Frobenius Eigenvalue Research Articles

On Spectral Radius and Energy of a Graph with Self-Loops

The spectral radius of a square matrix is the maximum among absolute values of its eigenvalues. Suppose a square matrix is nonnegative; then, by Perron–Frobenius theory, it will be one among its eigenvalues. In this paper, Perron–Frobenius theory for adjacency matrix of graph with self-loops AGS will be explored. Specifically, it discusses the nontrivial existence of Perron–Frobenius eigenvalue and eigenvector pair in the matrix AGS−σnI, where σ denotes the number of self-loops. Also, Koolen–Moulton type bound for the energy of graph GS is explored. In addition, the existence of a graph with self-loops for every odd energy is proved.

Moderate deviation principle for guesswork

In this paper, we establish a moderate deviation principle for the logarithm of guesswork, which was initially studied by Massey to quantify the number of guesses needed to ascertain a discrete random variable. Our approach is based on an asymptotic analysis for Perron–Frobenius eigenvalue of some perturbed matrix and several moments estimates bounds for guesswork.

Approximate spectral decomposition of Fisher information matrix for simple ReLU networks

We argue the Fisher information matrix (FIM) of one hidden layer networks with the ReLU activation function. For a network, let W denote the d×p weight matrix from the d-dimensional input to the hidden layer consisting of p neurons, and v the p-dimensional weight vector from the hidden layer to the scalar output. We focus on the FIM of v, which we denote as I. Under certain conditions, we characterize the first three clusters of eigenvalues and eigenvectors of the FIM. Specifically, we show that the following approximately holds. (1) Since I is non-negative owing to the ReLU, the first eigenvalue is the Perron–Frobenius eigenvalue. (2) For the cluster of the next maximum values, the eigenspace is spanned by the row vectors of W. (3) The direct sum of the eigenspace of the first eigenvalue and that of the third cluster is spanned by the set of all the vectors obtained as the Hadamard product of any pair of the row vectors of W. We confirmed by numerical calculation that the above is approximately correct when the number of hidden nodes is about 10000.

Learning by Population Genetics and Matrix Riccati Equation

A model of learning as a generalization of the Eigen's quasispecies model in population genetics is introduced. Eigen's model is considered as a matrix Riccati equation. The error catastrophe in the Eigen's model (when the purifying selection becomes ineffective) is discussed as the divergence of the Perron-Frobenius eigenvalue of the Riccati model in the limit of large matrices. A known estimate for the Perron-Frobenius eigenvalue provides an explanation for observed patterns of genomic evolution. We propose to consider the error catastrophe in Eigen's model as an analog of overfitting in learning theory; this gives a criterion for the presence of overfitting in learning.

The open Haldane–Shastry chain: thermodynamics and criticality

We study the thermodynamics and criticality of the su(m|n) Haldane–Shastry chain of BC N type with a general chemical potential term. We first derive a complete description of the spectrum of this model in terms of BC N -type motifs, from which we deduce a representation for the partition function as the trace of a product of site-dependent transfer matrices. In the thermodynamic limit, this formula yields a simple expression for the free energy per spin in terms of the Perron–Frobenius eigenvalue of the continuum limit of the transfer matrix. Evaluating this eigenvalue we obtain closed-form expressions for the thermodynamic functions of the chains with m, n ⩽ 2. Using the motif-based description of the spectrum derived here, we study in detail the ground state of these models and their low energy excitations. In this way we identify the critical intervals in chemical potential space and compute their corresponding Fermi velocities. By contrast with previously studied models of this type, we find in some cases two types of low energy excitations with linear energy-quasimomentum relation. Finally, we determine the central charge of all the critical phases by analyzing the low-temperature behavior of the expression for the free energy per spin.

A probabilistic proof of the Perron–Frobenius theorem

AbstractThe Perron–Frobenius theorem plays an important role in many areas of management science and operations research. This article provides a probabilistic perspective on the theorem, by discussing a proof that exploits a probabilistic representation of the Perron–Frobenius eigenvalue and eigenvectors in terms of the dynamics of a Markov chain. The proof recovers conditions in both the finite‐dimensional and infinite‐dimensional settings under which the Perron–Frobenius eigenvalue and eigenvectors have been shown to exist by other methods. In addition to providing new insights, the probabilistic representations that arise can be used to produce a Monte–Carlo algorithm for computing the Perron–Frobenius eigenvalue and eigenvectors that will be explored elsewhere.

Gambler’s ruin estimates on finite inner uniform domains

Gambler’s ruin estimates can be viewed as harmonic measure estimates for finite Markov chains which are absorbed (or killed) at boundary points. We relate such estimates to properties of the underlying chain and its Doob transform. Precisely, we show that gambler’s ruin estimates reduce to a good understanding of the Perron–Frobenius eigenfunction and eigenvalue whenever the underlying chain and its Doob transform are Harnack Markov chains. Finite inner-uniform domains (say, in the square grid Zn) provide a large class of examples where these ideas apply and lead to detailed estimates. In general, understanding the behavior of the Perron–Frobenius eigenfunction remains a challenge.

Finding Saddle-Node Bifurcations via a Nonlinear Generalized Collatz–Wielandt Formula

The Collatz–Wielandt formula obtained by Lothar Collatz (1942) and Helmut Wielandt (1950) provides a simple variational characterization of the Perron–Frobenius eigenvalue of certain types of matrices. We introduce a nonlinear generalization of the Collatz–Wielandt formula and show that it enables finding the so-called maximal saddle-node bifurcations of systems of nonlinear equations. As a consequence, we obtain an easily verifiable criterion for the detection of such saddle-node bifurcations. We illustrate our approach by examples of finite-difference approximations of nonlinear partial differential equations and a system of power flow.

Maximum Interval of Stability and Convergence of Solution of a Forced Mathieu’s Equation

This paper investigates the maximum interval of stability and convergence of solution of a forced Mathieu’s equation, using a combination of Frobenius method and Eigenvalue approach. The results indicated that the equilibrium point was found to be unstable and maximum bounds were found on the derivative of the restoring force showing sharp condition for the existence of periodic solution. Furthermore, the solution to Mathieu’s equation converges which extends and improves some results in literature.

Tight-Binding Modeling of Nucleic Acid Sequences: Interplay between Various Types of Order or Disorder and Charge Transport

This review is devoted to tight-binding (TB) modeling of nucleic acid sequences like DNA and RNA. It addresses how various types of order (periodic, quasiperiodic, fractal) or disorder (diagonal, non-diagonal, random, methylation et cetera) affect charge transport. We include an introduction to TB and a discussion of its various submodels [wire, ladder, extended ladder, fishbone (wire), fishbone ladder] and of the process of renormalization. We proceed to a discussion of aperiodicity, quasicrystals and the mathematics of aperiodic substitutional sequences: primitive substitutions, Perron–Frobenius eigenvalue, induced substitutions, and Pisot property. We discuss the energy structure of nucleic acid wires, the coupling to the leads, the transmission coefficients and the current–voltage curves. We also summarize efforts aiming to examine the potentiality to utilize the charge transport characteristics of nucleic acids as a tool to probe several diseases or disorders.

Mean field systems on networks, with singular interaction through hitting times

Building on the line of work (Ann. Appl. Probab. 25 (2015) 2096–2133; Stochastic Process. Appl. 125 (2015) 2451–2492; Ann. Appl. Probab. 29 (2019) 89–129; Arch. Ration. Mech. Anal. 233 (2019) 643–699; Ann. Appl. Probab. 29 (2019) 2338–2373; Finance Stoch. 23 (2019) 535–594), we continue the study of particle systems with singular interaction through hitting times. In contrast to the previous research, we (i) consider very general driving processes and interaction functions, (ii) allow for inhomogeneous connection structures and (iii) analyze a game in which the particles determine their connections strategically. Hereby, we uncover two completely new phenomena. First, we characterize the “times of fragility” of such systems (e.g., the times when a macroscopic part of the population defaults or gets infected simultaneously, or when the neuron cells “synchronize”) explicitly in terms of the dynamics of the driving processes, the current distribution of the particles’ values and the topology of the underlying network (represented by its Perron–Frobenius eigenvalue). Second, we use such systems to describe a dynamic credit-network game and show that, in equilibrium, the system regularizes, that is, the times of fragility never occur, as the particles avoid them by adjusting their connections strategically. Two auxiliary mathematical results, useful in their own right, are uncovered during our investigation: a generalization of Schauder’s fixed-point theorem for the Skorokhod space with the M1 topology, and the application of max-plus algebra to the equilibrium version of the network flow problem.

Galton–Watson and branching process representations of the normalized Perron–Frobenius eigenvector

Let A be a primitive matrix and let λ be its Perron–Frobenius eigenvalue. We give formulas expressing the associated normalized Perron–Frobenius eigenvector as a simple functional of a multitype Galton–Watson process whose mean matrix is A, as well as of a multitype branching process with mean matrix e(A−I)t. These formulas are generalizations of the classical formula for the invariant probability measure of a Markov chain.

Relationships between Perron–Frobenius eigenvalue and measurements of loops in networks

The Perron–Frobenius eigenvalue (PFE) is widely used as measurement of the number of loops in networks, but what exactly the relationship between the PFE and the number of loops in networks is has not been researched yet, is it strictly monotonically increasing? And what are the relationships between the PFE and other measurements of loops in networks? Such as the average loop degree of nodes, and the distribution of loop ranks. We make researches on these questions based on samples of ER random network, NW small-world network and BA scale-free network, and the results confirm that, both the number of loops in network and the average loop degree of nodes of all samples do increase with the increase of the PFE in general trend, but neither of them are strictly monotonically increasing, so the PFE is capable to be used as a rough estimative measurement of the number of loops in networks and the average loop degree of nodes. Furthermore, we find that a majority of the loop ranks of all samples obey Weibull distribution, of which the scale parameter A and the shape parameter B have approximate power-law relationships with the PFE of the samples.

Representations for the decay parameter of Markov chains

In this paper, we give variational representations for decay parameters of Markov chains. In continuous-time cases, the representation involves Donsker–Varadhan’s famous $I$-functional, from which some dual representations are given, which are expected to he useful in estimating the lower and upper bounds of the decay parameter. As a consequence, dual representations for decay parameters of discrete time Markov chains are derived. For continuous-time chains with finite states, we also give another form of dual formulas, which can be regarded as a version of the one for the Perron–Frobenius eigenvalue, with nonnegative matrices replaced by $Q$-matrices of the chains. Connections with quasi-stationarity and quasi-ergodicity of absorbing Markov chains are discussed. An interpretation for the corresponding variational solutions is given.

Analysis and Synthesis of Interconnected Positive Systems

This paper is concerned with the analysis and synthesis of interconnected systems constructed from heterogeneous positive subsystems and a nonnegative interconnection matrix. We first show that admissibility, to be defined in this paper, is an essential requirement in constructing such interconnected systems. Then, we clarify that the interconnected system is admissible and stable if and only if a Metzler matrix, which is built from the coefficient matrices of positive subsystems and the nonnegative interconnection matrix, is Hurwitz stable. By means of this key result, we further provide several results that characterize the admissibility and stability of the interconnected system in terms of the Frobenius eigenvalue of the interconnection matrix and the weighted L1- induced norm of the positive subsystems again to be defined in this paper. Moreover, in the case where every subsystem is SISO, we provide explicit conditions under which the interconnected system has the property of persistence, i.e., its state converges to a unique strictly positive vector (that is known in advance up to a strictly positive constant multiplicative factor) for any nonnegative and nonzero initial state. As an important consequence of this property, we show that the output of the interconnected system converges to a scalar multiple of the right eigenvector of a nonnegative matrix associated with its Frobenius eigenvalue, where the nonnegative matrix is nothing but the interconnection matrix scaled by the steady-stage gains of the positive subsystems. This result is then naturally and effectively applied to formation control of multiagent systems with positive dynamics. This result can be seen as a generalization of a well-known consensus algorithm that has been basically applied to interconnected systems constructed from integrators.

A Variational Formula for Risk-Sensitive Reward

We derive a variational formula for the optimal growth rate of reward in the infinite horizon risk-sensitive control problem for discrete time Markov decision processes with compact metric state and action spaces, extending a formula of Donsker and Varadhan for the Perron--Frobenius eigenvalue of a positive operator. This leads to a concave maximization formulation of the problem of determining this optimal growth rate.

Combating Strong–Weak Spatial–Temporal Resonances in Time-Reversal Uplinks

In a time-reversal (TR) communication system, the signal-to-noise ratio (SNR) is boosted and the inter-user interference (IUI) is suppressed due to the spatial–temporal resonances, commonly known as the focusing effects, of the TR technique when implemented in a rich scattering environment. However, since the spatial–temporal resonances highly depend on the location-specific multipath profile, there exists a strong–weak spatial–temporal resonances effect. In the TR uplink system, different users at different locations enjoy different strengths of spatial–temporal resonances, i.e., the received signal-to-interference-noise ratios (SINRs) for different users vary, and the weak ones can be blocked from correct detection in the presence of strong ones. In this paper, we formulate the strong–weak spatial–temporal resonances in the multiuser TR uplink system as a max–min weighted SINR balancing problem by joint power control and signature design. Then, a novel two-stage adaptive algorithm that can guarantee the convergence is proposed. In stage I, the original nonconvex problem is relaxed into a Perron Frobenius eigenvalue optimization problem and an iterative algorithm is proposed to obtain the optimum efficiently. In stage II, the gradient search method is applied to update the relaxed feasible set until the global optimum for the original optimization problem is obtained. Numerical results show that our algorithm converges quickly, achieves a high energy-efficiency, and provides a performance guarantee to all users.

On the structure of Thue–Morse subwords, with an application to dynamical systems

We give an in-depth analysis of the subwords of the Thue–Morse sequence. This allows us to prove that there are infinitely many injective primitive substitutions with Perron–Frobenius eigenvalue 2 that generate a symbolic dynamical system topologically conjugate to the Thue–Morse dynamical system.

Orbit representations from matrices

Each Markov interval map f naturally produces a transition 0–1 matrix of interval type (in every row, the entries equal to 1 should be consecutive). We show that any 0–1 matrix A can be transformed into an interval type matrix AI, by a careful use of the state splitting. We then prove that AI can be realized as a transition matrix of an interval map fAI,λAI arising from the Perron–Frobenius eigenvalue λAI and eigenvector of AI. Finally, we construct orbit representations associated with A from those of AI arising from the dynamical system ([0,1],fAI,λAI).

Zero-sum risk-sensitive stochastic games on a countable state space

Infinite horizon discounted-cost and ergodic-cost risk-sensitive zero-sum stochastic games for controlled Markov chains with countably many states are analyzed. Upper and lower values for these games are established. The existence of value and saddle-point equilibria in the class of Markov strategies is proved for the discounted-cost game. The existence of value and saddle-point equilibria in the class of stationary strategies is proved under the uniform ergodicity condition for the ergodic-cost game. The value of the ergodic-cost game happens to be the product of the inverse of the risk-sensitivity factor and the logarithm of the common Perron–Frobenius eigenvalue of the associated controlled nonlinear kernels.