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REVIEW 2 major objections 5 minor 62 references

Initial-state inhomogeneities can make waiting times between quantum jumps finite and independent of system size, resolving detector limits while the measurement-induced phase transition survives, at the cost of longer entanglement saturati

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T0 review · grok-4.5

2026-07-12 08:53 UTC pith:Z4UWQWHA

load-bearing objection Clean angular-momentum control of waiting times that fully kills the 1/N detector problem at heta=π, with MIPT survival; the only real softness is the authors’ own caveat on saturation-time asymptotics. the 2 major comments →

arxiv 2607.01332 v2 pith:Z4UWQWHA submitted 2026-07-01 quant-ph cond-mat.othercond-mat.stat-mech

Controlling Waiting Time Statistics in Monitored Collective Spins: Mitigating Detector's Resolution Barrier in Measurement-Induced Phase Transitions

classification quant-ph cond-mat.othercond-mat.stat-mech
keywords measurement-induced phase transitionsquantum trajectoriescollective spinswaiting timesdetector resolutionboundary time crystalpostselectionentanglement entropy
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.

Collective monitored spin systems already ease the post-selection problem because entanglement saturates only logarithmically with size, yet their jump rate grows with N, so finite detector resolution eventually merges many jumps into one bin and spoils pure-state trajectories. This paper shows that a controllable initial-state twist—two equal sub-ensembles rotated by an angle θ—suppresses the collective decay rate and therefore lengthens the average waiting time between jumps. For intermediate θ the waiting time still falls as 1/N but with a prefactor that can be orders of magnitude larger; when the ensembles are fully anti-aligned the waiting time remains finite and size-independent, fully removing the detector-resolution barrier. The measurement-induced phase transition itself persists, with area-law and sub-logarithmic entanglement regimes still visible. The practical price is that entanglement now takes longer to saturate, partially reintroducing a post-selection overhead. The result is an experimentally tunable trade-off between detector resolution and the number of trajectories one must post-select.

Core claim

By partitioning a collectively monitored spin ensemble into two subsystems rotated by an angle θ, the average waiting time between quantum jumps can be controlled: it still scales as 1/N for intermediate θ but with a strongly enhanced prefactor, and becomes finite and independent of N when θ=π. The measurement-induced phase transition survives the inhomogeneity, showing area-law entanglement in the stationary phase and sub-logarithmic growth inside the boundary time-crystalline phase. Detector-resolution mitigation is therefore achieved, yet entanglement saturation times lengthen beyond the logarithmic scaling of the homogeneous case, partially restoring a post-selection cost.

What carries the argument

An angular-momentum bound on the jump rate: total spin is conserved on average over trajectories, so the waiting time satisfies W ≳ N/(2κ⟨J²⟩), where the initial relative orientation θ of the two sub-ensembles sets ⟨J²⟩ and can cancel the leading O(N²) term when the ensembles are anti-aligned.

Load-bearing premise

The claim that longer saturation times partially reintroduce the post-selection barrier rests on finite-size trends (up to N≈80) that the authors themselves describe as inconclusive for the largest sizes.

What would settle it

Prepare anti-aligned (θ=π) and intermediate-θ ensembles of several hundred spins, record waiting times and entanglement saturation times under continuous monitoring; if waiting time stays O(1) while saturation time grows only logarithmically (or slower than any power of N), the stated trade-off is weaker than claimed.

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

If this is right

  • Detector temporal resolution no longer needs to improve with system size once the initial state is prepared anti-aligned.
  • The measurement-induced phase transition remains experimentally accessible with realistic finite-resolution detectors by tuning the initial-state angle.
  • Experiments must collect trajectories for longer times because entanglement saturates more slowly once inhomogeneity is present.
  • Intermediate angles give a continuous experimental dial between waiting-time gain and saturation-time cost.
  • Initial-state inhomogeneity itself becomes a route to highly entangled steady states without dark-state engineering.

Where Pith is reading between the lines

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

  • The same initial-state control of waiting times should transfer to other infinite-range monitored models whose jump operators scale with collective spin.
  • If larger-system data show that saturation time remains only polynomial, the residual post-selection overhead stays manageable for moderate experimental sizes.
  • Continuous drive or dissipation engineering might restore logarithmic saturation while preserving the waiting-time gain, eliminating the trade-off.
  • The logarithmic entanglement observed for all couplings when θ=π suggests anti-alignment effectively freezes the trajectory ensemble at a critical-like point.

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 / 5 minor

Summary. The manuscript studies a collectively driven and monitored spin ensemble that supports a boundary time-crystalline (BTC) phase, and shows that a controllable initial-state inhomogeneity—implemented by bipartitioning the ensemble into two Dicke subsystems rotated by an angle θ—can systematically increase the average waiting time W between quantum jumps. An angular-momentum bound (Eqs. 16–22) demonstrates that W scales as 1/N with a θ-dependent prefactor that grows by orders of magnitude, remaining finite and N-independent for the anti-aligned case θ=π, thereby fully mitigating the detector-resolution barrier. Numerical quantum-trajectory simulations (MCWF, 250 trajectories) corroborate the bound (Fig. 4). The measurement-induced phase transition survives under inhomogeneity, with area-law and sub-logarithmic entanglement regimes whose critical point tracks the mean-field stationary-to-BTC boundary (Figs. 2 and 5). The authors also report that the entanglement saturation time t* lengthens with θ (Fig. 6c), partially reintroducing a post-selection cost and establishing an experimental trade-off between detector resolution and post-selection overhead.

Significance. The work addresses a concrete experimental bottleneck for measurement-induced phases in collective systems: finite detector temporal resolution that forces coarse-graining of trajectories when W∼1/N. The angular-momentum lower bound on W is model-derived, parameter-free once θ is fixed, and cleanly separates the waiting-time control from the more delicate saturation-time issue. Survival of the MIPT under inhomogeneity, together with the explicit trade-off between resolution and post-selection, supplies a practical design principle for cold-atom or cavity-QED platforms that already realize collective spin models. The finite-size caveat on t* is already acknowledged by the authors and does not undermine the central waiting-time claim.

major comments (2)
  1. Sec. IV B and Fig. 6c: the claim that inhomogeneity “partially reintroduces the postselection barrier” rests on a finite-size trend of t* that the authors themselves describe as inconclusive for the largest accessible sizes (N≤80). A polynomial fit t*∼N^α_θ is offered, yet the largest-N points for θ=π/2 and 2π/3 visibly flatten. Either additional system sizes, an asymptotic argument (e.g., spin-wave or large-N rate equations), or a more cautious statement that the thermodynamic scaling of t* remains open is needed before the quantitative severity of the re-introduced barrier can be asserted.
  2. Eqs. 16–22 and the surrounding text: the lower bound W≳N/(2κ⟨J^{2}⟩) is derived from the trajectory-averaged jump rate and angular-momentum conservation. While the numerics of Fig. 4 confirm that the bound captures the correct N and θ dependence, the manuscript never quantifies how tight the bound remains at intermediate times or deep in the BTC phase (where ⟨J_z⟩ and ⟨J_z^{2}⟩ fluctuate). A short comparison of the instantaneous ⟨J+J-⟩ against the initial ⟨J^{2}⟩ would strengthen the analytic claim.
minor comments (5)
  1. Fig. 2 caption and Sec. II A: the numerical threshold “standard deviation exceeds 0.05” used to locate the mean-field critical point is arbitrary; a brief sensitivity check or an alternative criterion (e.g., long-time Fourier peak) would improve reproducibility.
  2. Sec. IV, numerical methods: the first-order MCWF integrator with κdt=0.01/N is stated without a convergence test against smaller steps or higher-order schemes; a short remark would reassure readers that the waiting-time statistics are free of integrator bias.
  3. Eq. (8) and surrounding text: the long-time average window T_avg and the choice of t0 after the transient are not specified numerically; stating the values used for the data in Figs. 5–6 would aid reproduction.
  4. Typographical: “T rajectories” and “ST A TE PREP ARA TION” in section headings contain spurious spaces; “Schrödinger” is occasionally rendered with an incorrect umlaut encoding.
  5. References [54] and [55] are cited as arXiv preprints; if published versions now exist they should be updated.

Circularity Check

0 steps flagged

No significant circularity: waiting-time bound and MIPT survival are derived from the model operators and direct numerics, not forced by definition or self-citation.

full rationale

The central analytical result is the lower bound on average waiting time W(t) ≳ N/(2κ ⟨J^{2}⟩_{t=0}) obtained from the angular-momentum identity ⟨J_{+}J_{-}⟩ ≤ ⟨J^{2}⟩ + ⟨J_z⟩ together with conservation of total spin sectors under the Lindbladian (Eqs. 16–22). Expanding ⟨J^{2}⟩ for the bipartition initial state of Eq. (15) immediately yields the explicit θ dependence, including the O(1) finite value at θ=π; this is a direct algebraic consequence of the jump operator and the prepared state, not a fit or a renamed input. The survival of the MIPT and the entanglement scalings are measured from quantum-trajectory averages (Figs. 5–6), not assumed. Self-citations to earlier BTC/MIPT works supply background phase-diagram context and the homogeneous-limit logarithmic saturation time, but none of them is invoked as a uniqueness theorem or load-bearing premise that forces the new θ-dependent waiting-time or trade-off claims. No parameters are fitted to one data subset and then “predicted” on a related subset; no ansatz is smuggled via citation. The only softness (finite-size saturation-time trend) is already flagged by the authors themselves and does not circularize the waiting-time result. The derivation chain is therefore self-contained against the paper’s own equations and numerics.

Axiom & Free-Parameter Ledger

4 free parameters · 4 axioms · 0 invented entities

The paper rests on standard open-quantum-system axioms (Lindblad master equation, quantum-jump unraveling, angular-momentum conservation) plus one modeling choice (bipartite rotation of two equal Dicke ensembles). No new particles or forces are introduced. Free parameters are ordinary control knobs ( heta, ω_{0}/κ) and two fitted scaling exponents that are reported but not load-bearing for the waiting-time claim.

free parameters (4)
  • inhomogeneity angle heta
    Continuous experimental control parameter that sets the initial relative orientation of the two sub-ensembles; not fitted to data.
  • drive-to-dissipation ratio ω_{0}/κ
    Standard control parameter of the model; scanned to map the phase diagram.
  • entanglement scaling exponent eta_ heta
    Fitted from steady-state S_{N/2} vs N curves in the BTC phase; used only for characterization, not for the waiting-time bound.
  • saturation-time exponent α_ heta
    Polynomial fit t* ~ N^{α_ heta} to finite-size data; authors note the fit is inconclusive at largest N.
axioms (4)
  • domain assumption Lindblad master equation with collective jump operator L = √(2κ/N) J_- generates the ensemble-averaged dynamics
    Standard quantum-optics description of a driven, collectively decaying atomic ensemble (Sec. II A).
  • standard math Total angular momentum J^{2} is conserved on average over trajectories, so the weight of each total-spin sector is fixed by the initial state
    Follows from [J^{2}, H] = [J^{2}, L] = 0; used to bound the jump rate (Sec. IV A).
  • domain assumption Quantum-jump (MCWF) unraveling correctly samples the pure-state trajectories whose entanglement is the MIPT diagnostic
    Standard unraveling of the Lindblad equation (Sec. II B).
  • ad hoc to paper Initial state is a product of two fully polarized Dicke states rotated by heta about x
    Modeling choice that introduces controllable inhomogeneity while preserving intra-subsystem permutation symmetry (Eq. 15, Sec. III).

pith-pipeline@v1.1.0-grok45 · 17263 in / 2849 out tokens · 29135 ms · 2026-07-12T08:53:21.902411+00:00 · methodology

0 comments
read the original abstract

In collective dissipative spin systems, the postselection barrier can be partially mitigated; however, a further obstacle may be posed by the finite temporal resolution of detectors. In this work, we investigate how initial-state inhomogeneities can control waiting-time statistics between quantum jumps, thereby mitigating the detector-resolution problem. We consider a collectively monitored spin model with a boundary time-crystalline phase, introducing inhomogeneity by partitioning the ensemble into two subsystems rotated by an angle $\theta$. We find that the measurement-induced phase transition survives under inhomogeneities, with different entanglement scaling regimes. The waiting time increases with $\theta$, scaling as $1/N$ but with a prefactor strongly enhanced by orders of magnitude, and in the anti-aligned limit $\theta = \pi$ it remains finite, fully resolving the resolution barrier. This mitigation, however, comes at a cost: the entanglement saturation time becomes significantly longer, partially reintroducing the postselection barrier. Our results highlight a trade-off between detector resolution and postselection overhead, with direct implications for the experimental observation of measurement-induced phenomena.

Figures

Figures reproduced from arXiv: 2607.01332 by Fernando Iemini, Tanbir Islam.

Figure 1
Figure 1. Figure 1: FIG. 1 [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Mean-field phase diagram of the collective spin [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Schematic representation of the inhomogeneous [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Indeed, homogeneous ensembles exhibit waiting times that vanish with system size, following an algebraic decay ∼ O(1/N). For intermediate angles 0 < θ < π, this algebraic decay persists, but with an overall multiplica￾tive factor that increases as the system approaches the anti-aligned configuration. In the extreme anti-aligned case, the waiting time remains finite in the large-N limit, thereby fully mitig… view at source ↗
Figure 5
Figure 5. Figure 5: FIG. 5. Steady-state entanglement entropy for the inhomo [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6 [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗

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Works this paper leans on

62 extracted references · 6 linked inside Pith

  1. [1]

    Fazio, J

    R. Fazio, J. Keeling, L. Mazza, and M. Schir` o, Many- body open quantum systems (2024), arXiv:2409.10300 [quant-ph]

  2. [2]

    Passarelli, X

    G. Passarelli, X. Turkeshi, A. Russomanno, P. Lucig- nano, M. Schir` o, and R. Fazio, Phys. Rev. Lett.132, 163401 (2024)

  3. [3]

    Y. Li, X. Chen, and M. P. A. Fisher, Phys. Rev. B98, 205136 (2018)

  4. [4]

    Skinner, J

    B. Skinner, J. Ruhman, and A. Nahum, Phys. Rev. X9, 031009 (2019)

  5. [5]

    H. J. Carmichael,Statistical Methods in Quantum Optics 1(Springer, 1999). 9

  6. [6]

    H. M. Wiseman and G. J. Milburn,Quantum Measure- ment and Control(Cambridge University Press, 2009)

  7. [7]

    Jacobs,Quantum Measurement Theory and its Appli- cations(Cambridge University Press, 2014)

    K. Jacobs,Quantum Measurement Theory and its Appli- cations(Cambridge University Press, 2014)

  8. [8]

    Y. Li, X. Chen, and M. P. A. Fisher, Phys. Rev. B100, 134306 (2019)

  9. [9]

    Szyniszewski, A

    M. Szyniszewski, A. Romito, and H. Schomerus, Phys. Rev. B100, 064204 (2019)

  10. [10]

    Jian, Y.-Z

    C.-M. Jian, Y.-Z. You, R. Vasseur, and A. W. W. Ludwig, Phys. Rev. B101, 104302 (2020)

  11. [11]

    Zabalo, M

    A. Zabalo, M. J. Gullans, J. H. Wilson, S. Gopalakrish- nan, D. A. Huse, and J. H. Pixley, Phys. Rev. B101, 060301 (2020)

  12. [12]

    Szyniszewski, A

    M. Szyniszewski, A. Romito, and H. Schomerus, Phys. Rev. Lett.125, 210602 (2020)

  13. [13]

    Turkeshi, R

    X. Turkeshi, R. Fazio, and M. Dalmonte, Phys. Rev. B 102, 014315 (2020)

  14. [14]

    O. Lunt, M. Szyniszewski, and A. Pal, Phys. Rev. B104, 155111 (2021)

  15. [15]

    Sierant, M

    P. Sierant, M. Schir` o, M. Lewenstein, and X. Turkeshi, Phys. Rev. B106, 214316 (2022)

  16. [16]

    Nahum, S

    A. Nahum, S. Roy, B. Skinner, and J. Ruhman, PRX Quantum2, 010352 (2021)

  17. [17]

    Zabalo, M

    A. Zabalo, M. J. Gullans, J. H. Wilson, R. Vasseur, A. W. W. Ludwig, S. Gopalakrishnan, D. A. Huse, and J. H. Pixley, Phys. Rev. Lett.128, 050602 (2022)

  18. [18]

    Sierant and X

    P. Sierant and X. Turkeshi, Phys. Rev. Lett.128, 130605 (2022)

  19. [19]

    Chiriaco, M

    G. Chiriaco, M. Tsitsishvili, D. Poletti, R. Fazio, and M. Dalmonte, Phys. Rev. B108, 075151 (2023)

  20. [20]

    Klocke and M

    K. Klocke and M. Buchhold, Phys. Rev. X13, 041028 (2023)

  21. [21]

    X. Cao, A. Tilloy, and A. De Luca, SciPost Phys.7, 024 (2019)

  22. [22]

    Nahum and B

    A. Nahum and B. Skinner, Phys. Rev. Research2, 023288 (2020)

  23. [23]

    Buchhold, Y

    M. Buchhold, Y. Minoguchi, A. Altland, and S. Diehl, Phys. Rev. X11, 041004 (2021)

  24. [24]

    C.-M. Jian, B. Bauer, A. Keselman, and A. W. W. Lud- wig, Phys. Rev. B106, 134206 (2022)

  25. [25]

    Coppola, E

    M. Coppola, E. Tirrito, D. Karevski, and M. Collura, Phys. Rev. B105, 094303 (2022)

  26. [26]

    M. Fava, L. Piroli, T. Swann, D. Bernard, and A. Nahum, Phys. Rev. X13, 041045 (2023)

  27. [27]

    Poboiko, P

    I. Poboiko, P. P¨ opperl, I. V. Gornyi, and A. D. Mirlin, Phys. Rev. X13, 041046 (2023)

  28. [28]

    Merritt and L

    J. Merritt and L. Fidkowski, Phys. Rev. B107, 064303 (2023)

  29. [29]

    Alberton, M

    O. Alberton, M. Buchhold, and S. Diehl, Phys. Rev. Lett. 126, 170602 (2021)

  30. [30]

    Turkeshi, A

    X. Turkeshi, A. Biella, R. Fazio, M. Dalmonte, and M. Schir´ o, Phys. Rev. B103, 224210 (2021)

  31. [31]

    Turkeshi, M

    X. Turkeshi, M. Dalmonte, R. Fazio, and M. Schir´ o, Phys. Rev. B105, L241114 (2022)

  32. [32]

    Piccitto, A

    G. Piccitto, A. Russomanno, and D. Rossini, Phys. Rev. B105, 064305 (2022)

  33. [33]

    Piccitto, A

    G. Piccitto, A. Russomanno, and D. Rossini, SciPost Phys. Core6, 078 (2023)

  34. [34]

    Tirrito, A

    E. Tirrito, A. Santini, R. Fazio, and M. Collura, SciPost Phys.15, 096 (2023)

  35. [35]

    Paviglianiti and A

    A. Paviglianiti and A. Silva, Phys. Rev. B108, 184302 (2023)

  36. [36]

    Rossini and E

    D. Rossini and E. Vicari, Phys. Rev. B102, 035119 (2020)

  37. [37]

    Tang and W

    Q. Tang and W. Zhu, Phys. Rev. Research2, 013022 (2020)

  38. [38]

    Fuji and Y

    Y. Fuji and Y. Ashida, Phys. Rev. B102, 054302 (2020)

  39. [39]

    Sierant, G

    P. Sierant, G. Chiriac` o, F. M. Surace, S. Sharma, X. Turkeshi, M. Dalmonte, R. Fazio, and G. Pagano, Quantum6, 638 (2022)

  40. [40]

    E. V. H. Doggen, Y. Gefen, I. V. Gornyi, A. D. Mir- lin, and D. G. Polyakov, Phys. Rev. Research4, 023146 (2022)

  41. [41]

    Altland, M

    A. Altland, M. Buchhold, S. Diehl, and T. Micklitz, Phys. Rev. Research4, L022066 (2022)

  42. [42]

    C. Noel, P. Niroula, D. Zhu, A. Risinger, L. Egan,et al., Nat. Phys.18, 760 (2022)

  43. [43]

    J. M. Koh, S.-N. Sun, M. Motta, and A. J. Minnich, Nat. Phys.19, 1314 (2023)

  44. [44]

    C. Y. Leung, D. Meidan, and A. Romito, Theory of free fermions dynamics under partial post-selected monitor- ing (2023), arXiv:2312.14022 [quant-ph]

  45. [45]

    S. J. Garratt and E. Altman, PRX Quantum5, 10.1103/prxquantum.5.030311 (2024)

  46. [46]

    Google Quantum AI and Collaborators, Nature622, 481 (2023)

  47. [47]

    Y. Li, Y. Zou, P. Glorioso, E. Altman, and M. P. A. Fisher, Phys. Rev. Lett.130, 220404 (2023)

  48. [48]

    Li and M

    Y. Li and M. P. A. Fisher, Phys. Rev. B108, 214302 (2023)

  49. [49]

    S. J. Garratt and E. Altman, Probing postmea- surement entanglement without post-selection (2023), arXiv:2305.20092 [quant-ph]

  50. [50]

    M. J. Gullans and D. A. Huse, Phys. Rev. Lett.125, 070606 (2020)

  51. [51]

    Ippoliti and V

    M. Ippoliti and V. Khemani, Phys. Rev. Lett.126, 060501 (2021)

  52. [52]

    Iadecola, S

    T. Iadecola, S. Ganeshan, J. H. Pixley, and J. H. Wilson, Phys. Rev. Lett.131, 060403 (2023)

  53. [53]

    Buchhold, T

    M. Buchhold, T. M¨ uller, and S. Diehl, Revealing measurement-induced phase transitions by pre-selection (2022), arXiv:2208.10506 [quant-ph]

  54. [54]

    Delmonte, Z

    A. Delmonte, Z. Li, G. Passarelli, E. Y. Song, D. Bar- berena, A. M. Rey, and R. Fazio, Measurement-induced phase transitions in monitored infinite-range interacting systems (2024), arXiv:2410.05394 [quant-ph]

  55. [55]

    Z. Li, A. Delmonte, X. Turkeshi, and R. Fazio, Mon- itored long-range interacting systems: Spin-wave the- ory for quantum trajectories (2024), arXiv:2405.12124 [quant-ph]

  56. [56]

    Iemini, A

    F. Iemini, A. Russomanno, J. Keeling, M. Schir` o, M. Dal- monte, and R. Fazio, Phys. Rev. Lett.121, 035301 (2018)

  57. [57]

    Iemini, D

    F. Iemini, D. Chang, and J. Marino, Physical Review A 109, 10.1103/physreva.109.032204 (2024)

  58. [58]

    M. B. Plenio and P. L. Knight, Rev. Mod. Phys.70, 101 (1998)

  59. [59]

    A. J. Daley, Advances in Physics63, 77 (2014)

  60. [60]

    Mattes, I

    R. Mattes, I. Lesanovsky, and F. Carollo, Phys. Rev. A 108, 062216 (2023)

  61. [61]

    L. d. S. Souza, L. F. dos Prazeres, and F. Iemini, Phys. Rev. Lett.130, 180401 (2023)

  62. [62]

    Kraus, H

    B. Kraus, H. P. B¨ uchler, S. Diehl, A. Kantian, A. Micheli, and P. Zoller, Phys. Rev. A78, 042307 (2008)