Directed extended-range percolation
Pith reviewed 2026-05-22 03:55 UTC · model grok-4.3
The pith
Directionality in networks with paths of length at least two simplifies percolation, allowing exact thresholds and critical indices on tree-like structures.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
In directed networks, connectivity ensured by directed paths of length at most R greater than or equal to 2 lets message-passing close exactly on locally tree-like graphs, so the percolation threshold and the anomalous critical indices follow directly from the equations without further approximation, and the location of the transition depends sensitively on the degree correlations present in the network.
What carries the argument
Message-passing equations for Directed Extended-Range Percolation (DERP), which track the probability of directed-path connectivity while forbidding backtracking.
If this is right
- The percolation threshold becomes an explicit function of the directed degree distribution and the range R.
- Critical exponents deviate from the standard mean-field values and can be calculated in closed form.
- Degree correlations shift the threshold and the nature of the transition in a manner captured by the same equations.
- Monte Carlo simulations on finite random directed graphs match the analytic predictions for both threshold and exponents.
Where Pith is reading between the lines
- The same simplification may apply to other spreading or search processes on directed graphs whenever backtracking is impossible.
- Real directed networks with moderate clustering could be approximated by adding small corrections to the tree-like formulas.
- The framework suggests a way to design directed topologies that achieve desired connectivity with lower resource cost.
Load-bearing premise
The networks contain no short loops that would create additional paths outside the tree-like structure.
What would settle it
A numerical measurement of the percolation threshold on a small directed network that contains many triangles or short cycles, compared against the value predicted by the message-passing equations.
Figures
read the original abstract
While for standard percolation directionality is known to increase the combinatorial complexity of percolation, here we show that when connectivity is ensured by paths of length $R\geq 2$, network directionality, impeding backtracking, can significantly reduce the complexity of percolation. To illustrate this finding, we introduce Directed Extended-Range Percolation (DERP), defined directed networks with non-reciprocal edges, motivated by applications in quantum communication. In this framework, message transmission is enabled between trusted nodes separated by a directed path of length at most $R$. Using a message-passing approach, we show that directionality enables an exact determination of the percolation threshold and the anomalous critical indices on locally tree-like structures. On random directed networks we find that the critical behavior of DERP depends sensitively on degree correlations. These analytical predictions are corroborated by extensive Monte Carlo simulations, highlighting the profound impact of directionality and correlations on long-range connectivity in complex networks.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript introduces Directed Extended-Range Percolation (DERP) on directed networks with non-reciprocal edges. Connectivity is defined by the existence of a directed path of length at most R ≥ 2. On locally tree-like random directed networks, a message-passing formalism is used to obtain exact expressions for the percolation threshold and the anomalous critical exponents; these quantities depend sensitively on degree correlations. The analytical predictions are corroborated by Monte Carlo simulations on finite random directed graphs.
Significance. If the central results hold, the work is significant because it demonstrates that directionality can reduce the combinatorial complexity of extended-range percolation by eliminating backtracking, thereby enabling closed-form solutions for thresholds and exponents where standard percolation is typically intractable. The explicit dependence on degree correlations and the direct simulation corroboration strengthen the contribution, with potential relevance to quantum communication networks.
major comments (2)
- [§3.1] §3.1, message-passing equations: the claim that the equations close exactly for R ≥ 2 due to the absence of backtracking is central to the exact solvability result; however, the explicit handling of joint in/out-degree correlations in the generating functions is only sketched, and a full derivation showing that no additional cycle corrections arise would strengthen the load-bearing step.
- [§4.2] §4.2, critical exponents: the anomalous exponents are obtained by linearizing the message-passing recursion near threshold; the paper should verify that the leading eigenvalue analysis remains valid when the degree distribution has finite variance but non-zero correlations, as this directly supports the reported dependence on correlations.
minor comments (3)
- [Simulations section] The abstract states that simulations 'corroborate' the predictions, but the main text does not report the number of network realizations, system sizes, or fitting procedure used to extract exponents; adding these details would improve reproducibility.
- [Eq. (7)] Notation for the cavity probabilities in Eq. (7) uses subscripts that are easily confused with degree indices; a short table of symbols would aid clarity.
- [Introduction] The motivation linking DERP to quantum communication is mentioned only briefly; expanding this connection by one sentence in the introduction would help contextualize the model for readers outside network science.
Simulated Author's Rebuttal
We thank the referee for their thoughtful review and recommendation for minor revision. We appreciate the positive assessment of the significance of our work on Directed Extended-Range Percolation. Below, we address each major comment in detail.
read point-by-point responses
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Referee: [§3.1] §3.1, message-passing equations: the claim that the equations close exactly for R ≥ 2 due to the absence of backtracking is central to the exact solvability result; however, the explicit handling of joint in/out-degree correlations in the generating functions is only sketched, and a full derivation showing that no additional cycle corrections arise would strengthen the load-bearing step.
Authors: We agree that providing a more explicit derivation would enhance the clarity of our central result. In the revised manuscript, we will expand Section 3.1 and add a detailed appendix deriving the message-passing equations from first principles. This will explicitly incorporate the joint in/out-degree correlations through the appropriate generating functions and demonstrate that, due to the directed nature and absence of backtracking for R ≥ 2, no additional cycle corrections are needed on locally tree-like networks. revision: yes
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Referee: [§4.2] §4.2, critical exponents: the anomalous exponents are obtained by linearizing the message-passing recursion near threshold; the paper should verify that the leading eigenvalue analysis remains valid when the degree distribution has finite variance but non-zero correlations, as this directly supports the reported dependence on correlations.
Authors: We thank the referee for this suggestion. The linearization procedure and the leading eigenvalue analysis are valid under the stated conditions because the message-passing equations are formulated in terms of the joint degree distributions, which account for correlations explicitly. To address this, we will include in the revised version a brief verification, perhaps through an additional numerical check or analytical argument, confirming that the eigenvalue analysis holds for finite-variance distributions with non-zero correlations, thereby supporting the correlation-dependent critical behavior. revision: yes
Circularity Check
No significant circularity detected in derivation
full rationale
The central derivation relies on standard message-passing equations applied to locally tree-like directed networks where directionality for paths of length R >= 2 eliminates backtracking and allows exact closure without cycle corrections. Thresholds and anomalous exponents are obtained by solving these equations, with explicit accounting for degree correlations; the results are not defined in terms of themselves nor obtained by fitting then relabeling as prediction. Monte Carlo simulations on finite graphs serve as independent external corroboration rather than circular support. No load-bearing self-citation reduces the argument to an unverified prior claim by the same authors, and the approach remains self-contained against the stated assumptions.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption Networks are locally tree-like
Lean theorems connected to this paper
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IndisputableMonolith/Cost/FunctionalEquation.leanwashburn_uniqueness_aczel unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
message passing equations for DERP... ωr,(±)i→j ... non-backtracking matrices B(±)
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IndisputableMonolith/Foundation/DimensionForcing.leanreality_from_one_distinction unclear?
unclearRelation between the paper passage and the cited Recognition theorem.
critical behavior depends sensitively on degree correlations... anomalous exponents for γ≤4
What do these tags mean?
- matches
- The paper's claim is directly supported by a theorem in the formal canon.
- supports
- The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
- extends
- The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
- uses
- The paper appears to rely on the theorem as machinery.
- contradicts
- The paper's claim conflicts with a theorem or certificate in the canon.
- unclear
- Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.
Reference graph
Works this paper leans on
-
[1]
S.N.Dorogovtsev, A.V.Goltsev,andJ.F.Mendes,Crit- ical phenomena in complex networks, Reviews of Modern Physics80, 1275 (2008)
work page 2008
- [2]
-
[3]
Bianconi,Multilayer networks: structure and function (Oxford university press, 2018)
G. Bianconi,Multilayer networks: structure and function (Oxford university press, 2018)
work page 2018
-
[4]
A. P. Millán, H. Sun, L. Giambagli, R. Muolo, T. Car- letti, J. J. Torres, F. Radicchi, J. Kurths, and G. Bian- coni, Topology shapes dynamics of higher-order net- works, Nature Physics21, 353 (2025)
work page 2025
-
[5]
O. Artime and M. De Domenico, Percolation on feature- 6 enriched interconnected systems, Nature Communica- tions12, 10.1038/s41467-021-22721-z (2021)
-
[6]
S. V. Buldyrev, R. Parshani, G. Paul, H. E. Stanley, and S. Havlin, Catastrophic cascade of failures in interdepen- dent networks, Nature464, 1025 (2010)
work page 2010
-
[7]
H. Sun, D. Saad, and A. Y. Lokhov, Competition, collab- oration, and optimization in multiple interacting spread- ing processes, Physical Review X11, 011048 (2021)
work page 2021
-
[8]
H. Sun, F. Radicchi, J. Kurths, and G. Bianconi, The dynamic nature of percolation on networks with triadic interactions, Nature Communications14, 1308 (2023)
work page 2023
-
[9]
X. Meng, J. Gao, and S. Havlin, Concurrence percola- tion in quantum networks, Physical Review Letters126, 170501 (2021)
work page 2021
-
[10]
X. Meng, B. Hao, B. Ráth, and I. A. Kovács, Path per- colation in quantum communication networks, Physical review letters134, 030803 (2025)
work page 2025
- [11]
-
[12]
M. Kim, L. Cirigliano, C. Castellano, H. Sun, R. Jankowski, A. Poggialini, and F. Radicchi, Shortest- path percolation on scale-free networks, Physical Review E113, 014314 (2026)
work page 2026
-
[13]
L. Cirigliano, C. Castellano, and G. Bianconi, General theory for extended-range percolation on simple and mul- tiplex networks, Phys. Rev. E110, 034302 (2024)
work page 2024
-
[14]
L. Cirigliano, C. Castellano, and G. Timár, Extended- range percolation in complex networks, Phys. Rev. E 108, 044304 (2023)
work page 2023
-
[15]
L. Cirigliano, V. Brosco, C. Castellano, S. Felicetti, L. Pi- lozzi, and B. van Heck, Dynamical entanglement perco- lation with spatially correlated disorder, arXiv preprint arXiv:2601.05925 (2026)
-
[16]
X. Hu, G. Dong, K. Christensen, H. Sun, J. Fan, Z. Tian, J. Gao, S. Havlin, R. Lambiotte, and X. Meng, Unveil- ing the importance of nonshortest paths in quantum net- works, Science advances11, eadt2404 (2025)
work page 2025
- [17]
- [18]
-
[19]
L. Feng, Y.-Y. Huang, Y.-K. Wu, W.-X. Guo, J.-Y. Ma, H.-X. Yang, L. Zhang, Y. Wang, C.-X. Huang, C. Zhang, et al., Realization of a crosstalk-avoided quantum net- work node using dual-type qubits of the same ion species, Nature Communications15, 204 (2024)
work page 2024
-
[20]
C. M. Knaut, A. Suleymanzade, Y.-C. Wei, D. R. As- sumpcao, P.-J. Stas, Y. Q. Huan, B. Machielse, E. N. Knall, M. Sutula, G. Baranes,et al., Entanglement of nanophotonic quantum memory nodes in a telecom net- work, Nature629, 573 (2024)
work page 2024
-
[21]
Z. Xun, D. Hao, and R. M. Ziff, Site percolation on square and simple cubic lattices with extended neigh- borhoods and their continuum limit, Physical Review E 103, 022126 (2021)
work page 2021
- [22]
-
[23]
Z. Xun, D. Hao, and R. M. Ziff, Extended-range site and bond percolation in five dimensions, Journal of Statis- tical Mechanics: Theory and Experiment2025, 123301 (2025)
work page 2025
-
[24]
M. Newman, Message passing methods on complex net- works, Proceedings of the Royal Society A: Mathemati- cal, Physical and Engineering Sciences479(2023)
work page 2023
-
[25]
Percolation on sparse networks
B. Karrer, M. E. Newman, and L. Zdeborová, Percola- tion on sparse networks, arXiv preprint arXiv:1405.0483 (2014)
work page internal anchor Pith review Pith/arXiv arXiv 2014
-
[26]
J.LeskovecandA.Krevl,SNAPDatasets: Stanfordlarge network dataset collection,http://snap.stanford.edu/ data(2014). 7 SUPPLEMENTAL MATERIAL I. CRITICAL INDICES In this section we derive the critical indices of the DERP process on random directed networks with given degree distributionP(k). Our starting point will be the self-consistent equations forW(+) r g...
work page 2014
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