We model a long queue of humans by a continuous-space model in which, when a customer moves forward, they stop a random distance behind the previous customer, but do not move at all if their distance behind the previous customer is below a threshold. The latter assumption leads to " of motion in which only some random number W of customers move. We prove that P(W > k) decreases as order k 1=2 ; in other words, for large k the k’th customer moves on average only once every order k 1=2 service times. A more rened analysis relies on a non-obvious asymptotic relation to the coalescing Brownian motion process; we give a careful outline of such an analysis without attending to all the technical details.
We do not know any previous work on closely related models. In one way, our model could be regarded as a continuum, syncronous-moves analog of the (discrete-space, asynchronous moves) TASEP which has been intensively studied @cite_9 owing to its connections with other statistical physics models. The small literature on such analogs of TASEP (see @cite_0 and citations therein) has focused on ergodic properties for processes on the doubly-infinite line. In another way, our phenomenon could be regarded as analogous to stop-and-go motion in traffic jams, for which realistic models would need to consider both positions and velocities of vehicles, although discrete-space discrete-time synchronous models have also been studied @cite_3 . Academic literature such as @cite_7 studying real world security lines does not address the specific wave" feature studied in this paper.
@cite_0 @cite_9 @cite_7 @cite_3
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We survey research on radiation propagation or ballistic particle motion through media with randomly variable material density, and we investigate the topic with an emphasis on very high spatial frequencies. Our new results are based on a specific variability model consisting of a zero-mean Gaussian scaling noise riding on a constant value that is large enough with respect to the amplitude of the noise to yield overwhelmingly non-negative density. We first generalize known results about sub-exponential transmission from regular functions, which are almost everywhere continuous, to merely “measurable” ones, which are almost everywhere discontinuous (akin to statistically stationary noises), with positively correlated fluctuations. We then use the generalized measure-theoretic formulation to address negatively correlated stochastic media without leaving the framework of conventional (continuum-limit) transport theory. We thus resolve a controversy about recent claims that only discrete-point process approaches can accommodate negative correlations, i.e., anti-clustering of the material particles. We obtain in this case the predicted super-exponential behavior, but it is rather weak. Physically, and much like the alternative discrete-point process approach, the new model applies most naturally to scales commensurate with the inter-particle distance in the material, i.e., when the notion of particle density breaks down due to Poissonian—or maybe not-so-Poissonian—number-count fluctuations occur in the sample volume. At the same time, the noisy structure must prevail up to scales commensurate with the mean-free-path to be of practical significance. Possible applications are discussed. In a recent Physical Review Letters article, propose a simple but compelling discrete-time model of n autonomous agents (i.e., points or particles) all moving in the plane with the same speed but with different headings. Each agent's heading is updated using a local rule based on the average of its own heading plus the headings of its "neighbors." In their paper, provide simulation results which demonstrate that the nearest neighbor rule they are studying can cause all agents to eventually move in the same direction despite the absence of centralized coordination and despite the fact that each agent's set of nearest neighbors change with time as the system evolves. This paper provides a theoretical explanation for this observed behavior. In addition, convergence results are derived for several other similarly inspired models. The Vicsek model proves to be a graphic example of a switched linear system which is stable, but for which there does not exist a common quadratic Lyapunov function. People have always tried to understand natural phenomena. In computer science natural phenomena are mostly used as a source of inspiration for solving various problems in distributed systems such as optimization, clustering, and data processing. In this paper we will give an overview of research in field of computer science where fireflies in nature are used as role models for time synchronization. We will compare two models of oscillators that explain firefly synchronization along with other phenomena of synchrony in nature (e.g., synchronization of pacemaker cells of the heart and synchronization of neuron networks of the circadian pacemaker). Afterwards, we will present Mirollo and Strogatz's pulse coupled oscillator model together with its limitations. As discussed by the authors of the model, this model lacks of explanation what happens when oscillators are nonidentical. It also does not support mobile and faulty oscillators. Finally, it does not take into consideration that in communication among oscillators there are communication delays. Since these limitations prevent Mirollo and Strogatz's model to be used in real-world environments (such as Machine-to-Machine systems), we will sum up related work in which scholars investigated how to modify the model in order for it to be applicable in distributed systems. However, one has to bear in mind that there are usually large differences between mathematical models in theory and their implementation in practice. Therefore, we give an overview of both mathematical models and mechanisms in distributed systems that were designed after them. AbstractIn this paper we propose a continuous-time, dissipative Markov dynamics that asymp-totically drives a network of n-dimensional quantum systems to the set of states that areinvariant under the action of the subsystem permutation group. The Lindblad-type gen-erator of the dynamics is built with two-body subsystem swap operators, thus satisfyinglocality constraints, and preserve symmetric observables. The potential use of the pro-posed generator in combination with local control and measurement actions is illustratedwith two applications: the generation of a global pure state and the estimation of thenetwork size. 1 INTRODUCTION Classical consensus algorithms and the related distributed control problems have recentlygenerated an impressive body of literature, motivated by applications in distributed com-putation and multi-agent coordination, see e.g. [1, 2, 3, 4, 5, 6, 7, 8, 9]. We have recentlyrecast the problem, and a class of algorithms for its solution, as a dynamical symmetriza-tion problem in a group-theoretic framework [10]. This allows to extend the use of simpleand robust algorithms, e.g. of gossip type [11], to new settings and applications. Amongthese, we have studied a quantum version of consensus problems and its applications [12],which can be seen as symmetrization with respect to the subsystem-permutation group, aswell as control methods like quantum dynamical decoupling [13], in which we generally donot have a multipartite structure and symmetrization is attained with respect to other ﬁnitegroups. The emerging dynamics are intrinsically in discrete time, and suitable for sequentialimplementation in dissipative quantum simulators [14].