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REVIEW 2 major objections 1 minor 1 cited by

Quantum fingerprints using coherent states transmit less information than any classical protocol to compute Euclidean distance on vectors of size 10^8.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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T0 review · grok-4.3

2026-06-28 21:47 UTC pith:TBUCKSCN

load-bearing objection This is a solid experimental implementation of known quantum fingerprinting for Euclidean distance at 10^8 scale, but the abstract leaves the key error-vs-classical-bound comparison unshown. the 2 major comments →

arxiv 2605.31516 v1 pith:TBUCKSCN submitted 2026-05-29 quant-ph

Experimental demonstration of quantum advantage in communication complexity for Euclidean distance problem

Verena Yacoub , Niraj Kumar , Iordanis Kerenidis , Eleni Diamanti This is my paper
classification quant-ph
keywords quantum fingerprintingcommunication complexityEuclidean distancecoherent statessimultaneous message passingsuperconducting nanowire detectorsquantum advantage
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper shows that two parties can estimate the Euclidean distance between their vectors by sending short quantum messages to a referee, and that the total information sent is smaller than the minimum required by any classical protocol once the vectors reach length 10^8. The implementation replaces ideal entangled qubits with trains of amplitude-modulated coherent-state pulses that can be generated and detected with existing technology. The advantage is verified on multiple data types, including actual grayscale image pixels, while keeping error rates and precision within stated bounds.

Core claim

In the simultaneous-message-passing model, the quantum fingerprinting protocol encodes each vector as a sequence of coherent-state pulses whose overlap statistics at the referee yield an estimate of the squared Euclidean distance; the experiment records a transmitted information volume below the classical lower bound for input dimension 10^8 across several data sets.

What carries the argument

Quantum fingerprinting protocol that maps each real-valued vector to a train of amplitude-modulated coherent pulses, allowing the referee to extract distance information from photon-arrival statistics.

Load-bearing premise

The measured photon statistics and losses in the laboratory setup match the theoretical model closely enough that no hidden classical side channel or excess noise erases the reported gap over the optimal classical protocol.

What would settle it

A direct comparison in which the classical lower bound on transmitted bits (for the observed error rate) is calculated from the same input distribution and shown to be smaller than the number of pulses actually sent in the quantum run.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • The same coherent-state encoding works for non-binary data sets including real grayscale images.
  • The quantum advantage appears at input sizes already relevant to image-processing tasks.
  • Precision and error remain acceptable without requiring entangled multi-qubit states.

Where Pith is reading between the lines

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

  • The same pulse-train technique could be applied to other vector inner-product or distance tasks that admit fingerprinting reductions.
  • Integration with existing fiber links would test whether the advantage survives realistic channel loss.
  • Scaling the number of pulses while keeping the mean photon number low would further reduce the classical communication floor.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 1 minor

Summary. The manuscript reports a proof-of-principle optical experiment implementing a quantum fingerprinting protocol in the simultaneous message passing model to compute the Euclidean distance between two real-valued vectors. Amplitude-modulated coherent-state pulse trains and superconducting nanowire single-photon detectors are used to encode and detect fingerprints for input sizes up to 10^8, including grayscale-image data sets. The authors claim that the measured transmitted information and error rates demonstrate an exponential quantum advantage over the optimal classical protocol while remaining within acceptable error bounds.

Significance. If the experimental error rates and communication costs are shown to lie strictly below the classical bound after all losses and imperfections, the result would constitute the first laboratory demonstration of exponential quantum advantage in communication complexity for a concrete, application-relevant task. It replaces idealized qubit fingerprints with practical coherent-state resources and thereby moves the field from asymptotic theory toward feasible optical implementations.

major comments (2)
  1. [Abstract / Results] Abstract and Results section: the central claim that the realized protocol 'surpasses the best classical protocol for an input size of 10^8' with 'reasonable precision and error bounds' is load-bearing, yet the text provides no explicit numerical comparison of the measured error probability against the theoretical threshold required to preserve the quantum advantage, nor a breakdown of how the classical communication bound was computed for the identical data sets (including the grayscale images).
  2. [Methods] Methods / Experimental setup: the manuscript must quantify all sources of loss, detector inefficiency, modulation imperfection, and any classical side-information that could increase the effective communication cost; without these numbers it is impossible to confirm that the reported advantage survives the actual experimental imperfections.
minor comments (1)
  1. Notation for the Euclidean distance and fingerprint length should be introduced once and used consistently; the transition from vector dimension n = 10^8 to the number of coherent-state pulses is not immediately clear.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments. We address each major point below and have revised the manuscript to strengthen the presentation of the central claims.

read point-by-point responses

  1. Referee: [Abstract / Results] Abstract and Results section: the central claim that the realized protocol 'surpasses the best classical protocol for an input size of 10^8' with 'reasonable precision and error bounds' is load-bearing, yet the text provides no explicit numerical comparison of the measured error probability against the theoretical threshold required to preserve the quantum advantage, nor a breakdown of how the classical communication bound was computed for the identical data sets (including the grayscale images).

    Authors: We agree that an explicit numerical comparison strengthens the claim. The revised manuscript adds a table in the Results section that reports the measured error probabilities for each data set (synthetic and grayscale) alongside the theoretical threshold required to preserve the quantum advantage. We have also added an appendix with the explicit calculation of the classical communication bound for the identical input vectors, using the known optimal classical protocol in the simultaneous-message-passing model. revision: yes

  2. Referee: [Methods] Methods / Experimental setup: the manuscript must quantify all sources of loss, detector inefficiency, modulation imperfection, and any classical side-information that could increase the effective communication cost; without these numbers it is impossible to confirm that the reported advantage survives the actual experimental imperfections.

    Authors: We agree that a full accounting of imperfections is required. The revised Methods section now includes measured values for all relevant loss channels (fiber transmission, coupling, detector efficiency), modulation fidelity, and any classical overhead, together with a short propagation-of-error analysis showing that the reported communication cost and error rate remain below the classical bound after these effects. revision: yes

Circularity Check

0 steps flagged

No significant circularity; experimental comparison to external classical bound

full rationale

The paper reports an experimental implementation of a quantum fingerprinting protocol for Euclidean distance in the simultaneous message passing model, using amplitude-modulated coherent states and SNSPDs. The claimed advantage is obtained by direct measurement of transmitted information and error rates, then comparison against the optimal classical communication bound taken from prior communication complexity theory. No load-bearing step reduces by definition or by fitting to the experimental outputs themselves; the classical bound is independent and externally derived. The provided text contains no self-definitional equations, fitted-input predictions, or self-citation chains that substitute for the central experimental claim.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Review performed on abstract only; no explicit free parameters, invented entities, or non-standard axioms are identifiable from the provided text. The protocol implicitly relies on standard quantum optics assumptions about coherent states.

axioms (1)
  • domain assumption Coherent states can be used to generate fingerprints whose overlap statistics match the theoretical quantum fingerprinting protocol for Euclidean distance.
    The experimental implementation replaces ideal qubits with coherent-state pulses; this assumption is required for the advantage claim.

pith-pipeline@v0.9.1-grok · 5774 in / 1253 out tokens · 28523 ms · 2026-06-28T21:47:36.865791+00:00 · methodology

0 comments
read the original abstract

When considering the complexity of communication protocols, the aim is to perform a certain task with the minimum amount of communication resources, such as time and transmitted information. The use of quantum states may lead to an exponential advantage in the use of such resources. Here, we are interested in the task of calculating the Euclidean distance between two vectors representing real data sets. It has been previously shown that it is possible to obtain an advantage for this task based on quantum fingerprinting. This protocol is defined in the simultaneous message passing model of communication complexity, where the two parties do not communicate with each other but send data to a third party, and exploits practical fingerprints generated using trains of coherent state pulses instead of highly entangled qubit states that are hard to generate for large input sizes needed to demonstrate an exponential advantage. We perform a proof-of-principle experimental demonstration of the Euclidean distance protocol using amplitude modulation techniques for encoding non-binary data sets and high-performance superconducting nanowire single-photon detectors required to increase the accessible input size. We show a quantum advantage in transmitted information surpassing the best classical protocol for an input size of $10^8$, for diverse types of data sets, including those corresponding to real grayscale images, and with reasonable precision and error bounds. Our results highlight the potential of quantum communication complexity for use in a broad set of applications.

Figures

Figures reproduced from arXiv: 2605.31516 by Eleni Diamanti, Iordanis Kerenidis, Niraj Kumar, Verena Yacoub.

Figure 1
Figure 1. Figure 1: FIG. 1: General scheme of the Euclidean distance [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2: Log-log plot of the transmitted information as a [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3: Experimental setup for the implementation of the Euclidean distance protocol. [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4: Grayscale images used as Alice’s (upper row) [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5: Distributions of the estimated Euclidean [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗

discussion (0)

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Forward citations

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