Emergent Operational Entanglement Graphs and Sub-Quadratic Authentication Scaling in Realistic E91 Quantum Networks
- URL: http://arxiv.org/abs/2605.27434v1
- Date: Fri, 22 May 2026 10:17:31 GMT
- Title: Emergent Operational Entanglement Graphs and Sub-Quadratic Authentication Scaling in Realistic E91 Quantum Networks
- Abstract summary: We show that quantum communication networks operating under loss, decoherence, and LOCC constraints exhibit fundamentally different scaling laws.<n>Our results suggest that scalable authentication in quantum communication networks emerges directly from the physics of entanglement transport.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Large-scale entanglement-based quantum key distribution (QKD) networks are commonly assumed to require authentication resources scaling quadratically with the number of users. We show that realistic quantum communication networks operating under loss, decoherence, and LOCC constraints exhibit fundamentally different scaling laws. Using Pauli transfer matrix (PTM) transport, we demonstrate that Bell correlations decay exponentially along entanglement-swapping paths, generating finite operational correlation lengths and sparse operational entanglement graphs. In sparse metropolitan quantum networks, the number of CHSH-usable Bell pairs consequently scales linearly with network size, while authentication complexity scales as \[ Θ(N\log N), \] under sparse-mixing assumptions. We further present an ancilla-assisted distributed Bell-state verification framework for realistic E91 quantum metropolitan infrastructures. Our results suggest that scalable authentication in quantum communication networks emerges directly from the physics of entanglement transport.
Related papers
- Homomorphic Aggregation of Continuous-Variable GKP States [0.0]
Direct passive linear optics degrade non-Gaussian Gottesman-Kitaev-Preskill grid states.<n>We present an active, measurement-based continuous-variable network primitive for combining spatially distributed payloads.
arXiv Detail & Related papers (2026-08-13T13:30:11Z) - Asymptotic Limits of Entanglement Distribution [43.748379918040854]
We investigate the limits of entanglement distribution across quantum networks utilizing intermediate stations and local operations.<n>We establish a strict dichotomy: the preservation of entanglement over arbitrarily long distances is possible if the underlying quantum channel admits a correctable subspace.<n>We derive a fundamental lower bound on the physical resource requirements, proving that for channels without a correctable subspace, the number of parallel channels per link must scale at least logarithmically with the number of intermediate stations to sustain a non-zero amount of entanglement.
arXiv Detail & Related papers (2026-05-22T09:56:38Z) - Towards a Quantum-classical Augmented Network [0.0]
We propose a change in the structure of the HTTP protocol such that it can carry both quantum and classical payload.<n>We implement logistic regression, CNN, LSTM, and BiLSTM models to classify the privacy label for outgoing communications.
arXiv Detail & Related papers (2025-05-23T18:17:07Z) - A polychromatic continuous-variable quantum communication network enabled by optical frequency combs [10.521337944579757]
We report a polychromatic continuous-variable quantum communication network enabled by optical frequency combs.<n>Compared to other multiplexing techniques, polychromatic quantum networks can theoretically achieve a secret key rate without decreasing with the increase in users.
arXiv Detail & Related papers (2025-03-06T12:53:58Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [62.46800898243033]
Recent progress in quantum learning theory prompts a question: can linear properties of a large-qubit circuit be efficiently learned from measurement data generated by varying classical inputs?<n>We prove that the sample complexity scaling linearly in $d$ is required to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.<n>We propose a kernel-based method leveraging classical shadows and truncated trigonometric expansions, enabling a controllable trade-off between prediction accuracy and computational overhead.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Effects of Different Q-swaps Modes on Percolation Threshold in
Small-world Quantum Networks [2.228665992307317]
We show that Quantum Entanglement Percolation (QEP) has a better percolation performance than Classical Entanglement Percolation (CEP)
We also introduce quantum walk as a new scheme to have an extra reduction in the percolation threshold.
arXiv Detail & Related papers (2024-01-22T11:30:22Z) - 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) - 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) - Conference key agreement in a quantum network [67.410870290301]
Quantum conference key agreement (QCKA) allows multiple users to establish a secure key from a shared multi-partite entangled state.
In a quantum network, this protocol can be efficiently implemented using a single copy of a N-qubit Greenberger-Horne-Zeilinger (GHZ) state to distil a secure N-user conference key bit.
arXiv Detail & Related papers (2022-07-04T18:00:07Z) - Strong entanglement distribution of quantum networks [3.6720510088596297]
Large-scale quantum networks have been employed to overcome practical constraints of transmissions and storage for single entangled systems.
We show any connected network consisting of generalized EPR states and GHZ states satisfies strong CKW monogamy inequality in terms of bipartite entanglement measure.
We classify entangled quantum networks by distinguishing network configurations under local unitary operations.
arXiv Detail & Related papers (2021-09-27T08:45:18Z) - Quantum communication complexity beyond Bell nonlocality [87.70068711362255]
Efficient distributed computing offers a scalable strategy for solving resource-demanding tasks.
Quantum resources are well-suited to this task, offering clear strategies that can outperform classical counterparts.
We prove that a new class of communication complexity tasks can be associated to Bell-like inequalities.
arXiv Detail & Related papers (2021-06-11T18:00:09Z) - 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)
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.