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arxiv: 2511.12313 · v2 · submitted 2025-11-15 · 🪐 quant-ph · cs.CR

An Improved Quantum Anonymous Notification Protocol for Quantum-Augmented Networks

Nitin Jha , Abhishek Parakh , Mahadevan Subramaniam This is my paper

Pith reviewed 2026-05-17 21:40 UTC · model grok-4.3

classification 🪐 quant-ph cs.CR
keywords quantum anonymous notificationGHZ statesdephasing noisequantum-augmented networksrotation operationsfalse notificationsswitch-bypass handling
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The pith

Rotation operations on shared GHZ states yield an improved quantum anonymous notification protocol with stronger resilience to false notifications under dephasing noise.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper develops an improved quantum anonymous notification protocol for n-user quantum-augmented networks by applying rotation operations to shared GHZ states. This produces an anonymous alert that a receiver can use to prepare for incoming quantum communication without revealing identities. The authors examine the protocol under a dephasing noise model and report lower rates of false notifications than earlier QAN methods. They further outline integration with a machine-learning classifier and switch-bypass handling to limit header leakage and interference at network switches.

Core claim

The authors propose an improved quantum anonymous notification (QAN) protocol that utilizes rotation operations on shared GHZ states to produce an anonymous notification in an n-user quantum-augmented network. They study the behavior of this modified QAN protocol under the dephasing noise model and observe stronger resilience to false notifications than earlier QAN approaches. The QAN framework is also proposed to be integrated with a machine-learning classifier in an enhanced quantum-augmented network, and they discuss how this notification layer integrates with QuANets so that receivers can allow switch-bypass handling of quantum payloads, reducing header-based information leakage and vuln

What carries the argument

Rotation operations applied to shared GHZ states, which generate the anonymous notification signal while preserving anonymity and functionality in the presence of noise.

If this is right

  • The protocol supports anonymous notifications for any number of users in a quantum-augmented network.
  • It maintains lower false-notification rates than prior approaches when dephasing noise is present.
  • Integration with machine-learning classifiers can create enhanced quantum-augmented networks.
  • Switch-bypass handling of quantum payloads reduces header-based information leakage and targeted interference at compromised switches.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The noise tolerance may allow quantum notification layers to operate on existing or near-term network hardware without requiring error-corrected channels.
  • The same rotation technique could be combined with quantum secret sharing or voting primitives to build more complex anonymous services.
  • Small-scale laboratory tests on GHZ-state distribution under controlled dephasing could directly check the reported resilience gain.

Load-bearing premise

The dephasing noise model represents the dominant errors in the target quantum-augmented channels and the rotation operations preserve anonymity and notification functionality under that noise without additional unstated network assumptions.

What would settle it

An experiment that measures the rate of false notifications in the proposed protocol versus earlier QAN protocols when both are run over channels subject to the same dephasing noise strength and finds no improvement, or a demonstration that the rotations allow an eavesdropper to link sender and receiver identities.

Figures

Figures reproduced from arXiv: 2511.12313 by Abhishek Parakh, Mahadevan Subramaniam, Nitin Jha.

Figure 1
Figure 1. Figure 1: One vision of quantum augmented network, as presented in7 . The work presents the idea of using machine learning algorithms to selectively classify communication messages in “private” and “non-private” classes. This allows us to only use quantum encryption for private classes and save resources for non-private messages. In the diagram, the red arrow indicates the flow of private/quantum-encryption informat… view at source ↗
Figure 2
Figure 2. Figure 2: A schematic diagram representing different stages of the outlined QAN protocol. The diagram shows a network having n-users, A represents Alice, and all other nodes are marked Bi ∈ [1,n], as each of them is equally likely to be the receiver of the notification by Alice. Stage I is distributing the secret share of the angle α, and the GHZ state. Stage II represents each node holding a state, and waiting to p… view at source ↗
Figure 3
Figure 3. Figure 3: Simulation results for QAN protocol outlined in Sec[2] for detection probability of notification received for increasing number of runs for different values of Pz , i.e., probability of application of the rotation operator by the notifier for the receiver index [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The probability distribution of different states in the QAN protocol shows a uniform distribution. It, thus, preserves the anonymity of the notifier. Here, we plotted the probability distribution of various strings averaged over 1000 simulation runs. 3.2 Noise Integration To study the extent of the effectiveness of the protocol, we introduce depolarizing noise models and present the comparison of the false… view at source ↗
Figure 5
Figure 5. Figure 5: This figure shows the false positive rate of notification detection in the presence of noise models mentioned above for the modified QAN protocol proposed in this work, compared to the QAN presented by Khan et al.9 . The false positive rate is calculated as any notification detected by an unintended party, as a result of different noise models present in the network. presented in9 . Dephasing noise model i… view at source ↗
Figure 6
Figure 6. Figure 6: A schematic diagram of the combined protocol that integrates the QAN protocol into the idea of quantum augmented network presented in7 . The diagram is divided into two parts: (1) the part outlined in blue box outlines the protocol that’s executed before actual transmission, (2) the red arrows mark the transmission and encryption method. In the first half of the protocol, Alice gets a privacy label for her… view at source ↗
read the original abstract

The scalability of current quantum networks is limited due to noisy quantum components and high implementation costs, thereby limiting the security advantages that quantum networks provide over their classical counterparts. Quantum Augmented Networks (QuANets) address this by integrating quantum components in classical network infrastructure to improve robustness and end-to-end security. To enable such integration, Quantum Anonymous Notification (QAN) is a method to anonymously inform a receiver of an incoming quantum communication. Therefore, several quantum primitives will serve as core tools, namely, quantum voting, quantum anonymous protocols, quantum secret sharing, etc. However, all current quantum protocols can be compromised in the presence of several common channel noises. In this work, we propose an improved quantum anonymous notification (QAN) protocol that utilizes rotation operations on shared GHZ states to produce an anonymous notification in an n-user quantum-augmented network. We study the behavior of this modified QAN protocol under the dephasing noise model and observe stronger resilience to false notifications than earlier QAN approaches. The QAN framework is also proposed to be integrated with a machine-learning classifier, an enhanced quantum-augmented network. Finally, we discuss how this notification layer integrates with QuANets so that receivers can allow switch-bypass handling of quantum payloads, reducing header-based information leakage and vulnerability to targeted interference at compromised switches.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes an improved quantum anonymous notification (QAN) protocol for n-user quantum-augmented networks that applies rotation operations to shared GHZ states. It analyzes the protocol's behavior under a dephasing noise model and claims stronger resilience to false notifications than earlier QAN approaches. The work also outlines integration of the QAN layer with a machine-learning classifier and discusses its role in QuANets for reducing header leakage and switch-level interference.

Significance. If the resilience advantage is demonstrated with explicit probability calculations, the protocol could strengthen anonymous notification primitives in noisy quantum networks, supporting more practical QuANet deployments. The hybrid ML integration idea points toward adaptive error mitigation but remains conceptual.

major comments (2)
  1. [Abstract and §3] Abstract and §3 (Protocol Description): The central claim that rotation operations on GHZ states yield stronger resilience to false notifications under dephasing noise is not supported by any derivation of the erroneous-notification probability. No comparison is shown between the post-rotation noisy density matrix and the baseline QAN scheme for the same dephasing parameter p, leaving the quantitative advantage unestablished.
  2. [§4] §4 (Noise Analysis): The manuscript does not track how the rotation unitary interacts with the dephasing Kraus operators to affect the off-diagonal coherences that trigger false notifications. Without an explicit calculation of the notification decision threshold on the noisy state, it is impossible to verify that the false-positive rate is strictly lower while the anonymity set size remains n.
minor comments (2)
  1. [§3] Notation for the rotation angle and GHZ state preparation is introduced without a clear definition of the measurement operators used for notification.
  2. [§5] The ML-classifier integration is described at a high level; a diagram or pseudocode would clarify how classical post-processing interfaces with the quantum notification outcome.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback on our manuscript. The comments highlight the need for more explicit derivations to support our claims regarding resilience under dephasing noise. We address each point below and will revise the manuscript to incorporate the requested calculations and comparisons.

read point-by-point responses

  1. Referee: [Abstract and §3] The central claim that rotation operations on GHZ states yield stronger resilience to false notifications under dephasing noise is not supported by any derivation of the erroneous-notification probability. No comparison is shown between the post-rotation noisy density matrix and the baseline QAN scheme for the same dephasing parameter p, leaving the quantitative advantage unestablished.

    Authors: We acknowledge that the manuscript states the resilience observation but does not present the full derivation of the erroneous-notification probability or a direct quantitative comparison. In the revised version, we will add an explicit calculation of the false-notification probability for the proposed protocol. This will include the post-rotation noisy density matrix under the dephasing channel with parameter p, followed by a side-by-side comparison against the baseline QAN scheme for the same p values. The anonymity set size will remain fixed at n in all cases. revision: yes

  2. Referee: [§4] The manuscript does not track how the rotation unitary interacts with the dephasing Kraus operators to affect the off-diagonal coherences that trigger false notifications. Without an explicit calculation of the notification decision threshold on the noisy state, it is impossible to verify that the false-positive rate is strictly lower while the anonymity set size remains n.

    Authors: We agree that a detailed tracing of the rotation unitary's effect on the coherences is required. In the revised Section 4, we will derive the action of the rotation unitary on the GHZ state followed by the dephasing Kraus operators, showing the resulting off-diagonal terms. We will then specify the notification decision threshold on the noisy state and demonstrate that the false-positive rate is lower than in the baseline protocol while preserving the anonymity set size of n. revision: yes

Circularity Check

0 steps flagged

No circularity: protocol and noise analysis are self-contained

full rationale

The derivation consists of proposing rotation operations on shared GHZ states for anonymous notification, followed by direct analysis of the resulting state under an external dephasing noise model. The resilience observation is obtained by applying standard Kraus operators to the modified protocol state and comparing false-notification probabilities to prior schemes; this comparison uses the noise parameter p as an independent input rather than a fitted value derived from the protocol itself. No equations reduce a claimed prediction to a fitted parameter by construction, no uniqueness theorem is imported from self-citation, and the central claim does not rely on renaming or smuggling an ansatz. The protocol therefore remains independent of its own outputs.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard quantum-information assumptions about shared entangled states and channel noise; no free parameters or new entities are introduced in the abstract.

axioms (2)
  • domain assumption GHZ states can be securely shared and maintained among n users for the duration of the notification protocol
    Invoked to enable the rotation operations that produce the anonymous notification.
  • domain assumption The dephasing noise model captures the dominant error process affecting the protocol performance
    Used to evaluate and claim improved resilience to false notifications.

pith-pipeline@v0.9.0 · 5539 in / 1392 out tokens · 45625 ms · 2026-05-17T21:40:17.549471+00:00 · methodology

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Reference graph

Works this paper leans on

24 extracted references · 24 canonical work pages

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