Searcharxiv⌕ Search

arXiv subjects

Rosario G. Garroppo

Publications and source records attributed to Rosario G. Garroppo.

3 recordsLinked to original sources

Transduction-Enabled Superconducting Quantum Repeater: Toward Deterministic Entanglement Distribution with High-Fidelity Gates

Long-distance entanglement distribution is hindered by photon loss in optical fibers and the nocloning theorem. Optical quantum repeater (QR) protocols rely on Bell state measurements (BSMs), they are intrinsically limited to probabilistic photon operations and fail 50% of the time. We propose a hybrid approach to building quantum repeaters that combines the high transmission speed of photonic qubits in optical fiber with the high-fidelity quantum processing capabilities enabled by superconducting circuits. The transduction-enabled superconducting QR (TESQR) architecture eliminates the need for probabilistic BSMs and allows deterministic processing operations. The TESQR framework always yields a final state at the remote nodes rather than aborting on photon loss, manifesting deterministic entanglement distribution within certain parameter regimes. We evaluate the performance by assessing output-state fidelities and success probabilities of entanglement distribution using realistic noise models. Additionally, we integrate an entanglement purification scheme and evaluate the performance through numerical simulations in QuTiP environment. Our results show that, for entanglement swapping, the proposed scheme improves the entanglement distribution rate by an average of 63% and by up to 159% compared with photonic-only architectures. Moreover, after purification, the end-to-end fidelities exceed 0.8 over distances up to 20 km.

quant-ph↗

QR-MO: Q-Routing for Multi-Objective Shortest-Path Computation in 5G-MEC Systems

Multi-access edge computing (MEC) is a promising technology that provides low-latency processing capabilities. To optimize the network performance in a MEC system, an efficient routing path between a user and a MEC host is essential. The network performance is characterized by multiple attributes, including packet-loss probability, latency, and jitter. A user service may require a particular combination of such attributes, complicating the shortest-path computation. This paper introduces Q-Routing for Multi-Objective shortest-path computation (QR-MO), which simultaneously optimizes multiple attributes. We compare the QR-MO's solutions with the optimal solutions provided by the Multi-objective Dijkstra Algorithm (MDA). The result shows the favorable potential of QR-MO. After 100 episodes, QR-MO achieves 100% accuracy in networks with low to moderate average node degrees, regardless of the size, and over 85% accuracy in networks with high average node degrees.

cs.NI↗

5G Multi-access Edge Computing: a Survey on Security, Dependability, and Performance

The Fifth Generation (5G) of mobile networks offers new and advanced services with stricter requirements. Multi-access Edge Computing (MEC) is a key technology that enables these new services by deploying multiple devices with computing and storage capabilities at the edge of the network, close to end-users. MEC enhances network efficiency by reducing latency, enabling real-time awareness of the local environment, allowing cloud offloading, and reducing traffic congestion. New mission-critical applications require high security and dependability, which are rarely addressed alongside performance. This survey paper fills this gap by presenting 5G MEC's three aspects: security, dependability, and performance. The paper provides an overview of MEC, introduces taxonomy, state-of-the-art, and challenges related to each aspect. Finally, the paper presents the challenges of jointly addressing these three aspects.

cs.NI↗