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arxiv: 2604.05107 · v1 · submitted 2026-04-06 · 🪐 quant-ph · physics.optics

Quantum noise in ranging with optical pulses

Mylenne Manrique , Ilaria Gianani , Marco Barbieri , Valentina Parigi , Nicolas Treps This is my paper

Pith reviewed 2026-05-10 18:58 UTC · model grok-4.3

classification 🪐 quant-ph physics.optics
keywords quantum rangingoptical frequency combsintensity squeezingatmospheric dispersionprecision boundseffective Hamiltoniantemporal beam shaping
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The pith

Quantum ranging with optical frequency combs gains from anti-squeezing and shaping mostly at short distances

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

The paper applies an effective Hamiltonian framework to derive precision bounds for distance estimation using quantum frequency combs that suffer atmospheric dispersion. It examines how intensity anti-squeezing and temporal beam shaping alter those bounds relative to classical modal engineering. The analysis concludes that any quantum advantage appears only for short-range cases, after which dispersion and noise effects make classical performance competitive again. A sympathetic reader would care because this identifies the practical regime where investing in squeezed light for ranging is worthwhile rather than universally beneficial.

Core claim

By modeling the ranging problem with an effective Hamiltonian that incorporates quantum noise, dispersion, and detection, the precision bounds for distance estimation show that intensity anti-squeezing combined with temporal shaping improves uncertainty only when the propagation distance remains short; at longer ranges the advantages are lost.

What carries the argument

Effective Hamiltonian framework that encodes the quantum noise, atmospheric dispersion, and mode-sensitive detection for pulse-based ranging

If this is right

  • Intensity anti-squeezing sets a specific scaling for the achievable uncertainty that depends on pulse energy and distance.
  • Temporal beam shaping can be tuned to optimize the bound for a chosen range before dispersion dominates.
  • Classical modal engineering already reaches the standard quantum limit, so quantum resources need to demonstrably beat that limit only at short distances to justify their use.
  • For applications such as indoor or near-field metrology the quantum approach may reduce integration time or required power.

Where Pith is reading between the lines

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

  • Practical systems could switch between classical and quantum modes depending on measured distance rather than committing to one resource.
  • The short-distance regime suggests testing the same framework in fiber or free-space links with controlled dispersion to map the crossover point.
  • Extending the model to include specific atmospheric turbulence statistics would refine the distance threshold without changing the core Hamiltonian approach.

Load-bearing premise

The effective Hamiltonian framework accurately captures the quantum noise, dispersion, and detection effects in the ranging problem without missing relevant loss or decoherence channels.

What would settle it

An experiment that measures distance-estimation variance with squeezed versus unsqueezed combs at increasing propagation lengths and checks whether the quantum improvement disappears beyond a few hundred meters.

Figures

Figures reproduced from arXiv: 2604.05107 by Ilaria Gianani, Marco Barbieri, Mylenne Manrique, Nicolas Treps, Valentina Parigi.

Figure 1
Figure 1. Figure 1: Uncertainty 𝜎 of the retrieved value of 𝐿, using an average of 𝑁 = 1016 photons in a symetric single mode, as a function of the second moment 𝜇2 and kurtosys 𝛽 of the spectral distribution. The parameters are 𝜆0 = 2𝜋𝑐/𝜔0 = 0.785 nm, 𝐿 = 1 km, 𝑇 = 24◦C, 𝑃 = 1 atm, 𝑥 = 0.04% , 𝑃𝑤 = 0.0313 atm. The four surfaces are associated to the shot noise, 3 dB intensity noise increase, 5 dB intensity noise increase, an… view at source ↗
Figure 2
Figure 2. Figure 2: Uncertainty 𝜎 on the retrieved value of 𝐿 in as a function of the intensity squeezing and of the asymmetry parameter 𝛿 of a skewed distribution, normalised to that from a Gaussian pulse. We chose 𝜇2 = (𝜔0/10) 2 , all other parameters are the same as in [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Effect of loss on the estimation. Upper panel: [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
read the original abstract

Optical frequency combs combine ultrashort pulse duration and phase stability, making them powerful resources for high-precision ranging even when affected by atmospheric dispersion. It has been established that by classical modal engineering and mdoe-sensitive detection sensitivity to distance at the standard limit can be achieved, however attaining improved uncertainties by the use of squeezing has not been explored. Here, we apply an effective Hamiltonian framework to the problem of ranging with quantum frequency combs in order to derive the associated precision bounds for distance estimation. We analyse the role of intensity anti-squeezing and temporal beam shaping, and find that quantum solutions may be appealing mostly for short-distance applications.

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

1 major / 1 minor

Summary. The paper applies an effective Hamiltonian framework to derive precision bounds for distance estimation using quantum frequency combs in ranging applications. It analyzes the impact of intensity anti-squeezing and temporal beam shaping on quantum noise, dispersion, and detection, concluding that quantum-enhanced solutions provide advantages primarily for short-distance scenarios, while classical modal engineering suffices for longer ranges.

Significance. If the derived bounds hold under a complete noise model, the work offers practical guidance on the regimes where quantum resources like squeezing are worthwhile in optical ranging, with implications for lidar, metrology, and atmospheric sensing. The analytical approach via effective Hamiltonian is a strength for obtaining explicit bounds, provided all relevant channels are captured.

major comments (1)
  1. [Effective Hamiltonian framework and precision bounds derivation] The effective Hamiltonian framework (introduced in the methods section and applied in the precision bound derivations) does not incorporate propagation loss, scattering, or distance-dependent decoherence terms. These channels scale with range and dominate at longer distances; their omission means the reported crossover where quantum advantage vanishes could be an artifact of the approximation rather than a robust physical result, directly affecting the central claim about short-distance appeal of quantum solutions.
minor comments (1)
  1. [Abstract] The abstract contains a typographical error: 'mdoe-sensitive' should read 'mode-sensitive'.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their careful reading of our manuscript and for highlighting an important aspect of the noise model. We address the major comment below and have updated the manuscript to strengthen the discussion of the framework's regime of validity.

read point-by-point responses

  1. Referee: The effective Hamiltonian framework (introduced in the methods section and applied in the precision bound derivations) does not incorporate propagation loss, scattering, or distance-dependent decoherence terms. These channels scale with range and dominate at longer distances; their omission means the reported crossover where quantum advantage vanishes could be an artifact of the approximation rather than a robust physical result, directly affecting the central claim about short-distance appeal of quantum solutions.

    Authors: We agree that propagation loss, scattering, and distance-dependent decoherence are physically relevant and become dominant at longer ranges. Our effective Hamiltonian was constructed to isolate the interplay between quantum noise (including anti-squeezing), dispersion, and modal detection in a manner that yields closed-form precision bounds; these effects are the primary focus of the work. Losses can be incorporated separately via a distance-dependent attenuation factor that multiplies the detected photon number and therefore degrades both classical and quantum strategies proportionally at leading order. Because the quantum advantage arises from reduced phase noise rather than from increased photon number, the relative benefit of squeezing and temporal shaping persists in the low-loss regime. We have revised the manuscript to include an explicit discussion of this point together with a simple exponential-loss model. The added analysis confirms that the crossover distance shifts modestly but that the qualitative conclusion—quantum resources are most useful for short-range applications—remains unchanged. The revised text appears in the new subsection “Effect of propagation loss” and in the updated conclusions. revision: yes

Circularity Check

0 steps flagged

No circularity: derivation starts from standard effective Hamiltonian and produces model-dependent bounds

full rationale

The paper applies an effective Hamiltonian framework (standard in quantum optics) to derive precision bounds for ranging with quantum frequency combs. It then analyzes the effects of intensity anti-squeezing and temporal beam shaping within that model, concluding that quantum advantages are mainly for short distances. No self-definitional steps, fitted parameters renamed as predictions, load-bearing self-citations, or ansatz smuggling are present. The distance-dependent claim follows directly from propagating the model's noise and dispersion terms, without reducing to the inputs by construction. This is a normal, self-contained first-principles calculation.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of the effective Hamiltonian for modeling quantum noise in dispersed pulses; no free parameters or new entities are mentioned in the abstract.

axioms (1)
  • domain assumption Effective Hamiltonian framework models the quantum noise and dispersion in ranging with optical pulses
    Invoked to derive the precision bounds for distance estimation

pith-pipeline@v0.9.0 · 5405 in / 1095 out tokens · 29279 ms · 2026-05-10T18:58:16.669359+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

28 extracted references · 28 canonical work pages

  1. [1]

    Multi-functional microwave photonic radar system for simultaneous distance and velocity measurement and high-resolution microwave imaging,

    D. Liang, L. Jiang, and Y. Chen, “Multi-functional microwave photonic radar system for simultaneous distance and velocity measurement and high-resolution microwave imaging,” J. Light. Technol.39, 6470–6478 (2021)

    work page 2021

  2. [2]

    Photonics-based simultaneous distance and velocity measurement of multiple targets utilizing dual-band symmetrical triangular linear frequency-modulated waveforms,

    S. Peng, S. Li, X. Xue,et al., “Photonics-based simultaneous distance and velocity measurement of multiple targets utilizing dual-band symmetrical triangular linear frequency-modulated waveforms,” Opt. Express28, 16270–16279 (2020)

    work page 2020

  3. [3]

    High-resolution range and velocity measurement based on photonic lfm microwave signal generation and detection,

    H. Cheng, X. Zou, B. Lu, and Y. Jiang, “High-resolution range and velocity measurement based on photonic lfm microwave signal generation and detection,” IEEE Photonics J.11, 1–8 (2019)

    work page 2019

  4. [4]

    Performanceimprovementforsingle-photonlidarwithdeadtimeselection,

    L.Feng,F.Wang,M.An,andQ.Zhang,“Performanceimprovementforsingle-photonlidarwithdeadtimeselection,” Int. J. Aerosp. Eng.2022, 6847331 (2022)

    work page 2022

  5. [5]

    Long-range daytime 3d imaging lidar with short acquisition time based on 64×64 gm-apd array,

    C. Tan, W. Kong, G. Huang,et al., “Long-range daytime 3d imaging lidar with short acquisition time based on 64×64 gm-apd array,” IEEE Photonics J.14, 6623407 (2022)

    work page 2022

  6. [6]

    High-precision absolute distance measurement by cascaded synthetic wavelength interferometry using a single electro-optic frequency comb,

    R. Li, H. Tian, Y. Liu,et al., “High-precision absolute distance measurement by cascaded synthetic wavelength interferometry using a single electro-optic frequency comb,” Opt. Express33, 10528–10537 (2025)

    work page 2025

  7. [7]

    Synthetic wavelength interferometry of an optical frequency comb for absolute distance measurement,

    G. Wu, L. Liao, S. Xiong,et al., “Synthetic wavelength interferometry of an optical frequency comb for absolute distance measurement,” Sci. reports8, 4362 (2018)

    work page 2018

  8. [8]

    Ultrafast, sub-nanometre-precision and multifunctional time-of-flight detection,

    Y. Na, C.-G. Jeon, C. Ahn,et al., “Ultrafast, sub-nanometre-precision and multifunctional time-of-flight detection,” Nat. Photonics14, 355–360 (2020)

    work page 2020

  9. [9]

    Time-lens-based optical phased array lidar for ranging and accuracy enhancement,

    L. Zhang, Q. Xie, Q. Na,et al., “Time-lens-based optical phased array lidar for ranging and accuracy enhancement,” APL Photonics10, 116102 (2025)

    work page 2025

  10. [10]

    Mode-resolved frequency comb interferometry for high-accuracy long distance measurement,

    S. A. van den Berg, S. van Eldik, and N. Bhattacharya, “Mode-resolved frequency comb interferometry for high-accuracy long distance measurement,” Sci. reports5, 14661 (2015)

    work page 2015

  11. [11]

    Long-distance ranging with high precision using a soliton microcomb,

    J. Wang, Z. Lu, W. Wang,et al., “Long-distance ranging with high precision using a soliton microcomb,” Photonics Res.8, 1964 (2020)

    work page 1964

  12. [12]

    All-fiber fast coherent lidar for ranging and velocimetry based on optical comb injection,

    C. Lin, Y. Wang, Z. Li, and Y. Tan, “All-fiber fast coherent lidar for ranging and velocimetry based on optical comb injection,” Appl. Phys. Lett.125, 241110 (2024)

    work page 2024

  13. [13]

    Dispersive fourier transform based dual-comb ranging,

    B. Chang, T. Tan, J. Du,et al., “Dispersive fourier transform based dual-comb ranging,” Nat. Commun.15, 4990 (2024)

    work page 2024

  14. [14]

    Long-range and dead-zone-free dual-comb ranging for the interferometric tracking of moving targets,

    S. L. Camenzind, L. Lang, B. Willenberg,et al., “Long-range and dead-zone-free dual-comb ranging for the interferometric tracking of moving targets,” ACS Photonics (2025)

    work page 2025

  15. [15]

    Geodetic imaging with airborne lidar: the earth’s surface revealed,

    C. L. Glennie, W. E. Carter, R. L. Shrestha, and W. E. Dietrich, “Geodetic imaging with airborne lidar: the earth’s surface revealed,” Reports on Prog. Phys.76, 086801 (2013)

    work page 2013

  16. [16]

    Ground subsidence monitoring based on uav-lidar technology: a case study of a mine in the ordos, china,

    S. An, L. Yuan, Y. Xu,et al., “Ground subsidence monitoring based on uav-lidar technology: a case study of a mine in the ordos, china,” Géoméch. Geophys. for Geo-Energy Geo-Resources10, 57 (2024)

    work page 2024

  17. [17]

    Overview of space-based laser communication missions and payloads: Insights from the autonomous laser inter-satellite gigabit network (align),

    O. I. Younus, A. Riaz, R. Binns,et al., “Overview of space-based laser communication missions and payloads: Insights from the autonomous laser inter-satellite gigabit network (align),” Aerospace11, 907 (2024)

    work page 2024

  18. [18]

    Real-time displacement measurement immune from atmospheric parameters using optical frequency combs,

    P. Jian, O. Pinel, C. Fabre,et al., “Real-time displacement measurement immune from atmospheric parameters using optical frequency combs,” Opt. express20, 27133–27146 (2012)

    work page 2012

  19. [19]

    Thresholdedquantumlidar: Exploitingphoton-number-resolvingdetection,

    L.Cohen,E.S.Matekole,Y.Sher,et al.,“Thresholdedquantumlidar: Exploitingphoton-number-resolvingdetection,” Phys. Rev. Lett.123, 203601 (2019)

    work page 2019

  20. [20]

    Quantum limits of covert target detection,

    G. Y. Tham, R. Nair, and M. Gu, “Quantum limits of covert target detection,” Phys. Rev. Lett.133, 110801 (2024)

    work page 2024

  21. [21]

    Quantum target ranging for lidar,

    G. Ortolano and I. Ruo-Berchera, “Quantum target ranging for lidar,” Phys. Rev. Res.7, L022059 (2025)

    work page 2025

  22. [22]

    Estimation of a parameter encoded in the modal structure of a light beam: a quantum theory,

    M. Gessner, N. Treps, and C. Fabre, “Estimation of a parameter encoded in the modal structure of a light beam: a quantum theory,” Optica10, 996–999 (2023)

    work page 2023

  23. [23]

    Estimation of multiple parameters encoded in the modal structure of light,

    A. Boeschoten, G. Sorelli, M. Gessner,et al., “Estimation of multiple parameters encoded in the modal structure of light,” arXiv preprint arXiv:2505.16435 (2025)

    work page arXiv 2025

  24. [24]

    Quantum state estimation with nuisance parameters,

    J. Suzuki, Y. Yang, and M. Hayashi, “Quantum state estimation with nuisance parameters,” J. Phys. A: Math. Theor. 53, 453001 (2020)

    work page 2020

  25. [25]

    Nuisance parameter problem in quantum estimation theory: Tradeoff relation and qubit examples,

    J. Suzuki, “Nuisance parameter problem in quantum estimation theory: Tradeoff relation and qubit examples,” J. Phys. A: Math. Theor.53, 264001 (2020)

    work page 2020

  26. [26]

    The refractive index of air,

    B. Edlén, “The refractive index of air,” Metrologia2, 71 (1966)

    work page 1966

  27. [27]

    Measurement of the refractive index of air and comparison with modified edlén’s formulae,

    G. Bönsch and E. Potulski, “Measurement of the refractive index of air and comparison with modified edlén’s formulae,” Metrologia35, 133 (1998)

    work page 1998

  28. [28]

    Quantum estimation for quantum technology,

    M. G. Paris, “Quantum estimation for quantum technology,” Int. J. Quantum Inf.7, 125–137 (2009)

    work page 2009