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Angela Sara Cacciapuoti

Researcher at University of Naples Federico II

Publications -  84
Citations -  2383

Angela Sara Cacciapuoti is an academic researcher from University of Naples Federico II. The author has contributed to research in topics: Quantum network & Cognitive radio. The author has an hindex of 25, co-authored 75 publications receiving 1641 citations. Previous affiliations of Angela Sara Cacciapuoti include Information Technology University & Georgia Institute of Technology.

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Quantum Internet: Networking Challenges in Distributed Quantum Computing

TL;DR: The goal of this work is to shed light on the challenges and open problems of Quantum Internet design and introduce quantum teleportation as the key strategy for transmitting quantum information without physically transferring the particle that stores the quantum information or violating the principles of quantum mechanics.
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Quantum internet: from communication to distributed computing!

TL;DR: The authors discuss the exponential computing speed-up achievable by interconnecting quantum computers through a quantum internet and identify key future research challenges and open problems for quantum internet design and deployment.
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When Entanglement Meets Classical Communications: Quantum Teleportation for the Quantum Internet

TL;DR: In this paper, the authors shed light on the quantum entanglement in the context of quantum teleportation and the challenges in the design and practical application of these functionalities, and acknowledge that quantum information is subject to the deleterious effects of quantum decoherence.
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Towards a distributed quantum computing ecosystem

TL;DR: This paper introduces the Quantum Internet as the fundamental underlying infrastructure of the Distributed Quantum Computing ecosystem and elaborates on a high-level system abstraction of thedistributed quantum Computing ecosystem, described through a set of logical layers.
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Correlation-Aware User Selection for Cooperative Spectrum Sensing in Cognitive Radio Ad Hoc Networks

TL;DR: A fully distributed user selection algorithm is developed by adaptively selecting uncorrelated cognitive radio users, which is able to account for dynamic changes in the network topology and in the channel conditions, and results reveal the benefits of adopting the proposed correlation-aware user selection for cooperative spectrum sensing.