Satellite-based Quantum Information Networks: Use cases, Architecture,
and Roadmap
- URL: http://arxiv.org/abs/2202.01817v3
- Date: Tue, 17 Jan 2023 10:50:54 GMT
- Title: Satellite-based Quantum Information Networks: Use cases, Architecture,
and Roadmap
- Authors: Laurent de Forges de Parny (1), Olivier Alibart (2), Julien Debaud
(3), Sacha Gressani (3), Alek Lagarrigue (2,1,4), Anthony Martin (2),
Alexandre Metrat (3), Matteo Schiavon (5), Tess Troisi (2,1), Eleni Diamanti
(5), Patrick G\'elard (4), Erik Kerstel (3), S\'ebastien Tanzilli (2) and
Mathias Van Den Bossche (1) ((1) Thales Alenia Space, (2) Universit\'e C\^ote
d'Azur, (3) Universit\'e Grenoble Alpes, (4) Centre National d'Etudes
Spatiales, (5) Sorbonne Universit\'e)
- Abstract summary: Quantum Information Networks (QINs) enable connecting quantum devices over long distances.
This paper defines a high-level architecture of a generic QIN, before focusing on the architecture of the Space segment.
We detail the already concluded first step, the design and numerical simulation of a Space-to-ground entanglement distribution demonstrator.
- Score: 37.89976990030855
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Quantum Information Networks (QINs) attract increasing interest, as they
enable connecting quantum devices over long distances, thus greatly enhancing
their intrinsic computing, sensing, and security capabilities. The core
mechanism of a QIN is quantum state teleportation, consuming quantum
entanglement, which can be seen in this context as a new kind of network
resource. Here we identify use cases per activity sector, including key
performance targets, as a reference for the network requirements. We then
define a high-level architecture of a generic QIN, before focusing on the
architecture of the Space segment, with the aim of identifying the main design
drivers and critical elements. A survey of the state-of-the-art of these
critical elements is presented, as are issues related to standardisation.
Finally, we explain our roadmap to developing the first QINs and detail the
already concluded first step, the design and numerical simulation of a
Space-to-ground entanglement distribution demonstrator.
Related papers
- STQS: A Unified System Architecture for Spatial Temporal Quantum Sensing [13.365388879978264]
We present STQS, a unified system architecture for distributed quantum sensing.
By employing a comprehensive gate-based framework, we systemically explore the design space of quantum sensing schemes.
We introduce a novel distance-based metric that compares reference states to sensing states and assigns a confidence level.
arXiv Detail & Related papers (2025-02-25T02:13:13Z) - SeQUeNCe GUI: An Extensible User Interface for Discrete Event Quantum Network Simulations [55.2480439325792]
SeQUeNCe is an open source simulator of quantum network communication.
We implement a graphical user interface which maintains the core principles of SeQUeNCe.
arXiv Detail & Related papers (2025-01-15T19:36:09Z) - Quantum Data Center Infrastructures: A Scalable Architectural Design Perspective [0.6192426532704245]
This paper presents the design of scalable quantum networks that utilize optical switches to interconnect multiple quantum processors.
We aim to address the limitations of current quantum processors and explore the potential of quantum data centers.
arXiv Detail & Related papers (2025-01-09T22:12:33Z) - From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks [56.51893966016221]
Quantum Graph Neural Networks (QGNNs) represent a novel fusion of quantum computing and Graph Neural Networks (GNNs)
This paper critically reviews the state-of-the-art in QGNNs, exploring various architectures.
We discuss their applications across diverse fields such as high-energy physics, molecular chemistry, finance and earth sciences, highlighting the potential for quantum advantage.
arXiv Detail & Related papers (2024-08-12T22:53:14Z) - Quantum Key Distribution Routing Protocol in Quantum Networks: Overview and Challenges [3.533191491086764]
This paper explores the potential of utilizing established routing design techniques in the context of quantum key distribution.
The implementation of these techniques poses substantial challenges, including quantum memory decoherence, key rate generation, latency delays, inherent noise in quantum systems, limited communication ranges, and the necessity for highly specialized hardware.
arXiv Detail & Related papers (2024-07-18T04:46:32Z) - 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) - Reconfigurable Quantum Internet Service Provider [13.854695863568166]
We demonstrate the concept of quantum internet service provider (QISP)
We construct a reconfigurable QISP comprising both the quantum hardware and classical control software.
Our experiment demonstrates the robust capabilities of the QISP.
arXiv Detail & Related papers (2023-05-15T22:19:00Z) - Routing Protocols for Quantum Networks: Overview and Challenges [1.2891210250935143]
Quantum routing design requires a substantial deviation from conventional network design protocols.
Implementing these techniques poses significant challenges, such as decoherence and noise in quantum systems.
This paper summarizes the present state of quantum routing techniques, including their principles, protocols, and challenges.
arXiv Detail & Related papers (2023-05-01T08:15:55Z) - The Basis of Design Tools for Quantum Computing: Arrays, Decision
Diagrams, Tensor Networks, and ZX-Calculus [55.58528469973086]
Quantum computers promise to efficiently solve important problems classical computers never will.
A fully automated quantum software stack needs to be developed.
This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.
arXiv Detail & Related papers (2023-01-10T19:00:00Z) - 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) - Demonstration of teleportation across a quantum network code [0.0]
We study measurement-based quantum network coding (MQNC), which is a protocol particularly suitable for noisy intermediate-scale quantum devices.
In particular, we develop techniques to adapt MQNC to state-of-the-art superconducting processors and subsequently demonstrate successful teleportation of quantum information.
The teleportation in our demonstration is shown to occur with fidelity higher than could be achieved via classical means, made possible by considering qubits from a polar cap of the Bloch Sphere.
arXiv Detail & Related papers (2022-10-06T12:59:48Z) - Physics-Informed Quantum Communication Networks: A Vision Towards the
Quantum Internet [79.8886946157912]
We present a novel analysis of the performance of quantum communication networks (QCNs) in a physics-informed manner.
The need of the physics-informed approach is then assessed and its fundamental role in designing practical QCNs is analyzed.
We identify novel physics-informed performance metrics and controls that enable QCNs to leverage the state-of-the-art advancements in quantum technologies.
arXiv Detail & Related papers (2022-04-20T05:32:16Z) - Branching Quantum Convolutional Neural Networks [0.0]
Small-scale quantum computers are already showing potential gains in learning tasks on large quantum and very large classical data sets.
We present a generalization of QCNN, the branching quantum convolutional neural network, or bQCNN, with substantially higher expressibility.
arXiv Detail & Related papers (2020-12-28T19:00:03Z)
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.