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When proofreading improves both speed and accuracy

T0 review · 0 major / 3 minor · reviewed 2026-06-27 · grok-4.3

Pith's one-line read Proofreading improves both speed and accuracy when fluctuations in stall durations exceed a threshold set by the error rate.

desk verdict The paper derives a CV threshold on stall times that lets proofreading improve both speed and accuracy in a non-Markovian renewal setup. read the letter →

arxiv 2606.12795 v1 pith:KGDCHFQY submitted 2026-06-11 cond-mat.stat-mech physics.bio-ph

classification cond-mat.stat-mechphysics.bio-ph
keywords proofreadingspeed-accuracytrade-offstall-timefluctuationsnon-Markovianrenewalkineticnonequilibriumprocessesself-assemblypolymerreplication
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper establishes that the usual speed-accuracy trade-off in proofreading can be reversed in stochastic processes that include long-lived stalled states. It derives exact expressions for error rate and completion time using a non-Markovian renewal framework that handles arbitrary stall-time distributions. The central result is that fluctuations, quantified by the coefficient of variation of stall times, rather than the mean stall duration, control whether proofreading simultaneously reduces errors and shortens completion time. In the strong-stalling limit this reversal occurs once the coefficient of variation surpasses a value fixed by the intrinsic error rate. Readers care because the criterion applies directly to polymer replication, self-assembly, and immune recognition, offering a general condition for efficient nonequilibrium information processing.

What carries the argument

A non-Markovian renewal framework that computes error rate and completion time for arbitrary stall-time distributions in the presence of proofreading.

What would settle it

Measure error rate and mean completion time in a controlled system while varying the coefficient of variation of stall durations across the predicted threshold; both quantities should improve together with proofreading only above the threshold.

Watch

Extended reading notes

Core claim

In stochastic processes with long-lived stalled states, proofreading can increase both speed and accuracy when the coefficient of variation of the stall-time distribution exceeds a threshold determined by the intrinsic error rate; this follows from exact expressions for error rate and completion time obtained via a non-Markovian renewal framework that accommodates arbitrary stall-time distributions.

Load-bearing premise

The analysis requires that long-lived stalled states exist and that their durations can be treated as independent draws from a fixed but arbitrary distribution within a renewal process.

Editorial extensions

If this is right

  • Proofreading simultaneously raises accuracy and lowers completion time once stall-time fluctuations exceed the error-rate threshold.
  • The reversal holds in the strong-stalling limit for any stall-time distribution whose coefficient of variation is large enough.
  • The same criterion supplies a general test for whether proofreading is beneficial in self-assembly, polymer replication, and immune recognition.
  • Fluctuations in stall duration, not their average length, set the boundary between the usual trade-off and the improved regime.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Systems could be engineered to tune stall-time variability deliberately in order to enter the improved regime.
  • The result may extend to other kinetic-proofreading contexts where stall durations are known to be broadly distributed.
  • Experimental tests could fix the mean stall time and sweep only its variance to isolate the fluctuation effect.
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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

0 major / 3 minor

Summary. The paper claims that in stochastic processes featuring long-lived stalled states, proofreading can simultaneously improve both speed and accuracy, reversing the conventional trade-off. Employing a non-Markovian renewal framework, the authors derive exact expressions for the error rate and mean completion time that hold for arbitrary stall-time distributions. The central result is that, in the strong-stalling limit, this beneficial regime occurs when the coefficient of variation of the stall-time distribution exceeds a threshold determined by the intrinsic error rate; fluctuations, rather than the mean stall duration alone, control the outcome.

Significance. If the derivations hold, the work supplies a general, distribution-independent criterion for when proofreading is advantageous, with direct applicability to self-assembly, polymer replication, immune recognition, and other nonequilibrium information-processing systems. The explicit use of renewal theory for arbitrary distributions, the parameter-free character of the CV threshold, and the falsifiable prediction that sufficiently large stall-time fluctuations enable simultaneous gains in speed and accuracy are notable strengths.

minor comments (3)
  1. [§2.2] §2.2: the transition from the general renewal expression (Eq. 7) to the strong-stalling limit (Eq. 12) would benefit from an explicit statement of the order of the neglected terms for non-exponential distributions.
  2. [Figure 3] Figure 3: the caption does not indicate whether the plotted curves are obtained from the exact renewal formula or from numerical simulation of the underlying process.
  3. The notation for the stall-time density and its moments is introduced without a dedicated symbol table; a short table in §2 would improve readability for readers outside the renewal-theory community.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive assessment of our work and the recommendation for minor revision. The report lists no specific major comments, so we have no points requiring detailed rebuttal. We will address any minor issues identified during the revision process.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity; derivation self-contained from renewal theory

full rationale

The paper claims exact expressions for error rate and completion time derived via non-Markovian renewal theory applied to arbitrary stall-time distributions, with the CV threshold emerging in the strong-stalling limit as a consequence of that general framework. No quoted step reduces a prediction to a fitted input by construction, invokes a self-citation as load-bearing uniqueness theorem, or renames a known result. The derivation is presented as independent of the target regime and benchmarked externally, satisfying the criteria for a non-circular result.

Assumptions & free parameters 0 free parameters · 2 assumptions · 0 invented entities

The central claim rests on the existence of long-lived stalled states and the validity of the non-Markovian renewal framework for arbitrary distributions; no free parameters or invented entities are mentioned in the abstract.

assumptions (2)
  • domain assumption Long-lived stalled states exist in the stochastic process
    Invoked to define the regime where proofreading can reverse the trade-off.
  • domain assumption Non-Markovian renewal framework applies to arbitrary stall-time distributions
    Used to derive exact expressions for error rate and completion time.

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Cite this review

Pith. "Pith review of When proofreading improves both speed and accuracy." pith.science (2026). https://pith.science/paper/KGDCHFQY

@misc{pith2026260612795,
  author       = {Pith},
  title        = {Pith review of: When proofreading improves both speed and accuracy},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KGDCHFQY}},
  note         = {Machine review of arXiv:2606.12795}
}
read the original abstract

Proofreading is generally thought to improve accuracy at the expense of speed. We show that this trade-off can be reversed in stochastic processes with long-lived stalled states. Using a non-Markovian renewal framework, we derive exact expressions for the error rate and completion time under proofreading for arbitrary stall-time distributions. Our analysis reveals that fluctuations in stall durations, rather than their mean alone, determine whether proofreading can simultaneously increase speed and accuracy. In the limit of strong stalling, this regime emerges when the coefficient of variation of the stall time exceeds a threshold set by the intrinsic error rate. These results provide a general criterion for proofreading in systems ranging from self-assembly and polymer replication to immune recognition and other nonequilibrium information-processing systems.

Figures

Figures reproduced from arXiv: 2606.12795 by the authors.

Figure 1
Figure 1. FIG. 1 [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2 [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3 [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: FIG. 4 [PITH_FULL_IMAGE:figures/full_fig_p006_4.png]

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Reference graph

Works this paper leans on

45 extracted references · 1 canonical work pages

  1. [1]

    more accurate is faster

    ) ⟨Tec⟩ ≈ ⟨T⟩+ ∂⟨Tec⟩ ∂kex kex=0 kex +O(k 2 ex),(9) where⟨T⟩=µ⟨T s⟩+ (1−µ)⟨T f ⟩is the MFPT without error-correction. For MFPT to reduce with proofread- ing we must have ∂⟨Tec⟩ ∂kex kex=0 <0 which leads to the condition (see Sec. S5 [29]) CV 2 s +a 2pµCV 2 f >2 ⟨Ton⟩ ⟨Ts⟩ (1 +ap µ) + 2 1 +p µ (1 +ap µ)2 −a 2pµ −1, (10) wherea= ⟨Tf ⟩ ⟨Ts⟩ and the coefficie...

  2. [2]

    T. A. Kunkel and D. A. Erie, Annu. Rev. Biochem.74, 681 (2005)

  3. [3]

    J. M. Poulton, P. R. Ten Wolde, and T. E. Ouldridge, Proceedings of the National Academy of Sciences116, 1946 (2019)

  4. [4]

    M. J. Thomas, A. A. Platas, and D. K. Hawley, Cell93, 627 (1998)

  5. [5]

    H. S. Zaher and R. Green, Cell136, 746 (2009)

  6. [6]

    Voliotis, N

    M. Voliotis, N. Cohen, C. Molina-Par´ ıs, and T. B. Liv- erpool, Physical review letters102, 258101 (2009)

  7. [7]

    Murugan, D

    A. Murugan, D. A. Huse, and S. Leibler, Proceedings of the National Academy of Sciences109, 12034 (2012)

  8. [8]

    M. F. Hagan, O. M. Elrad, and R. L. Jack, The Journal of chemical physics135(2011)

Show all 45 references
  1. [9]

    Dogterom and S

    M. Dogterom and S. Leibler, Physical review letters70, 1347 (1993)

  2. [10]

    J. J. De Yoreo and P. G. Vekilov, Reviews in mineralogy and geochemistry54, 57 (2003)

  3. [11]

    Whitelam, Y

    S. Whitelam, Y. R. Dahal, and J. D. Schmit, The Journal of chemical physics144(2016)

  4. [12]

    J. Wang, K. Liu, R. Xing, and X. Yan, Chemical Society Reviews45, 5589 (2016)

  5. [13]

    T. W. McKeithan, Proceedings of the national academy of sciences92, 5042 (1995)

  6. [14]

    Goldstein, J

    B. Goldstein, J. R. Faeder, and W. S. Hlavacek, Nature Reviews Immunology4, 445 (2004)

  7. [15]

    J. J. Hopfield, Proceedings of the National Academy of Sciences71, 4135 (1974)

  8. [16]

    Ninio, Biochimie57, 587 (1975)

    J. Ninio, Biochimie57, 587 (1975)

  9. [17]

    Ravasio, K

    R. Ravasio, K. Husain, C. G. Evans, R. Phillips, M. Ribezzi-Crivellari, J. W. Szostak, and A. Murugan, Science391, 818 (2026)

  10. [18]

    Ravasio, K

    R. Ravasio, K. Husain, C. G. Evans, R. Phillips, M. Ribezzi-Crivellari, J. W. Szostak, and A. Murugan, arXiv preprint arXiv:2605.13009 (2026)

  11. [19]

    J. A. Esteban, M. Salas, and L. Blanco, Journal of Bio- logical Chemistry268, 2719 (1993)

  12. [20]

    C. A. Joazeiro, Nature reviews Molecular cell biology20, 368 (2019)

  13. [21]

    W. K. Johnston, P. J. Unrau, M. S. Lawrence, M. E. Glasner, and D. P. Bartel, Science292, 1319 (2001)

  14. [22]

    M. R. Evans and S. N. Majumdar, Physical Review Let- ters106, 160601 (2011)

  15. [23]

    M. R. Evans and S. N. Majumdar, Journal of Physics A: Mathematical and Theoretical44, 435001 (2011)

  16. [24]

    M. R. Evans, S. N. Majumdar, and G. Schehr, Journal of Physics A: Mathematical and Theoretical53, 193001 (2020)

  17. [25]

    G. Bel, B. Munsky, and I. Nemenman, Physical biology 7, 016003 (2010)

  18. [26]

    Munsky, I

    B. Munsky, I. Nemenman, and G. Bel, The Journal of chemical physics131(2009)

  19. [27]

    C. H. Bennett, International Journal of Theoretical Physics21, 905 (1982)

  20. [28]

    T. A. Kunkel, Journal of Biological Chemistry279, 16895 (2004)

  21. [29]

    In [17], the authors discuss the particular case of excision after periodic intervalsT r, which corresponds to the limit 6 fTex(t) =δ(t−T r) in our approach

  22. [30]

    See Supplemental Material (SM) for detailed additional derivations and numerical results along with other related discussions

  23. [31]

    Kusmierz, S

    L. Kusmierz, S. N. Majumdar, S. Sabhapandit, and G. Schehr, Physical Review Letters113, 220602 (2014)

  24. [32]

    Reuveni, Physical Review Letters116, 170601 (2016)

    S. Reuveni, Physical Review Letters116, 170601 (2016)

  25. [33]

    Pal and S

    A. Pal and S. Reuveni, Physical Review Letters118, 030603 (2017)

  26. [34]

    A. Pal, L. Kusmierz, and S. Reuveni, Physical Review Research2, 043174 (2020)

  27. [35]

    Reuveni, M

    S. Reuveni, M. Urbakh, and J. Klafter, Proceedings of the National Academy of Sciences111, 4391 (2014)

  28. [36]

    T. P. Hoekstra, M. Depken, S.-N. Lin, J. Cabanas-Dan´ es, P. Gross, R. T. Dame, E. J. Peterman, and G. J. Wuite, Biophysical journal112, 575 (2017)

  29. [37]

    K. C. Neuman, E. A. Abbondanzieri, R. Landick, J. Gelles, and S. M. Block, Cell115, 437 (2003)

  30. [38]

    J. W. Shaevitz, E. A. Abbondanzieri, R. Landick, and S. M. Block, Nature426, 684 (2003)

  31. [39]

    Y. Yuan, H. Wang, H. Fu, C. Yang, Z. Lin, C. Xu, S. Hu, T. Chen, Q. Jia, M. Li,et al., Journal of the American Chemical Society147, 46094 (2025)

  32. [40]

    S. C. Bera, M. Seifert, R. N. Kirchdoerfer, P. Van Nies, Y. Wubulikasimu, S. Quack, F. S. Papini, J. J. Arnold, B. Canard, C. E. Cameron,et al., Cell Reports36(2021)

  33. [41]

    J.-D. Wen, L. Lancaster, C. Hodges, A.-C. Zeri, S. H. Yoshimura, H. F. Noller, C. Bustamante, and I. Tinoco, Nature452, 598 (2008)

  34. [42]

    Dulin, I

    D. Dulin, I. D. Vilfan, B. A. Berghuis, S. Hage, D. H. Bamford, M. M. Poranen, M. Depken, and N. H. Dekker, Cell reports10, 983 (2015)

  35. [43]

    W. Y. Huang, S. Alvarez, Y. Kondo, Y. K. Lee, J. K. Chung, H. Y. M. Lam, K. H. Biswas, J. Kuriyan, and J. T. Groves, Science363, 1098 (2019)

  36. [44]

    Johnson-Buck and W

    A. Johnson-Buck and W. M. Shih, Nano letters17, 7940 (2017)

  37. [45]

    When proofreading improves speed and accuracy

    A. Pal and V. V. Prasad, Physical Review Research1, 032001 (2019). FIG. 4.Nature of the transition: The optimal value of rate of excision as obtained from Eq. (17) exhibits both first and second order phase transitions with respect toτs andCV s. For first-order transition, how...

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Reviewed June 27, 2026 · model on record in the stance chip above.