), thus validating the proposed approach.

Entire-domain, spectral basis functions (BFs) have witnessed recent interest in the integral-equation analysis of large metasurface (MS) antennas modeled via homogenized impedance boundary conditions. We present a formulation employing classical Galerkin test via Rao–Wilton–Glisson functions yet assembled to represent entire-domain div-conforming BFs for the shape of interest (e.g., circular/coaxial waveguide modes). On the one hand, the rationale is that entire-domain, spectral BFs afford a significant economy in the number of necessary unknowns; on the other hand, being expressed as combination of Rao–Wilton–Glisson functions, reaction integrals are computed with optimum cost via fast methods. This is applied to reduce the cost of the optimization process used to design MS antennas based on spatially modulated reactance profiles. The authors support the method proposed, presenting criteria to define the entire-domain functions, considering the overall numerical complexity in an optimization framework, and providing a convergence analysis and the numerical results for holographic leaky-wave antennas, relevant in the MS context.

A hierarchical quasi-Helmholtz decomposition, originally developed to address the dense-discretization breakdowns for the electric field integral equation, is applied together with an algebraic preconditioner to improve the convergence of the combined field integral equation in multiscale problems. The effectiveness of the proposed method is studied first on some simple examples; next, tests on real-life cases up to several hundreds of wavelengths show its good performance.

This paper offers an efficient numerical approach to optimizing the design of large circular planar Metasurfaces (MTSs) antennas based on specially varying impedance profiles. Div-conforming spectral basis functions on the whole antenna are defined. The goal is to reduce the number of unknowns, to lead to a well-conditioned system, and to speed up the multiple solutions needed by an automatic optimization code. We consider the overall numerical complexity of the scheme and show its advantages in optimization applications.

The Near Field to far Field transformation problem is investigated in the case of near field samples acquired with a radio source mounted on an Unmanned Aerial Vehicle. The effect of irregular sampling and samples position uncertainty due to the vehicle flight are studied in a synthetic case with a real flight trajectory and a simulated antenna to be measured.

We present a novel algorithm for the synthesis of planar (2-D) arrays subject to arbitrary pattern masks and excitation constraints (e.g., dynamic range). The algorithm is simple and deterministic, and considers the radiating element pattern. The procedure starts with a conventional constrained fixed-grid synthesis on a regular lattice, yielding a goal radiated field. Next, element locations are selected sequentially by maximizing projection on field difference to goal, while excitation amplitudes are computed using fixed-grid constrained synthesis for irregular lattices. The final result is the sparse layout and constrained excitation coefficients. The proposed method is validated against literature results; application examples are given for circular flat-top, isoflux and triangular flat-top shaped beam patterns, with constraints on excitation coefficients dynamic range, both for isotropic and patch-type element patterns.

SUMMARY An efficient methodology to study conditions for stable in-phase synchronization in networks of periodic identical nonlinear oscillators is proposed. The problem of investigating synchronization properties on periodic trajectories is reduced to an eigenvalue problem by means of the joint application of master stability function and harmonic balance techniques. The proposed method permits to exploit the periodicity of trajectories, reducing computational time with respect to traditional time-domain approaches (which were designed to deal with generic attractors) and good accuracy. In addition, such method can easily deal with networks of nonlinear periodic oscillators described by differential-algebraic equations, and then both static and dynamic coupling could be studied. Copyright © 2011 John Wiley & Sons, Ltd.

Synchronization is deemed to play an important role in information processing in many neuronal systems. In this work, using a well known technique due to Pecora and Carroll, we investigate the existence of a synchronous state and the bifurcation diagram of a network of synaptically coupled neurons described by the Hindmarsh-Rose model. Through the analysis of the bifurcation diagram, the different dynamics of the possible synchronous states are evidenced. Furthermore, the influence of the topology on the synchronization properties of the network is shown through an example.

Some numerical results about the use of a Reduced Order Model to map currents to their radiated field in the presence of a scatterer are shown for antenna design and placement.

The project STRUCTURES, funded by the European Union, started in July 2012 to study problems related to the emerging threats of electromagnetic attacks to critical infrastructures. Partners of the team have worked to list possible threats, identify the main characteristics of the critical infrastructures our way of living depends on, test current protection strategies with different simulation and measurement techniques, and condensate the results in guidelines accessible to an audience wider than the one of people working in the field. Here, we summarize the challenges, the solutions, and the results of almost three years of work.

We present some preliminary results on the construction of a Reduced Order Model to simulate the electromagnetic response of a structure at different frequencies with Surface Integral Equations. The Discrete Empirical Interpolation Method, introduced for the simulation of nonlinear differential equations, is used in this context to accelerate the construction of the Reduced Order Model.

A short introduction is given about how to interpolate on the parameter space using custom basis functions obtained from simulations, also referred to as physics-based interpolation. Examples on a simplified structure are shown, encompassing from simpler to more challenging scenarios.

Some preliminary results are shown about the application to the case of dielectric and metallic object of a multiresolution change of basis to deal with the low-frequency breakdown appearing in the surface integral equation formulation of electromagnetic modelling. The main effect of the change of basis is to allow a simple diagonal preconditioner to become very effective, with respect to the analogous application without the change of basis. The idea, developed for the case of impenetrable objects treated with the Electric Field Integral Equation, is here applied to the case of penetrable objects as well, treated with the standard Poggio-Miller-Chang-Harrington-Wu-Tsai formulation. The effects on the condition number of the system resulting to the application of the Method of Moments, on the convergence path of an iterative solver, on the global error and on the error on the induced current in a simplified IEMI scenario are presented.

This paper proposes an innovative functional testing methodology suitable for RF end-to-end antenna testing. Any measurement point requires mechanical movement and signal integration time to produce a sample; thus, the most radical way to reduce testing time is to reduce the number of required measured samples to a minimum. The presented approach exploits existing measurement capabilities, and allows a radical under-sampling via insertion of a-priori information by way of suitable use of advanced numerical modeling tools. The methodology can be used also with non-canonical grids, and when only a limited number of measured points is available. Experimental results are provided to show the potentials of the method.

An overview of the European project STRUCTURES and its main challenges is given. Current and foreseen Intentional Electromagnetic Interference (IEMI) threats are classified according to their availability, their technical characteristics (such as bandwidth) and their portability. Critical infrastructures are identified and their most characteristic aspects are highlighted, from an electromagnetic point of view. These concepts are used to establish a set of reference threats to be investigated and possible techniques to handle simulations and measurements in this complex environment are explored, emphasizing the use of the topological approach. © 2012 IEEE.

In this chapter, the subject of synchronization is introduced and discussed considering the effects due to network topology. The chapter is organized as follows: (a) after a brief recap of a method due to Pecora and Carroll for checking the conditions for identical synchronization, several of the most popular topologies are considered, showing their influence on network synchronizability; (b) a technique, useful to find out the onset of synchronization in network of periodic oscillators is described in detail; (c) some simulation examples are given; (d) the case of synchronization in networks of nearly identical oscillators is illustrated by examples.

This paper presents a comprehensive application of the Field-to-TL approach implemented through a computer framework designed to facilitate data exchange among different computational tools. The framework is used also to compare results from different codes, specifically MDD (Multilevel Domain Differentiate) and CRIPTE, thus providing a validation test case for both of them. Furthermore, the comparison with measurements gives an idea of the degree of accuracy obtained with such an operating approach.

This paper deals with Compressive Domain Decomposition for Integral Equation methods; it starts from an overview encompassing computational aspects like parallel- and grid-computing. The DD paradigm is then analyzed in terms of overall computational requirements in association with fast factorizations; ways out to avoid bottlenecks are outlined.

This paper uses synchronization as a tool for further validating a circuit (HR-PWL circuit) recently proposed in the literature and based on a piecewise-linear (PWL) approxima- tion of the Hindmarsh-Rose (HR) neuron model. The accuracy of the single neuron hardware implementation has been already validated through bifurcation analysis tools. Here, the syn- chronization behavior of networks formed by HR neurons is simulated and compared to that of companion networks of PWL neurons, with the purpose of validating the HR-PWL circuit also from a collective behavior point of view. In the considered cases, the neurons are connected either by linear diffusive or by nonlinear sigmoidal coupling, with different topologies. The analysis is based on the Master Stability Function approach and is verified by extensive nu- merical time-domain simulations. The synchronization properties of the PWL neuron networks turn out to be qualitatively very similar to those of the companion HR networks, confirming the validity of the proposed hardware-implemented neuron.

We propose an index to measure cooperation among different time-series based on the Renyi entropy of the eigenvalues of the signal correlation matrix and an optimization step. The index could be considered as a generalization of a previously known index, based instead on the Shannon entropy. The extension to Renyi entropy and the optimization step allow a better use of the information conveyed by the correlation matrix, especially when dealing with a small number of signals.

We introduce a novel paradigm for generating basis functions for domain-decomposition (DD) in Integral-Equation formulations. The system uses the spectral-filling properties of the newly introduced Shannon basis functions, and a revised version of classical wavelet decomposition. Unlike other DD bases like CBF, SFX, this approach yields a sparse transformation matrix.

In this paper we present a simple, fast, novel algorithm for building networks whose topology has high synchronizability, is robust against failures, and supports efficient communication. We show that the algorithm is able to build these networks in a small number of steps that scales with the networks density. In addition, we track the evolution of different topological properties in the process of generating these networks. The results show that the topological properties are homogeneously distributed and the topology is less authoritative. Furthermore, we show that the networks we generate are more robust than random, geometric random, small-world or scale-free networks with similar average connectivity. Finally, all of the results indicate that the topology of these networks is entangled, which in many cases represents an optimal topology.

Indices based on correlation or more sub­tle strategies are among the standard ways to infer dependencies (i.e., exchange of information or cou­pling) in aggregations of different systems observed in the time domain. We propose a new index based on R´enyi entropy and confront it with other indices, studying if some of these techniques can recognize when we are observing the same system twice, even when the observation conditions are bad. It turns out that our index gives better results than the other examined ones. Moreover, we notice that those indices based on data processed with state space reconstruction and filtered with Principal Component Analysis are, generally, less sensitive to bad observations. However, state space reconstruction by itself is not enough to obtain good performances when the data are very noisy, and a Principal Component Analysis filter is needed to improve the results.

In this paper we analyze the collective behaviors of networks of Hindmarsh-Rose (HR) neurons and compare them with the behaviors of networks of piecewise-linear (PWL) approximations of the HR neurons. In all cases, the neurons are assumed to be symmetrically and diffusively coupled, with different topologies. The analysis is based on the Master Stability Function (MSF) approach. The obtained results are verified by numerical time domain simulations of networks of 100 neurons. The synchronization properties of the PWL networks turn out to be very similar to those of the HR networks, as well as the dynamical properties of the single neurons (analyzed elsewhere).

The reconstruction of the links among coupled dynamical systems can be handled in many ways. One of them is through synchronization, building a system composed by a "mirror" network and by evolution equations for the links of interest, in such a way that the two networks will synchronize if and only if the links are correctly estimated. A procedure based on this idea to estimate the topology of a network of interacting objects when the state variables are known is already present in literature, and here it is extended to systems ruled by implicit differential equations, to better suit some actual cases arising, in particular, in electric and electronic systems. The developed method is applied to a case of practical interest: the test of connections in a nanoscale device, introduced in the literature as "quantum dot cellular neural network", which can be easily produced in a self-assembled way. The whole iter has some steps sensitive to errors which can lead to a final device where the links among the "dots" are different from the desired ones. Our interest is in applying the method to detect such bad links.

Synchronization plays central role in processing of information in many systems. In this work we propose a method for both to predict the behavior of the synchronous state of a network of Hindmarsh-Rose neurons and to synthesize such a network with a prescribed time-domain evolution. This method combines the synchronization conditions of the network and the bifurcation diagram of the synchronous state.

Synchronization plays a central role in information processing in many systems. In this work, starting from a method for predicting the behavior of the synchronous state in a network of Hindmarsh-Rose neurons, the dependence of the synchronization properties of the network on the topology is shown.