Sharif Digital Repository

Quantum mechanics imposes a fundamental bound on the minimum time required for the quantum systems to evolve between two states of interest. This bound introduces a limit on the speed of the dynamical evolution of the systems, known as the quantum speed limit. We show that black holes can drastically affect the speed limit of a fermionic quantum system subjected to an open quantum dynamics. As we demonstrate, the quantum speed limit can enhance at the vicinity of a black hole's event horizon in the Schwarzschild spacetime. © 2020 The Author(s)  

We study the dynamics of a macroscopic superconducting qubit coupled to two independent non-stationary reservoirs by using time-dependent perturbation theory. We show that an equilibrium environment surpasses the coherent evolution of the macroscopic qubit completely. When the qubit couples to two different reservoirs, exemplifying a non-equilibrium environment, the short-time dynamics is affected by the interference between two reservoirs, implying the non-additivity of effects of two reservoirs. The non-additivity can be traced back to a non-Markovian effect, even though two reservoirs are independently assumed to be Markovian. Explicitly, the non-equilibrium environment intensifies both... 

In this chapter, we introduce Lévy noise-driven Langevin and fractional Fokker–Planck equations, and derive short-time propagator of the Lévy-driven processes. Then, we provide the details of the limit theorems for the Wiener and Lévy processes. Finally, non-parametric reconstruction of the Lévy-driven Langevin dynamics from time series is described. © 2019, Springer Nature Switzerland AG  

In this chapter, we introduce Lévy noise-driven Langevin and fractional Fokker–Planck equations, and derive short-time propagator of the Lévy-driven processes. Then, we provide the details of the limit theorems for the Wiener and Lévy processes. Finally, non-parametric reconstruction of the Lévy-driven Langevin dynamics from time series is described. © 2019, Springer Nature Switzerland AG  

Network pricing is an effective transportation demand management scheme to reduce traffic and control air pollution, particularly in CBDs. In this study, congested area cordon entry and Park-and-Ride (P/R) facility use are priced for automobiles. Increase in these prices may reduce private auto demand by impelling some of the auto passengers to use public transport from the origin of their trips, or encouraging them to park their cars at the P/R facilities and use buses, or pay the entrance fee and drive inside the cordon. A Markov decision process has been devised to find an optimal policy for pricing the P/R facilities and cordon entry in a city within a variable demand context. This... 

The simultaneous emergence of several abrupt disease outbreaks or the extinction of some serotypes of multistrain diseases are fingerprints of the interaction between pathogens spreading within the same population. Here, we propose a general and versatile benchmark to address the unfolding of both cooperative and competitive interacting diseases. We characterize the explosive transitions between the disease-free and the epidemic regimes arising from the cooperation between pathogens and show the critical degree of cooperation needed for the onset of such abrupt transitions. For the competing diseases, we characterize the mutually exclusive case and derive analytically the transition point... 

We demonstrate that Markov processes play a fundamental role in probing rough surfaces and characterizing their topography. The surface topography obtained by a probe, as in the atomic force microscopy (AFM) technique, is based on the probe-surface interactions. When the size of the probe tip is comparable with the height of the surface fluctuation, the surface image can be aberrated from its origin. Due to the tip effect, there is a crossover in the structure function of the surface. For scales smaller than the Markov length -the minimum length scale over which a process is Markovian - the stochastic function that describes a rough surface is non-Markovian, whereas for length scales larger... 

Let LL be a reversible Markovian generator on a finite set View the MathML sourceV. Relations between the spectral decomposition of LL and subpartitions of the state space View the MathML sourceV into a given number of components which are optimal with respect to min–max or max–min Dirichlet connectivity criteria are investigated. Links are made with higher-order Cheeger inequalities and with a generic characterization of subpartitions given by the nodal domains of an eigenfunction. These considerations are applied to generators whose positive rates are supported by the edges of a discrete cycle ZNZN, to obtain a full description of their spectra and of the shapes of their eigenfunctions, as... 

In an acceptance-sampling plan, where items of an incoming batch of products are inspected one by one, if the number of conforming items between successive non conforming items falls below a lower control threshold, the batch is rejected. If it falls above an upper control threshold, the batch is accepted, and if it lies within the thresholds then the process of inspecting the items continues. The purpose of this article is to develop an optimization model to determine the optimum values of the thresholds such that constraints on the probability of Type I and Type II errors are satisfied. This article starts by developing a Markovian model to derive the expected total cost of the inspection... 

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

We develop an analytical framework for queueing and delay analysis in the case of a number of distinct flows arriving at a network node, where asynchronous partial network coding is applied for an efficient packet transmission. In order to perfectly model and analyze the practical communication networks, the arriving flows are assumed to be general Markovian arrival processes. As a key example, we apply the proposed model to the problem of coded caching in single bottleneck caching networks. In addition, we verify the accuracy of the proposed model through simulations and real trace-driven experiments. © 1967-2012 IEEE  

A fluctuation relation for the heat exchange of an open quantum system under a thermalizing Markovian dynamics is derived. We show that the probability that the system absorbs an amount of heat from its bath, at a given time interval, divided by the probability of the reverse process (releasing the same amount of heat to the bath) is given by an exponential factor which depends on the amount of heat and the difference between the temperatures of the system and the bath. Interestingly, this relation is akin to the standard form of the fluctuation relation (for forward-backward dynamics). We also argue that the probability of the violation of the second law of thermodynamics in the form of the... 

We introduce a dynamical picture, referred to as correlation picture, which connects a correlated bipartite state to its uncorrelated counterpart. This picture allows us to derive an exact dynamical equation for a general open-system dynamics with system-environment correlations included. This exact dynamics is in the form of a Lindblad-like equation even in the presence of initial system-environment correlations. For explicit calculations, we also develop a weak-correlation expansion that allows us to introduce systematic perturbative approximations. This expansion provides approximate master equations that can feature advantages over existing weak-coupling techniques. As a special case, we... 

Manipulation of a quantum system requires the knowledge of how it evolves. To impose that the dynamics of a system becomes a particular target operation (for any preparation of the system), it may be more useful to have an equation of motion for the dynamics itself, rather than the state. Here we develop a Markovian master equation for the process matrix of an open system interacting with a reservoir, which resembles the Lindblad Markovian master equation. We employ this equation to introduce a scheme for optimal local coherent process control at target times and extend the Krotov technique to obtain optimal control. We illustrate utility of this framework through several quantum... 

Let L be a reversible Markovian generator on a finite set V. Relations between the spectral decomposition of L and subpartitions of the state space V into a given number of components which are optimal with respect to min-max or max-min Dirichlet connectivity criteria are investigated. Links are made with higher-order Cheeger inequalities and with a generic characterization of subpartitions given by the nodal domains of an eigenfunction. These considerations are applied to generators whose positive rates are supported by the edges of a discrete cycle Z N, to obtain a full description of their spectra and of the shapes of their eigenfunctions, as well as an interpretation of the spectrum... 

We provide a framework for modeling and analyzing both qualitative and quantitative aspects of mobile ad hoc network (MANET) protocols above the data-link layer. We extend Restricted Broadcast Process Theory [11,9]: delay functions are assigned to actions, while the semantics captures the interplay of a MANET protocol with stochastic behavior of the data-link and physical layer, and the dynamic topology. A continuous-time Markov chain is derived from our semantic model by resolving non-determinism, using the notion of weak Markovian network bisimilarity. The framework is applied to a leader election algorithm