Markovian Evolution Research Articles

A general mathematical framework for the analysis of spatiotemporal point processes

Spatial and stochastic models are often straightforward to simulate but difficult to analyze mathematically. Most of the mathematical methods available for nonlinear stochastic and spatial models are based on heuristic rather than mathematically justified assumptions, so that, e.g., the choice of the moment closure can be considered more of an art than a science. In this paper, we build on recent developments in specific branch of probability theory, Markov evolutions in the space of locally finite configurations, to develop a mathematically rigorous and practical framework that we expect to be widely applicable for theoretical ecology. In particular, we show how spatial moment equations of all orders can be systematically derived from the underlying individual-based assumptions. Further, as a new mathematical development, we go beyond mean-field theory by discussing how spatial moment equations can be perturbatively expanded around the mean-field model. While we have suggested such a perturbation expansion in our previous research, the present paper gives a rigorous mathematical justification. In addition to bringing mathematical rigor, the application of the mathematically well-established framework of Markov evolutions allows one to derive perturbation expansions in a transparent and systematic manner, which we hope will facilitate the application of the methods in theoretical ecology.

Critical transistors nexus based circuit-level aging assessment and prediction

Accurate age modeling, and fast, yet robust reliability sign-off emerged as mandatory constraints in Integrated Circuits (ICs) design for advanced process technology nodes. In this paper we introduce a novel method to assess and predict the circuit reliability at design time as well as at run-time. The main goal of our proposal is to allow for: (i) design time reliability optimization; (ii) fine tuning of the run-time reliability assessment infrastructure, and (iii) run-time aging assessment. To this end, we propose to select a minimum-size kernel of critical transistors and based on them to assess and predict an IC End-Of-Life (EOL) via two methods: (i) as the sum of the critical transistors end-of-life values, weighted by fixed topology-dependent coefficients, and (ii) by a Markovian framework applied to the critical transistors, which takes into account the joint effects of process, environmental, and temporal variations. The former model exploits the aging dependence on the circuit topology to enable fast run-time reliability assessment with minimum aging sensors requirements. By allowing the performance boundary to vary in time such that both remnant and nonremnant variations are encompassed, and imposing a Markovian evolution, the probabilistic model can be better fitted to various real conditions, thus enabling at design-time appropriate guardbands selection and effective aging mitigation/compensation techniques. The proposed framework has been validated for different stress conditions, under process variations and aging effects, for the ISCAS-85 c499 circuit, in PTM 45 nm technology. From the total of 1526 transistors, we obtained a kernel of 15 critical transistors, for which the set of topology dependent weights were derived. Our simulation results for 15 critical transistors kernel indicate a small approximation error (i.e., mean smaller than 15% and standard deviation smaller than 6%) for the considered circuit estimated end-of-life (EOL), when comparing to the end-of-life values obtained from Cadence simulation, which quantitatively confirm the accuracy of the IC lifetime evaluation. Moreover, as the number of critical transistors determines the area overhead, we also investigated the implications of reducing their number on the reliability assessment accuracy. When only 5 transistors are included into the critical set instead of 15, which results in a 66% area overhead reduction, the EOL estimation accuracy diminished with 18%. This indicates that area vs. accuracy trade-offs are possible, while maintaining the aging prediction accuracy within reasonable bounds.

Dynamical crossovers in Markovian exciton transport

The large deviation theory has recently been applied to open quantum systems to uncover dynamical crossovers in the space of quantum trajectories associated to Markovian evolutions. Such dynamical crossovers are characterized by qualitative changes in the fluctuations of rare quantum jump trajectories, and have been observed in the statistics of coherently driven quantum systems. In this paper we investigate the counting statistics of the rare quantum trajectories of an undriven system undergoing a pure relaxation process, namely, Markovian exciton transport. We find that dynamical crossovers occur in systems with a minimum of three interacting molecules, and are strongly activated by exciton delocalization and interference. Our results illustrate how quantum features of the underlying system Hamiltonian can influence the statistical properties of energy transfer processes in a non-trivial manner.

Quantum Stochastic Cocycles and Completely Bounded Semigroups on Operator Spaces

Quantum stochastic cocycles provide a basic model for time-homogeneous Markovian evolutions in a quantum setting, and a direct counterpart in continuous time to quantum random walks, in both the Schrodinger and Heisenberg pictures. This paper is a sequel to one in which correspondences were established between classes of quantum stochastic cocycle on an operator space or C*-algebra, and classes of Schur-action `global' semigroup on associated matrix spaces over the operator space. In this paper we investigate the stochastic generation of cocycles via the generation of their corresponding global semigroups, with the primary purpose of strengthening the scope of applicability of semigroup theory to the analysis and construction of quantum stochastic cocycles. An explicit description is given of the affine relationship between the stochastic generator of a completely bounded cocycle and the generator of any one of its associated global semigroups. Using this, the structure of the stochastic generator of a completely positive quasicontractive quantum stochastic cocycle on a C*-algebra whose expectation semigroup is norm continuous is derived, giving a comprehensive stochastic generalisation of the Christensen--Evans extension of the GKS&L theorem of Gorini, Kossakowski and Sudarshan, and Lindblad. The transformation also provides a new existence theorem for cocycles with unbounded structure map as stochastic generator. The latter is applied to a model of interacting particles known as the quantum exclusion Markov process, in particular on integer lattices in dimensions one and two.

Characterizing non-Markovian quantum evolution

We analyze classes of legitimate quantum dynamics using a local in time master equation. Markovian dynamics is characterized in terms of a divisible dynamical map. Moreover, we provide a family of criteria which can distinguish Markovian and non-Markovian quantum evolution. They are based on a simple observation that Markovian dynamics implies monotonic behavior of several well-known quantities such as distinguishability of states, fidelity and relative entropy.

On nonautonomous Markov evolutions in continuum

The nonautonomous Cauchy problem in a scale of Banach spaces is investigated. The existence and uniqueness of solutions to this problem is proven. The obtained results are applied to several dynamics of Markov evolutions in continuum (e.g. spatial logistic model, Glauber dynamics, etc.).

Stochastic evolution of a continuum particle system with dispersal and competition

A Markov evolution of a system of point particles in $\mathbb{R}^d$ is described at micro-and mesoscopic levels. The particles reproduce themselves at distant points (dispersal) and die, independently and under the influence of each other (competition). The microscopic description is based on an infinite chain of equations for correlation functions, similar to the BBGKY hierarchy used in the Hamiltonian dynamics of continuum particle systems. The mesoscopic description is based on a Vlasov-type kinetic equation for the particle's density obtained from the mentioned chain via a scaling procedure. The main conclusion of the microscopic theory is that the competition can prevent the system from clustering, which makes its description in terms of densities reasonable. A possible homogenization of the solutions to the kinetic equation in the long-time limit is also discussed.

Simple non-Markovian microscopic models for the depolarizing channel of a single qubit

The archetypal one-qubit noisy channels—depolarizing, phase-damping and amplitude-damping channels—describe both Markovian and non-Markovian evolution. Simple microscopic models for the depolarizing channel, both classical and quantum, are considered. Microscopic models that describe phase-damping and amplitude-damping channels are briefly reviewed.

Monotonicity of the dynamical activity

The Donsker–Varadhan rate function for occupation-time fluctuations has been seen numerically to exhibit monotone return to stationary non-equilibrium (Maes et al 2011 Phys. Rev. Lett. 107 010601). That rate function is related to dynamical activity and, except under detailed balance, it does not derive from the relative entropy for which the monotonicity in time is well understood. We give a rigorous argument that the Donsker–Varadhan function is indeed monotone under the Markov evolution at large enough times with respect to the relaxation time, provided that a ‘normal linear-response’ condition is satisfied.

Decoherence for Quantum Markov Semi-Groups on Matrix Algebras

In this work we describe a necessary and sufficient condition for decoherence of quantum Markov evolutions acting on matrix spaces (according to the definition introduced by Blanchard and Olkiewicz). This condition is related to the spectral analysis of the generator $${\mathcal{L}}$$ of the semigroup and is easily stated: the evolution displays decoherence if and only if the maximal algebra $${\mathcal{N}(\mathcal{T})}$$ on which the semigroup is *-automorphic contains all the eigenvalues of $${\mathcal{L}}$$ associated with eigenvectors with null real part. Moreover, this condition is surely verified when the semigroup admits a faithful invariant state.

Markovian evolution of classical and quantum correlations in transverse-field XY model

The transverse-field XY model in one dimension is a well-known spin model for which the ground state properties and excitation spectrum are known exactly. The model has an interesting phase diagram describing quantum phase transitions (QPTs) belonging to two different universality classes. These are the transverse-field Ising model and the XX model universality classes with both the models being special cases of the transverse-field XY model. In recent years, quantities related to quantum information theoretic measures like entanglement, quantum discord (QD) and fidelity have been shown to provide signatures of QPTs. Another interesting issue is that of decoherence to which a quantum system is subjected due to its interaction, represented by a quantum channel, with an environment. In this paper, we determine the dynamics of different types of correlations present in a quantum system, namely, the mutual information, the classical correlations and the quantum correlations, as measured by the quantum discord, in a two-qubit state. The density matrix of this state is given by the nearest-neighbour reduced density matrix obtained from the ground state of the transverse-field XY model in 1d. We assume Markovian dynamics for the time-evolution due to system-environment interactions. The quantum channels considered include the bit-flip, bit-phase-flip and phase-flip channels. Two different types of dynamics are identified for the channels in one of which the quantum correlations are greater in magnitude than the classical correlations in a finite time interval. The origins of the different types of dynamics are further explained. For the different channels, appropriate quantities associated with the dynamics of the correlations are identified which provide signatures of QPTs. We also report results for further-neighbour two-qubit states and finite temperatures.

A STOCHASTIC MODEL FOR TISSUE CONSISTENCE EVOLUTION BASED ON THE INVERSE PROBLEM

An inverse-stochastic framework is proposed to reproduce the pattern evolution and predict the mechanical properties of a tissue-engineered culture from ultrasonic measurements in an in-vitro culture. A Markovian type of evolution is expected in tissue cultures for mechanical properties such us bulk modulus (K) or attenuation coefficient (AC), under the hypothesis that the future of the process depends only upon its present state, and not upon past states. Additionally a spread in the evolution histories for different repetitions of the same process is expected, consequently stochastic models such us Markov chains [Gallager, 1996] seems to be more suitable. The method proposed is predictive in nature and can be applicable to any measurable biomechanical process, under the assumption that the process shows Markovian evolution.

Turning on the charm

We argue that the strong jet quenching of heavy flavors observed in heavy-ion collisions is to a large extent due to binary scatterings in the quark-gluon plasma. It can be understood from first principles: the charm collision probability beyond logarithmic accuracy and Markov evolution.

Master Equations for Correlated Quantum Channels

We derive the general form of a master equation describing the reduced time evolution of a sequence of subsystems "propagating" in an environment which can be described as a sequence of subenvironments. The interaction between subsystems and subenvironments is described in terms of a collision model, with the irreversible dynamics of the subenvironments between collisions explicitly taken into account. In the weak coupling regime, we show that the collisional model produces a correlated Markovian evolution for the joint density matrix of the multipartite system. The associated Lindblad superoperator contains pairwise terms describing cross correlation between the different subsystems. Such a model can describe a broad range of physical situations, ranging from quantum channels with memory to photon propagation in concatenated quantum optical systems.

Transverse Ising model: Markovian evolution of classical and quantum correlations under decoherence

The transverse Ising Model (TIM) in one dimension is the simplest model which exhibits a quantum phase transition (QPT). Quantities related to quantum information theoretic measures like entanglement, quantum discord (QD) and fidelity are known to provide signatures of QPTs. The issue is less well explored when the quantum system is subjected to decoherence due to its interaction, represented by a quantum channel, with an environment. In this paper we study the dynamics of the mutual information I(ρ AB ), the classical correlations C(ρ AB ) and the quantum correlations Q(ρ AB ), as measured by the QD, in a two-qubit state the density matrix of which is the reduced density matrix obtained from the ground state of the TIM in 1d. The time evolution brought about by system-environment interactions is assumed to be Markovian in nature and the quantum channels considered are amplitude damping, bit-flip, phase-flip and bit-phase-flip. Each quantum channel is shown to be distinguished by a specific type of dynamics. In the case of the phase-flip channel, there is a finite time interval in which the quantum correlations are larger in magnitude than the classical correlations. For this channel as well as the bit-phase-flip channel, appropriate quantities associated with the dynamics of the correlations can be derived which signal the occurrence of a QPT.

A theorem allowing the derivation of deterministic evolution equations from stochastic evolution equations. III The Markovian–non-Markovian mix

The proof of a theorem that allows one to construct deterministic evolution equations from a set, with two subsets, containing two types of discrete stochastic evolution equation is developed. One subset evolves Markovianly and the other non-Markovianly. As an illustrative example, the deterministic evolution equations of quantum electrodynamics are derived from two sets of Markovian and non-Markovian stochastic evolution equations, of different type, after an average over realization, using the theorem. This example shows that deterministic differential equations that contain both first-order and second-order time derivatives can be derived after a Taylor series expansion of the dynamical variables. It is shown that the derivation of such deterministic differential equations can be done by solving a set of linear equations. Two explicit examples, the first containing updating rules that depend on one previous time step and the second containing updating rules that depend on two previous time steps, are given in detail in order to show step by step the linear transformations that allow one to obtain the deterministic differential equations.

Diffusive behavior from a quantum master equation

We study a general class of translation invariant quantum Markov evolutions for a particle on \documentclass[12pt]{minimal}\begin{document}${\mathbb Z}^d$\end{document}Zd. The evolution consists of free flow, interrupted by scattering events. We assume spatial locality of the scattering events and exponentially fast relaxation of the momentum distribution. It is shown that the particle position diffuses in the long time limit. This generalizes standard results about central limit theorems for classical (non-quantum) Markov processes.

Markovian and Non-Markovian Protein Sequence Evolution: Aggregated Markov Process Models

Over the years, there have been claims that evolution proceeds according to systematically different processes over different timescales and that protein evolution behaves in a non-Markovian manner. On the other hand, Markov models are fundamental to many applications in evolutionary studies. Apparent non-Markovian or time-dependent behavior has been attributed to influence of the genetic code at short timescales and dominance of physicochemical properties of the amino acids at long timescales. However, any long time period is simply the accumulation of many short time periods, and it remains unclear why evolution should appear to act systematically differently across the range of timescales studied. We show that the observed time-dependent behavior can be explained qualitatively by modeling protein sequence evolution as an aggregated Markov process (AMP): a time-homogeneous Markovian substitution model observed only at the level of the amino acids encoded by the protein-coding DNA sequence. The study of AMPs sheds new light on the relationship between amino acid-level and codon-level models of sequence evolution, and our results suggest that protein evolution should be modeled at the codon level rather than using amino acid substitution models.

Markov models of amino acid substitution to study proteins with intrinsically disordered regions.

BackgroundIntrinsically disordered proteins (IDPs) or proteins with disordered regions (IDRs) do not have a well-defined tertiary structure, but perform a multitude of functions, often relying on their native disorder to achieve the binding flexibility through changing to alternative conformations. Intrinsic disorder is frequently found in all three kingdoms of life, and may occur in short stretches or span whole proteins. To date most studies contrasting the differences between ordered and disordered proteins focused on simple summary statistics. Here, we propose an evolutionary approach to study IDPs, and contrast patterns specific to ordered protein regions and the corresponding IDRs.ResultsTwo empirical Markov models of amino acid substitutions were estimated, based on a large set of multiple sequence alignments with experimentally verified annotations of disordered regions from the DisProt database of IDPs. We applied new methods to detect differences in Markovian evolution and evolutionary rates between IDRs and the corresponding ordered protein regions. Further, we investigated the distribution of IDPs among functional categories, biochemical pathways and their preponderance to contain tandem repeats.ConclusionsWe find significant differences in the evolution between ordered and disordered regions of proteins. Most importantly we find that disorder promoting amino acids are more conserved in IDRs, indicating that in some cases not only amino acid composition but the specific sequence is important for function. This conjecture is also reinforced by the observation that for of our data set IDRs evolve more slowly than the ordered parts of the proteins, while we still support the common view that IDRs in general evolve more quickly. The improvement in model fit indicates a possible improvement for various types of analyses e.g. de novo disorder prediction using a phylogenetic Hidden Markov Model based on our matrices showed a performance similar to other disorder predictors.

Characterization of decoherence from an environmental perspective

For the case of phase damping (pure decoherence) we investigate the extent to which environmental traits are imprinted on an open quantum system. The dynamics is described using the quantum channel approach. We study what the knowledge of the channel may reveal about the nature of its underlying dynamics and, conversely, what the dynamics tells us about how to consistently model the environment. We find that for a Markov phase-damping channel, that is, a channel compatible with a time-continuous Markovian evolution, the environment may adequately be represented by a mixture of only a few coherent states. For arbitrary Hilbert space dimension $N\geq 4$ we refine the idea of {\it quantum phase damping}, of which we show a means of identification. Symmetry considerations are used to identify decoherence-free subspaces of the system.