The phenomenon of nonreciprocity arises from the disruption of time reversal symmetry, enabling the one‐way transfer of signals through specific channels. In the framework of cavity optomechanics, this symmetry breaking is attributed to a nonuniform radiation pressure force resulting from the interaction between light and matter. This study investigates a hybrid cavity optomechanical system (COMS) comprising two optical modes, directly coupled to each other via photon hopping interaction and indirectly via a common mechanical excitation in the form of a movable mirror, and an additional parallel metallic plate that induces a dynamical Casimir force (DCF) interaction between the plates. The two optical cavities are driven by two strong laser fields, accompanied by two weak probe classical fields from each port. The primary focus lies in exploring the nonreciprocal behavior of the light field across ports one and two, strongly manipulated by the DCF. The DCF plays a pivotal role in providing extra degrees of flexibility and manipulation in controlling the nonreciprocal signal transmission by modifying the resonance conditions of the fields within the hybrid COMS and is responsible for the amplification and swapping of information between the two ports.

Utilizing a crossdisciplinary approach, we explore Shannon information-theoretic characterizations of the information capacity limits of generic electromagnetic surfaces intended for possible use in wireless communication links. Our principal task is to first formulate at a general and rigorous level the electromagnetic theory of the information that can be extracted from the Maxwellian fields radiated by an arbitrarily-shaped continuous surface. This is then followed by a detailed derivation and illustration of practical physics-informed algorithms for computing approximations of the Shannon capacity of surfaces with any given geometry operating in Gaussian channels. Our formalism can address both near- and far-field information capacity scenarios, with a mathematical treatment that includes a complete characterization of the source-field polarization structure, mutual coupling, and interactions.

A general computational paradigm, the time-domain IDM method, is developed and applied to compute reactive energy and radiated power for arbitrary shaped antennas with different time-domain excitations. The proposed technique first utilizes finite-difference time-domain (FDTD) method to compute the time-domain radiating antenna currents from nearzone electric/magnetic fields. Further, the far-zone time-domain radiated power is analytically estimated using a suitable infinitesimal dipole model (IDM) of the antenna spacetime current distributions. The time-domain reactive energy is calculated by adopting a rigorous energy subtraction approach. The proposed time-domain IDM technique is first validated by reproducing the standard antenna-Q factor results of half-wavelength thin-wire dipoles. Secondly, time-domain reactive energy signatures are obtained for pulse-excited single and multi-band dipole antennas, both in isolated condition and two-element MIMO topology. Thirdly, the effects of parasitic reflector and director elements on the spatio-temporal energy dynamics of thin-wire Yagi-Uda antennas are demonstrated. The proposed algorithm is very general, applicable to arbitrary antenna shape and spacetime excitations, and hence is expected to enable engineers to look beyond traditional single frequency Q factors of electrically small antennas to probe into the more fundamental spatio-temporal energy dynamics of general radiating structures, especially future generation 5G MIMO antennas.

We propose a general design methodology for synthesizing surface or volume MIMO (Multi-Input-Multi-Output) antenna arrays with optimum cross-correlation diversity gain performance through engineering the array’s geometrical shape. The design algorithm is based on approximating arbitrary antenna geometrical configurations by arrays of infinitesimal (electrically small) dipoles and then using the recently-introduced cross-correlation Green’s function in order to compute far-field cross-correlations without the need to explicitly measure or compute far-zone fields. After directly expressing far-field cross correlation in terms of the geometrical details of the antenna array (position and orientation), the method applies a global optimization strategy (the genetic algorithm) to find optimum positions and orientations of the MIMO antennas’ elements within a given geometrical shape, resulting in the statistically best system performance. We provide extensive numerical results, including various array topologies (both fixed and conformal), with investigations of the impact of the array density, positions, and the relative orientations of the composing antenna elements on the attainable diversity gain. The paper also outlines an expansion of the proposed design methodology in order to deal with the important special case when a ground plane is present in the MIMO environment. It is found using the proposed methods that small MIMO Rx terminals can be made to fit any geometrical shape by properly controlling the position and the orientation of each element. All resulting arrays have dimensions that are smaller then 0.35λ×0.35λ with diversity gain of %80 or greater. It was also found that for each antenna topology, a critical number of antennas per unit area/volume exists such that no further improvement of the diversity gain is possible. This upper bound is geometrical in nature but is obtained through electromagnetic analysis, clearly demonstrating the impact of relative antenna positioning and orientations. Various 2D and 3D antenna array configurations, including disk, ring, spheres, spherical layers, were investigated and their critical array densities tabulated. Also, a practical example of conformal arrays mounted on an avionic nose was provided. It was also found that relative orientations alone can be exploited to substantially improve the performance of MIMO arrays by considering different scenarios comparing position-alone, orientation-alone, and position-andorientation optimization processes with random arrays in terms of diversity gain performance. The method developed in this paper can be expanded to include more complex antenna types, but is also suitable for scalable computing analysis of continuous large radiating and receiving antenna surfaces and massive MIMO. In particular, for mmWave applications, we expect that the need to optimize large arrays of tiny antennas will increase the demand for accurate and general design algorithms like the one proposed here.

In this paper, we propose an Infinitesimal Dipole Model, Cross-Correlation Green's Function (IDM-CGF) algorithm suitable for the efficient determination of spatial correlation matrix data for massive MIMO antennas with arbitrary element polarization and inter-element spacing. Through observations of the dominant eigenspace of the massive MIMO correlation matrix, we show that one can easily assess the available degrees of freedom in channel-hardened scenario of UE-to-BS communication. We provide several examples featuring 8×8 and 16 × 16 massive MIMO arrays comprised of infinitesimal dipoles (IDs), lending crucial insights into the correlation matrix eigenspace structural modifications incurred by changing element polarization, spatial positioning, and inter-element spacing.