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Every new generation of mobile networks brings significant advances in two segments, enhancement of the network parameters within the legacy technologies and introduction of new technologies enabling new paradigms in designing the networks. In the first class of enhancements the effort is to increase data rates, improve energy efficiency, enhance connectivity, reduce data transmission latency etc. In the second class of innovations for 6G and 7G, we anticipate focus on optimum integration of advanced ML and AI in general, and quantum computing with the continuous interest in the satellite networks for optimal quantum key distribution . By introducing quantum technology 7G will be able to speed up computing processes in the net, enhance network security as well as to enable distributed QC, which is a new paradigm in computer sciences. Using advanced networks as a basic ingredient of inter system integration, here we focus only on the second segment of anticipated innovations in networking and present a survey of the subset of potential technology enablers for the above concept with special emphasis on the inter dependency of the solutions chosen in different segments of the network. In Section II, we present several anticipated 6G/7G (system of systems type) network optimization examples resulting in a new paradigm of network optimization indicating a need for quantum computing and quantum computing based optimization algorithms. In Section III we survey work on quantum cryptography and QKD.

In this paper, we propose the use of epistemic dependencies to express data protection policies in Controlled Query Evaluation (CQE), which is a form of confidentiality-preserving query answering over ontologies and databases. The resulting policy language goes significantly beyond those proposed in the literature on CQE so far, allowing for very rich and practically interesting forms of data protection rules. We show the expressive abilities of our framework and study the data complexity of CQE for (unions of) conjunctive queries when ontologies are specified in the Description Logic DL-Lite_R. Interestingly, while we show that the problem is in general intractable, we prove tractability for the case of acyclic epistemic dependencies by providing a suitable query rewriting algorithm. The latter result paves the way towards the implementation and practical application of this new approach to CQE.

Post Quantum and Quantum Cryptography schemes are feasible quantum computer applications for 7G networks. These schemes could possibly replace existing schemes. These algorithms have been compromised by advances in quantum search algorithms run on quantum computers like Shor algorithm. Shor algorithm is a quantum algorithm for finding the prime factors of an integer which is the basis of existing algorithm. This has become an available quantum computer application putting the use of ESA algorithm at risk. Our recent paper provides a detailed survey of the work on post quantum and quantum cryptography algorithms with focus on their applicability in 7G networks. Since the paper focuses on the cryptography algorithms as a follow up, in this paper, we provide a new framework for quantum network optimization and survey in detail the work on enabling technologies (quantum hardware) for the practical implementation of these algorithms including the most important segments of quantum hardware in 7G. As always in engineering practice practical solutions are a compromise between the performance and complexity of the implementation. For this reason, as the main contribution, the paper presents a network and computer applications optimization framework that includes implementation imperfections. The tools should be useful in optimizing future generation practical computer system design. After that a comprehensive survey of the existing work on quantum hardware is presented pointing out the sources of these imperfections. This enables us to make a fair assessment of how much investment into quantum hardware improvements contributes to the performance enhancement of the overall system. In this way a decision can be made on proper partitioning between the investment in hardware and system level complexity.

We consider the first eigenvalue of the magnetic Laplacian in a bounded and simply connected planar domain, with uniform magnetic field and Neumann boundary conditions. We investigate the reverse Faber-Krahn inequality conjectured by S. Fournais and B. Helffer, stating that this eigenvalue is maximized by the disk for a given area. Using the method of level lines, we prove the conjecture for small enough values of the magnetic field (those for which the corresponding eigenfunction in the disk is radial)., Comment: 27 pages. Accepted pre-publication version

Quantum state teleportation represents a pillar of quantum information and a milestone on the roadmap towards quantum networks with a large number of nodes. Successful photonic demonstrations of this protocol have been carried out employing different qubit encodings. However, demonstrations in the Fock basis encoding are challenging, due to the impossibility of creating a coherent superposition of vacuum-one photon states on a single mode with linear optics. Previous realizations using such an encoding strongly relied on ancillary modes of the electromagnetic field, which only allowed the teleportation of subsystems of entangled states. Here, we enable quantum teleportation of genuine vacuum-one photon states avoiding ancillary modes, by exploiting coherent control of a resonantly excited semiconductor quantum dot in a micro-cavity. Within our setup, we can teleport vacuum-one-photon qubits and perform entanglement swapping in such an encoding. Our results may disclose new potentialities of quantum dot single-photon sources for quantum information applications., Comment: 10 pages, 4 figures + Supplementary Information

We study the geometry of the first two eigenvalues of a magnetic Steklov problem on an annulus $\Sigma$ (a compact Riemannian surface with genus zero and two boundary components), the magnetic potential being the harmonic one-form having flux $\nu\in\mathbb R$ around any of the two boundary components. The resulting spectrum can be seen as a perturbation of the classical, non-magnetic Steklov spectrum, obtained when $\nu=0$ and studied e.g., by Fraser and Schoen. We obtain sharp upper bounds for the first and the second normalized eigenvalues and we discuss the geometry of the maximisers. Concerning the first eigenvalue, we isolate a noteworthy class of maximisers which we call $\alpha$-surfaces: they are free-boundary surfaces which are stationary for a weighted area functional (depending on the flux) and have proportional principal curvatures at each point; in particular, they belong to the class of linear Weingarten surfaces. We then study the second normalized eigenvalue for a fixed flux $\nu$ and prove the existence of a maximiser for rotationally invariant metrics. Moreover, the corresponding eigenfunctions define a free-boundary immersion in the unit ball of $\mathbb R^3$. Finally, we prove that the second normalized eigenvalue associated to a flux $\nu$ has an absolute maximum when $\nu=0$, the corresponding maximiser being the critical catenoid.

Neural networks find widespread use in scientific and technological applications, yet their implementations in conventional computers have encountered bottlenecks due to ever-expanding computational needs. Photonic neuromorphic hardware, which manipulates information and represents data continuously in the optical domain, is one of the promising platforms with potential advantages of massive parallelism, ultralow latency, and reduced energy consumption. While linear photonic neural networks are within reach, photonic computing with large-scale optical nonlinear nodes remains largely unexplored. Here, we demonstrate a large-scale, high-performance nonlinear photonic neural system based on a disordered polycrystalline slab composed of lithium niobate nanocrystals. Mediated by random quasi-phase-matching and multiple scattering, linear and nonlinear optical speckle features are generated as the interplay between the simultaneous linear random scattering and the second-harmonic generation, defining a complex neural network in which the second-order nonlinearity acts as internal nonlinear activation functions. Benchmarked against linear random projection, such nonlinear mapping embedded with rich physical computational operations shows improved performance across a large collection of machine learning tasks in image classification, regression, and graph classification with varying complexity. Demonstrating up to 27,648 input and 3,500 nonlinear output nodes, the combination of optical nonlinearity and random scattering serves as a scalable computing engine for diverse applications.

We present a graph-based model for multiple scattering of light in integrated lithium niobate on insulator (LNOI) networks, which describes an open network of single-mode integrated waveguides with tunable scattering at the network nodes. We first validate the model at small scale with experimental LNOI resonator devices and show consistent agreement between simulated and measured spectral data. Then, the model is used to demonstrate a novel platform for on-chip multiple scattering in large-scale optical networks up to few hundred nodes, with tunable scattering behaviour and tailored disorder. Combining our simple graph-based model with material properties of LNOI, this platform creates new opportunities to control randomness in large optical networks.

We consider the eigenvalues of the magnetic Laplacian on a bounded domain $\Omega$ of $\mathbb R^2$ with uniform magnetic field $\beta>0$ and magnetic Neumann boundary conditions. We find upper and lower bounds for the ground state energy $\lambda_1$ and we provide semiclassical estimates in the spirit of Kr\"oger for the first Riesz mean of the eigenvalues. We also discuss upper bounds for the first eigenvalue for non-constant magnetic fields $\beta=\beta(x)$ on a simply connected domain in a Riemannian surface. In particular: we prove the upper bound $\lambda_1<\beta$ for a general plane domain, and the upper bound $\lambda_1<\sup_{x\in\Omega}|\beta(x)|$ for a variable magnetic field when $\Omega$ is simply connected. For smooth domains, we prove a lower bound of $\lambda_1$ depending only on the intensity of the magnetic field $\beta$ and the rolling radius of the domain. The estimates on the Riesz mean imply an upper bound for the averages of the first $k$ eigenvalues which is sharp when $k\to\infty$ and consists of the semiclassical limit $\dfrac{2\pi k}{|\Omega|}$ plus an oscillating term. We also construct several examples, showing the importance of the topology: in particular we show that an arbitrarily small tubular neighborhood of a generic simple closed curve has lowest eigenvalue bounded away from zero, contrary to the case of a simply connected domain of small area, for which $\lambda_1$ is always small.

Penetration of cellphones into markets requires their robust operation in time-varying radio environments, especially for millimeter-wave communications. Hands and fingers of a human cause significant changes in the physical environments of cellphones, which influence the communication qualities to a large extent. In this paper, electromagnetic models of real hands and cellphone antennas are developed, and their efficacy is verified through measurements for the first time in the literature. Referential cellphone antenna arrays at $28$ and $39$~GHz are designed. Their radiation properties are evaluated through near-field scanning of the two prototypes, first in free space for calibration of the antenna measurement system and for building simplified models of the cellphone arrays. Next, radiation measurements are set up with real hands so that they are compared with electromagnetic simulations of the interaction between hands and simplified models of the arrays. The comparison showed a close agreement in terms of spherical coverage, indicating the efficacy of the hand and antenna array models along with the measurement approach. The repeatability of the measurements is $0.5$~dB difference in terms of cumulative distributions of the spherical coverage at the median level., Comment: 11 pages, 17 figures, Journal

Controlled Query Evaluation (CQE) has been recently studied in the context of Semantic Web ontologies. The goal of CQE is concealing some query answers so as to prevent external users from inferring confidential information. In general, there exist multiple, mutually incomparable ways of concealing answers, and previous CQE approaches choose in advance which answers are visible and which are not. In this paper, instead, we study a dynamic CQE method, namely, we propose to alter the answer to the current query based on the evaluation of previous ones. We aim at a system that, besides being able to protect confidential data, is maximally cooperative, which intuitively means that it answers affirmatively to as many queries as possible; it achieves this goal by delaying answer modifications as much as possible. We also show that the behavior we get cannot be intensionally simulated through a static approach, independent of query history. Interestingly, for OWL 2 QL ontologies and policy expressed through denials, query evaluation under our semantics is first-order rewritable, and thus in AC0 in data complexity. This paves the way for the development of practical algorithms, which we also preliminarily discuss in the paper., Comment: This paper is the extended version of "P.Bonatti, G.Cima, D.Lembo, L.Marconi, R.Rosati, L.Sauro, and D.F.Savo. Controlled query evaluation in OWL 2 QL: A "Longest Honeymoon" approach" accepted for publication at ISWC 2022

The importance of indoor mobile connectivity has increased during the last years, especially during the Covid-19 pandemic. In contrast, new energy-efficient buildings contain structures like low-emissive windows and multi-layered thermal insulations which all block radio signals effectively. To solve this problem with indoor connectivity, we study passive antenna systems embedded in walls of low-energy buildings. We provide analytical models of a load bearing wall along with numerical and empirical evaluations of wideband back-to-back antenna spiral antenna system in terms of electromagnetic- and thermal insulation. The antenna systems are optimized to operate well when embedded into load bearing walls. Unit cell models of the antenna embedded load bearing wall, which are called signal-transmissive walls in this paper, are developed to analyze their electromagnetic and thermal insulation properties. We show that our signal-transmissive wall improves the electromagnetic transmission compared to a raw load bearing wall over a wide bandwidth of 2.6-8 GHz, covering most of the cellular new radio frequency range 1, without compromising the thermal insulation capability of the wall demanded by the building regulation. Optimized antenna deployment is shown with 22 dB improvement in electromagnetic transmission through the load bearing wall., Comment: 9 pages, 13 figures, submitted to IEEE Transactions on Antennas and Propagation

We discuss isoperimetric inequalities for the magnetic Laplacian on bounded domains of $\mathbb R^2$ endowed with an Aharonov-Bohm potential. When the flux of the potential around the pole is not an integer, the lowest eigenvalue for the Neumann and the Steklov problems is positive. We establish isoperimetric inequalitites for the lowest eigenvalue in the spirit of the classical inequalities of Szeg\"o-Weinberger, Brock and Weinstock, the model domain being a disk with the pole at its center. We consider more generally domains in the plane endowed with a rotationally invariant metric, which include the spherical and the hyperbolic case.