Continuous-time symmetric Hopfield nets are computationally universal

We establish a fundamental result in the theory of computation by continuous-time dynamical systems by showing that systems corresponding to so-called continuous-time symmetric Hopfield nets are capable of general computation. As is well known, such networks have very constrained Lyapunov-function controlled dynamics. Nevertheless, we show that they are universal and efficient computational devices, in the sense that any convergent synchronous fully parallel computation by a recurrent network of n discrete-time binary neurons, with in general asymmetric coupling weights, can be simulated by a symmetric continuous-time Hopfield net containing only 18n + 7 units employing the saturated-linear activation function. Moreover, if the asymmetric network has maximum integer weight size w(max) and converges in discrete time t*, then the corresponding Hopfield net can be designed to operate in continuous time Theta(t*/epsilon) for any epsilon > 0 such that w(max)2(12n) 相似文献   

Efficiency of open quantum walk implementation of dissipative quantum computing algorithms

An open quantum walk formalism for dissipative quantum computing is presented. The approach is illustrated with the examples of the Toffoli gate and the Quantum Fourier Transform for 3 and 4 qubits. It is shown that the algorithms based on the open quantum walk formalism are more efficient than the canonical dissipative quantum computing approach. In particular, the open quantum walks can be designed to converge faster to the desired steady state and to increase the probability of detection of the outcome of the computation.     

Laplacian versus adjacency matrix in quantum walk search

A quantum particle evolving by Schrödinger’s equation contains, from the kinetic energy of the particle, a term in its Hamiltonian proportional to Laplace’s operator. In discrete space, this is replaced by the discrete or graph Laplacian, which gives rise to a continuous-time quantum walk. Besides this natural definition, some quantum walk algorithms instead use the adjacency matrix to effect the walk. While this is equivalent to the Laplacian for regular graphs, it is different for non-regular graphs and is thus an inequivalent quantum walk. We algorithmically explore this distinction by analyzing search on the complete bipartite graph with multiple marked vertices, using both the Laplacian and adjacency matrix. The two walks differ qualitatively and quantitatively in their required jumping rate, runtime, sampling of marked vertices, and in what constitutes a natural initial state. Thus the choice of the Laplacian or adjacency matrix to effect the walk has important algorithmic consequences.     

A review on quantum search algorithms

The use of superposition of states in quantum computation, known as quantum parallelism, has significant advantage in terms of speed over the classical computation. It is evident from the early invented quantum algorithms such as Deutsch’s algorithm, Deutsch–Jozsa algorithm and its variation as Bernstein–Vazirani algorithm, Simon algorithm, Shor’s algorithms, etc. Quantum parallelism also significantly speeds up the database search algorithm, which is important in computer science because it comes as a subroutine in many important algorithms. Quantum database search of Grover achieves the task of finding the target element in an unsorted database in a time quadratically faster than the classical computer. We review Grover’s quantum search algorithms for a singe and multiple target elements in a database. The partial search algorithm of Grover and Radhakrishnan and its optimization by Korepin called GRK algorithm are also discussed.     

A quantum walk on the half line with a particular initial state

Quantum walks are considered to be quantum counterparts of random walks. They show us impressive probability distributions which are different from those of random walks. That fact has been precisely proved in terms of mathematics and some of the results were reported as limit theorems. When we analyze quantum walks, some conventional methods are used for the computations; especially, the Fourier analysis has played a role to do that. It is, however, compatible with some types of quantum walks (e.g., quantum walks on the line with a spatially homogeneous dynamics) and cannot well work on the derivation of limit theorems for all the quantum walks. In this paper, we try to obtain a limit theorem for a quantum walk on the half line by the usage of the Fourier analysis. Substituting a quantum walk on the line for it, we will lead to a possibility that the Fourier analysis is useful to compute a limit distribution of the quantum walk on the half line.     

Comparing classical and quantum PageRanks

Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker’s probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.     

Emulation of n−trailer Systems through Differentially Driven Multi-Agent Systems: Continuous- and Discrete- Time Approaches

This paper proposes the emulation of a physical standard or generalized n?trailer through the decentralized control of a multi-agent system composed of several differentially driven mobile robots. The key point is to solve a time-varying version of the well known formation tracking or marching problem. The problem is solved both in discrete- and continuous-time cases. Four different control laws are proposed which require different variables to be available for feedback or feedforward, depending on the specifications of the experimental platform. The performance of the proposed control laws is illustrated through real-time experiments. It is shown that the discrete-time control law exhibits a performance comparable to that of the continuous-time control law with a sampling period 20 times larger than the one used in the continuous-time experiment.     

Generalized teleportation by quantum walks

We develop a generalized teleportation scheme based on quantum walks with two coins. For an unknown qubit state, we use two-step quantum walks on the line and quantum walks on the cycle with four vertices for teleportation. For any d-dimensional states, quantum walks on complete graphs and quantum walks on d-regular graphs can be used for implementing teleportation. Compared with existing d-dimensional states teleportation, prior entangled state is not required and the necessary maximal entanglement resource is generated by the first step of quantum walk. Moreover, two projective measurements with d elements are needed by quantum walks on the complete graph, rather than one joint measurement with \(d^2\) basis states. Quantum walks have many applications in quantum computation and quantum simulations. This is the first scheme of realizing communicating protocol with quantum walks, thus opening wider applications.     

Time-optimal control for discrete-time hybrid automata

In this paper, the problem of time-optimal control for hybrid systems with discrete-time dynamics is considered. The hybrid controller steers all trajectories starting from a maximal set to a given target set in minimum time. We derive an algorithm that computes this maximal winning set. Also, algorithms for the computation of level sets associated with the value function rather than the value function itself are presented. We show that by solving the reachability problem for the discrete time hybrid automata we obtain the time optimal solution as well. The control synthesis is subject to hard constraints on both control inputs and states. For linear discrete-time dynamics, linear programming and quantifier elimination techniques are employed for the backward reachability analysis. Emphasis is given on the computation of operators for non-convex sets using an extended convex hull approach. A two-tank example is considered in order to demonstrate the techniques of the paper.     

Frequency-domain identification of continuous-time ARMA models from sampled data

The subject of this paper is the direct identification of continuous-time autoregressive moving average (CARMA) models. The topic is viewed from the frequency domain perspective which then turns the reconstruction of the continuous-time power spectral density (CT-PSD) into a key issue. The first part of the paper therefore concerns the approximate estimation of the CT-PSD from uniformly sampled data under the assumption that the model has a certain relative degree. The approach has its point of origin in the frequency domain Whittle likelihood estimator. The discrete- or continuous-time spectral densities are estimated from equidistant samples of the output. For low sampling rates the discrete-time spectral density is modeled directly by its continuous-time spectral density using the Poisson summation formula. In the case of rapid sampling the continuous-time spectral density is estimated directly by modifying its discrete-time counterpart.     

基于连续时间量子游走的链路预测方法研究*

链路预测是复杂网络研究的基础问题之一。目前研究者们已经提出了许多链路预测的方法,其中大量的链路预测方法是基于经典随机游走。量子游走是经典随机游走的量子模拟。大量研究表明,在诸如图匹配、搜索等很多领域,基于量子游走的量子算法的性能远优于其对应的经典随机游走算法。但目前关于基于量子游走的链路预测算法几乎没有研究报道。本文提出了一种基于连续时间量子游走的链路预测方法。实验结果表明,连续时间量子游走链路预测结果的AUC值和经典随机游走的结果非常接近。而在Precision和Recall指标上,远优于经典随机游走的链路预测结果。     

A survey of distributed optimization

In distributed optimization of multi-agent systems, agents cooperate to minimize a global function which is a sum of local objective functions. Motivated by applications including power systems, sensor networks, smart buildings, and smart manufacturing, various distributed optimization algorithms have been developed. In these algorithms, each agent performs local computation based on its own information and information received from its neighboring agents through the underlying communication network, so that the optimization problem can be solved in a distributed manner. This survey paper aims to offer a detailed overview of existing distributed optimization algorithms and their applications in power systems. More specifically, we first review discrete-time and continuous-time distributed optimization algorithms for undirected graphs. We then discuss how to extend these algorithms in various directions to handle more realistic scenarios. Finally, we focus on the application of distributed optimization in the optimal coordination of distributed energy resources.     

An overview of quantum cellular automata

Quantum cellular automata are arrays of identical finite-dimensional quantum systems, evolving in discrete-time steps by iterating a unitary operator G. Moreover the global evolution G is required to be causal (it propagates information at a bounded speed) and translation-invariant (it acts everywhere the same). Quantum cellular automata provide a model/architecture for distributed quantum computation. More generally, they encompass most of discrete-space discrete-time quantum theory. We give an overview of their theory, with particular focus on structure results; computability and universality results; and quantum simulation results.

     

A state-space approach to optimum postfiltering of sampled data

In this paper, we apply state-space techniques to the problem of reconstructing a random continuous-time waveform from its discrete-time samples. The optimal zero-lag filter that accomplishes this is well known, but to our knowledge the smoothing problem has not been previously considered in this context. We develop smoothing algorithms in the mixed-time framework appropriate to the interpolation problem, and then compare our results with those obtained previously in discrete time. Our results are related to those previously obtained in a simple and intuitive way, and the required computations are straightforward modifications of those described previously for purely discrete and purely continuous time.     

Nonlinear regulation: The piecewise linear approach

This paper approaches nonlinear control problems through the use of (discrete-time) piecewise linear systems. These are systems whose next-state and output maps are both described by PL maps, i.e., by maps which are affine on each of the components of a finite polyhedral partition. Various results on state and output feedback, observers, and inverses, standard for linear systems, are proved for PL systems. Many of these results are then used in the study of more general (both discrete- and continuous-time) systems, using suitable approximations.     

One-dimensional discrete-time quantum walks on random environments

We consider discrete-time nearest-neighbor quantum walks on random environments in one dimension. Using the method based on a path counting, we present both quenched and annealed weak limit theorems for the quantum walk.     

Spatial search by continuous-time quantum walk with multiple marked vertices

In the typical spatial search problems solved by continuous-time quantum walk, changing the location of the marked vertices does not alter the search problem. In this paper, we consider search when this is no longer true. In particular, we analytically solve search on the “simplex of \(K_M\) complete graphs” with all configurations of two marked vertices, two configurations of \(M+1\) marked vertices, and two configurations of \(2(M+1)\) marked vertices, showing that the location of the marked vertices can dramatically influence the required jumping rate of the quantum walk, such that using the wrong configuration’s value can cause the search to fail. This sensitivity to the jumping rate is an issue unique to continuous-time quantum walks that does not affect discrete-time ones.     

离散时间系统零动态的研究现状和未来挑战

在数字控制系统的分析与设计中, 零动态是一个被广泛关注的重要概念, 近年来取得了诸多新的理论与方法进展. 本文首先描述了离散时间系统零动态理论的研究背景和研究意义, 同时简要介绍了离散时间系统零动态理论所涉及到的3个相关问题, 如: 信号的采样与重建、连续时间系统的等价离散时间系统模型以及在离散连续时间系统过程中所需要的工具(q算子和±算子). 其次, 立足现有文献, 针对离散零动态的特点, 从线性离散时间系统和非线性离散时间系统两个方面全面而深入地介绍了近年来离散零动态研究工作的进展. 最后分析了零动态在数字控制系统分析与设计中的局限性以及出现的挑战性课题, 并指明未来工作的研究方向.     

Time averaged distribution of a discrete-time quantum walk on the path

The discrete time quantum walk which is a quantum counterpart of random walk plays important roles in the theory of quantum information theory. In the present paper, we focus on discrete time quantum walks viewed as quantization of random walks on the path. We obtain a weak limit theorem for the time averaged distribution of our quantum walks.