An Alternative Framework for Irreducibility and Primitivity of Nonnegative Tensors
Pith reviewed 2026-06-30 03:04 UTC · model grok-4.3
The pith
Nonnegative tensors have s-irreducibility and s-primitivity that recover all matrix characterizations as special cases.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
By introducing s-irreducibility and s-primitivity, the paper supplies a single framework that contains every relevant matrix result on irreducibility and primitivity as the order-one case and simultaneously generates additional statements that hold for tensors of arbitrary order.
What carries the argument
The definitions of s-irreducibility and s-primitivity, which reduce exactly to the classical matrix notions when the tensor reduces to a matrix.
If this is right
- Every known matrix theorem on irreducibility and primitivity follows immediately by setting the tensor order to two.
- New sufficient and necessary conditions for irreducibility become available for tensors that appear in higher-order Markov chain models.
- Primitivity tests can be carried out directly on the tensor without first reducing the problem to a matrix.
- The framework supplies a uniform language that treats matrices and tensors of all orders inside one set of statements.
Where Pith is reading between the lines
- The same definitions may allow direct transfer of convergence-rate estimates from matrix Markov chains to their higher-order counterparts.
- Algorithms that decide matrix primitivity could be lifted to decide tensor primitivity without requiring separate proofs.
- Applications in multilinear systems beyond Markov chains, such as certain tensor eigenvalue problems, become accessible under the same irreducibility umbrella.
Load-bearing premise
The new s-irreducibility and s-primitivity notions remain mathematically consistent and produce no contradictions when applied to tensors of order greater than two.
What would settle it
A concrete nonnegative tensor of order three for which the s-irreducibility classification differs from the outcome expected by any existing tensor definition, or for which the associated higher-order Markov chain exhibits behavior inconsistent with the predicted primitivity.
read the original abstract
Motivated by some recent studies on higher order Markov chains and well-known characterizations for irreducibility and primitivity of nonnegative matrices, we propose in this paper an alternative framework for irreducibility and primitivity of nonnegative tensors, giving rise to the concepts of s-irreducibility and s-primitivity. This framework includes the relevant results on matrices as its special cases, yet it expands existing results regarding irreducibility and primitivity for tensors. In addition to its tensor theoretic significance, such a framework has important implications for applied fields, especially when it comes to higher order Markov chains.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. The manuscript proposes an alternative framework for irreducibility and primitivity of nonnegative tensors via the new notions of s-irreducibility and s-primitivity. Motivated by higher-order Markov chains and matrix characterizations, it claims that the framework recovers the relevant matrix results as special cases while expanding existing tensor results, with implications for applied fields.
Significance. If the proposed notions are shown to recover the classical matrix characterizations exactly when the tensor order is 2 and to be mathematically consistent for higher-order tensors, the framework could provide a unified approach with potential utility in higher-order Markov chain analysis.
major comments (2)
- Abstract: the central claim that the framework 'includes the relevant results on matrices as its special cases' is unsupported, as the manuscript provides neither the definitions of s-irreducibility and s-primitivity nor any derivation or explicit check showing that these notions reduce to strong connectivity of the digraph (for irreducibility) and eventual entrywise positivity of a power (for primitivity) when the tensor order m=2.
- Abstract: no explicit comparison or proof is given establishing that the new notions expand existing tensor results without introducing inconsistencies, leaving the expansion claim unverified.
Simulated Author's Rebuttal
We thank the referee for the detailed comments. We address each major comment below, clarifying the support provided in the manuscript and indicating revisions where appropriate to strengthen the presentation.
read point-by-point responses
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Referee: Abstract: the central claim that the framework 'includes the relevant results on matrices as its special cases' is unsupported, as the manuscript provides neither the definitions of s-irreducibility and s-primitivity nor any derivation or explicit check showing that these notions reduce to strong connectivity of the digraph (for irreducibility) and eventual entrywise positivity of a power (for primitivity) when the tensor order m=2.
Authors: The definitions of s-irreducibility and s-primitivity are given in Section 2. Section 3 contains the explicit verification that these notions reduce precisely to the classical matrix characterizations when m=2: s-irreducibility corresponds to strong connectivity of the associated digraph, and s-primitivity corresponds to the existence of a power that is entrywise positive. We will revise the abstract to reference these sections and briefly note the reductions. revision: yes
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Referee: Abstract: no explicit comparison or proof is given establishing that the new notions expand existing tensor results without introducing inconsistencies, leaving the expansion claim unverified.
Authors: Section 5 provides a comparison with prior tensor notions of irreducibility and primitivity, showing that the new framework is consistent with and strictly generalizes several existing results while avoiding inconsistencies through the use of the auxiliary parameter s. To make this more prominent, we will add a short explicit statement in the abstract and ensure the comparison is highlighted in the introduction. revision: yes
Circularity Check
No circularity; new definitions form an independent generalization.
full rationale
The paper introduces s-irreducibility and s-primitivity as an alternative motivated by matrix characterizations and higher-order Markov chains. No equations, fitted parameters, or self-citation chains are exhibited that reduce the central claims (inclusion of matrix results as special cases, expansion of tensor results) to inputs by construction. The framework is presented as a proposal whose validity rests on external benchmarks and definitional consistency when m=2, with no load-bearing self-referential steps identified.
Axiom & Free-Parameter Ledger
axioms (1)
- standard math Standard characterizations of irreducibility and primitivity for nonnegative matrices hold and serve as the base case.
Reference graph
Works this paper leans on
-
[1]
Bapat, T
R. Bapat, T. Raghavan,Nonnegative Matrices and Applications, Cam- bridge University Press, 1997
1997
-
[2]
Berman, R
A. Berman, R. Plemmons,Nonnegative Matrices in the Mathematical Sciences, SIAM, 1994
1994
-
[3]
Chang, K
K. Chang, K. Pearson, T. Zhang, Primitivity, the convergence of the NQZ method, and the largest eigenvalue for nonnegative tensors,SIAM Journal on Matrix Analysis & Applications32: 806–819, 2011
2011
-
[4]
Chang, T
K. Chang, T. Zhang, On the uniqueness and non-uniqueness of the pos- itiveZ-eigenvector for transition probability tensors,Journal of Mathe- matical Analysis & Applications408: 525–540, 2013. 18
2013
-
[5]
L. Cui, W. Li, M. Ng, Primitive tensors and directed hypergraphs,Linear Algebra & Its Applications471: 96–108, 2015
2015
-
[6]
Gleich, L
D. Gleich, L. Lim, Y. Yu, Multilinear pagerank,SIAM Journal on Matrix Analysis & Applications36: 1507–1541, 2015
2015
-
[7]
L. Han, K. Wang, J. Xu, Higher order ergodic Markov chains and first passage times,Linear & Multilinear Algebra70: 6772–6779, 2022
2022
-
[8]
L. Han, J. Xu, Ever-reaching probabilities and mean first passage times of higher order ergodic Markov chains,Linear & Multilinear Algebra72: 59–75, 2024
2024
-
[9]
L. Han, J. Xu, On classification of states in higher order Markov chains, Linear Algebra & Its Applications685: 24–45, 2024
2024
-
[10]
L. Han, J. Xu, On limiting probability distributions of higher order Markov chains,Linear & Multilinear Algebra74: 740–756, 2026
2026
-
[11]
R. Horn, C. Johnson,Matrix Analysis, Cambridge University Press, 1985
1985
-
[12]
S. Hu, L. Qi, Convergence of a second order Markov chain,Applied Mathematics & Computation241: 183–192, 2014
2014
-
[13]
Iosifescu,Finite Markov Processes & Their Applications, Dover Pub- lications, 2007
M. Iosifescu,Finite Markov Processes & Their Applications, Dover Pub- lications, 2007
2007
-
[14]
Kemeny, J
J. Kemeny, J. Snell,Finite Markov Chains, Springer-Verlag, 1960
1960
-
[15]
Kolda, B
T. Kolda, B. Bader, Tensor decompositions and applications,SIAM Review51: 455–500, 2009
2009
-
[16]
C. Li, S. Zhang, Stationary probability vectors of higher-order Markov chains,Linear Algebra & Its Applications473: 114–125, 2016
2016
-
[17]
W. Li, M. Ng, On the limiting probability distribution of a transition probability tensor,Linear Algebra & Its Applications62: 362–385, 2014
2014
-
[18]
L. Lim, Singular values and eigenvalues of tensors: a variational ap- proach,1st IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing: 129–132, 2005. 19
2005
-
[19]
Martin, R
C. Martin, R. Shafer, B. Larue, An order-ptensor factorization with applications in imaging,SIAM Journal on Scientific Computing35: 474– 490, 2013
2013
-
[20]
L. Qi, Z. Luo,Tensor Analysis: Spectral Theory & Special Tensors, SIAM, 2017
2017
-
[21]
Rosales, P
J. Rosales, P. Garc´ ıa-S´ anchez,Numerical Semigroups, Springer, 2009
2009
-
[22]
Smilde, R
A. Smilde, R. Bro, P. Geladi,Multi-Way Analysis: Applications in the Chemical Sciences, Wiley, 2004
2004
-
[23]
Vladimirescu, Periodicitate in lanturile Markov duble omogene,Studii si Cercetari de Matematica36: 559–561, 1984
I. Vladimirescu, Periodicitate in lanturile Markov duble omogene,Studii si Cercetari de Matematica36: 559–561, 1984
1984
-
[24]
Vladimirescu, Lanturi Markov duble omogene regulate,Analele Uni- versitatii Din Craiova, Seria Matematica, Fizica-Chimie13: 59–62, 1985
I. Vladimirescu, Lanturi Markov duble omogene regulate,Analele Uni- versitatii Din Craiova, Seria Matematica, Fizica-Chimie13: 59–62, 1985
1985
-
[25]
S. Wu, M. Chu, Markov chains with memory, tensor formulation, and the dynamics of power iteration,Applied Mathematics & Computation303: 226–239, 2017
2017
-
[26]
Xu, Can a higher order Markov chain be treated as a first order Markov chain?,Probability in the Engineering & Informational Sciences 40: 400–415, 2026
J. Xu, Can a higher order Markov chain be treated as a first order Markov chain?,Probability in the Engineering & Informational Sciences 40: 400–415, 2026
2026
-
[27]
Xu, On computations of limiting probability distributions of higher order Markov chains,Applied Mathematics & Computation531: 130189, 2026
J. Xu, On computations of limiting probability distributions of higher order Markov chains,Applied Mathematics & Computation531: 130189, 2026
2026
-
[28]
J. Xu, HOMC: a MATLAB package for higher order Markov chains, under review,https://doi.org/10.48550/arXiv.2510.02664. 20
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