Statistical properties and repetition rates for a quantum network with
geographical distribution of nodes
- URL: http://arxiv.org/abs/2312.09130v1
- Date: Thu, 14 Dec 2023 17:01:21 GMT
- Title: Statistical properties and repetition rates for a quantum network with
geographical distribution of nodes
- Authors: Rute Oliveira, Raabe Oliveira, Nadja K. Bernardes, Rafael Chaves
- Abstract summary: We build upon recent models for quantum networks based on optical fibers by considering the effect of a non-uniform distribution of nodes.
We employ it to compute the repetition rates for entanglement swapping, an essential protocol for quantum communication based on quantum repeaters.
- Score: 0.49157446832511503
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Steady technological advances and recent milestones such as intercontinental
quantum communication and the first implementation of medium-scale quantum
networks are paving the way for the establishment of the quantum internet, a
network of nodes interconnected by quantum channels. Here we build upon recent
models for quantum networks based on optical fibers by considering the effect
of a non-uniform distribution of nodes, more specifically based on the
demographic data of the federal states in Brazil. We not only compute the
statistical properties of this more realistic network, comparing its features
with previous models but also employ it to compute the repetition rates for
entanglement swapping, an essential protocol for quantum communication based on
quantum repeaters.
Related papers
- Quantum Backbone Networks for Hybrid Quantum Dataframe Transmission [0.26217304977339473]
We elaborate on the design that uses entanglement and quantum teleportation to build the quantum backbone between packetized quantum networks.
We design a network interface to interconnect packetized quantum networks with entanglement-based quantum backbone networks.
For feasibility, we analyze various system parameters via simulation to benchmark the performance of the overall network.
arXiv Detail & Related papers (2024-04-29T09:07:44Z) - Quantum Networks Enhanced by Distributed Quantum Memories [0.0]
We show that a network-wide synergistic usage of quantum memories distributed in a quantum communication network offers a fundamental advantage.
We first map the problem of quantum communication with local usage of memories into a classical continuum percolation model.
This improved mapping can be formulated in terms of graph-merging rules, analogous to the decimation rules of the renormalization group treatment of disordered quantum magnets.
arXiv Detail & Related papers (2024-03-25T02:16:25Z) - Guarantees on the structure of experimental quantum networks [105.13377158844727]
Quantum networks connect and supply a large number of nodes with multi-party quantum resources for secure communication, networked quantum computing and distributed sensing.
As these networks grow in size, certification tools will be required to answer questions regarding their properties.
We demonstrate a general method to guarantee that certain correlations cannot be generated in a given quantum network.
arXiv Detail & Related papers (2024-03-04T19:00:00Z) - Entanglement-Assisted Quantum Networks: Mechanics, Enabling
Technologies, Challenges, and Research Directions [66.27337498864556]
This paper presents a comprehensive survey of entanglement-assisted quantum networks.
It provides a detailed overview of the network structure, working principles, and development stages.
It also emphasizes open research directions, including architecture design, entanglement-based network issues, and standardization.
arXiv Detail & Related papers (2023-07-24T02:48:22Z) - QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional
Networks [124.7972093110732]
We propose quantum graph convolutional networks (QuanGCN), which learns the local message passing among nodes with the sequence of crossing-gate quantum operations.
To mitigate the inherent noises from modern quantum devices, we apply sparse constraint to sparsify the nodes' connections.
Our QuanGCN is functionally comparable or even superior than the classical algorithms on several benchmark graph datasets.
arXiv Detail & Related papers (2022-11-09T21:43:16Z) - Quantum Network Utility: A Framework for Benchmarking Quantum Networks [14.638996634412976]
We propose a general framework for quantifying the performance of a quantum network.
We define the quantum network utility metric $U_QN$ to capture the social and economic value of quantum networks.
arXiv Detail & Related papers (2022-10-19T17:50:11Z) - Packet Switching in Quantum Networks: A Path to Quantum Internet [0.0]
We introduce packet switching as a new paradigm for quantum data transmission in future and near-term quantum networks.
We propose a classical-quantum data frame structure and explore methods of frame generation and processing.
We present conceptual designs for a quantum reconfigurable optical add-drop multiplexer to realize the proposed transmission scheme.
arXiv Detail & Related papers (2022-05-16T08:39:05Z) - An Evolutionary Pathway for the Quantum Internet Relying on Secure
Classical Repeaters [64.48099252278821]
We conceive quantum networks using secure classical repeaters combined with the quantum secure direct communication principle.
In these networks, the ciphertext gleaned from a quantum-resistant algorithm is transmitted using QSDC along the nodes.
We have presented the first experimental demonstration of a secure classical repeater based hybrid quantum network.
arXiv Detail & Related papers (2022-02-08T03:24:06Z) - The Computational and Latency Advantage of Quantum Communication
Networks [70.01340727637825]
This article summarises the current status of classical communication networks.
It identifies some critical open research challenges that can only be solved by leveraging quantum technologies.
arXiv Detail & Related papers (2021-06-07T06:31:02Z) - Quantum Federated Learning with Quantum Data [87.49715898878858]
Quantum machine learning (QML) has emerged as a promising field that leans on the developments in quantum computing to explore large complex machine learning problems.
This paper proposes the first fully quantum federated learning framework that can operate over quantum data and, thus, share the learning of quantum circuit parameters in a decentralized manner.
arXiv Detail & Related papers (2021-05-30T12:19:27Z) - A Proactive Connection Setup Mechanism for Large Quantum Networks [0.0]
It is necessary to have an efficient mechanism to distribute entanglement among quantum network nodes.
This paper presents a novel way to quicken connection setup between two nodes using historical data.
Results show, with quantum network size increase, the proposed approach improves success rate of connection establishments.
arXiv Detail & Related papers (2020-12-25T11:48:40Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.