Hilbert quantum image scrambling and graph signal processing-based image steganography

Steganography plays a big role in secret communication by concealing secret information in the carrier. This paper presents a graph signal processing-based robust image steganography technique for posting images over social networks. In the embedding, we first obtained a scrambled version of the secret image using quantum scrambling. Next, we applied graph wavelet transformation on both the cover image and scrambled secret image followed by α (alpha) blending on both image signals (cover image signal and scrambled image signal). Finally, inverse graph wavelet transformation of the resulting image was undertaken to obtain the stego image. In this paper, the use of graph wavelet transformation improved interpixel correlation, which resulted in the excellent visual quality of both the stego image and the extracted secret image. Our experiments show that the picture quality of both the cover image and the stego image is exactly the same.

     

GPPR：跨域环境下的个性化PageRank算法

个性化PageRank作为大图分析中的的基本算法,在搜索引擎、社交推荐、社区检测等领域具有广泛的应用,一直是研究者们关注的热点问题.现有的分布式个性化PageRank算法均假设所有数据位于同一地理位置,且数据所在的计算节点之间具有相同的网络环境.然而,在现实世界中,这些数据可能分布在跨洲际的多个数据中心中,这些跨域分布（Geo-Distributed）的数据中心之间通过广域网连接,存在网络带宽异构、硬件差异巨大、通信费用高昂等特点.而分布式个性化PageRank算法需要多轮迭代,并在全局图上进行随机游走.因此,现有的分布式个性化PageRank算法不适用于跨域环境.针对此问题,本研究提出了GPPR（Geo-Distributed Personalized PageRank）算法.该算法首先对跨域环境中的大图数据进行预处理,通过采用启发式算法映射图数据,以降低网络带宽异构对算法迭代速度的影响.其次,GPPR改进了随机游走方式,提出了基于概率的push算法,通过减少工作节点之间传输数据的带宽负载,进一步减少算法所需的迭代次数.我们基于Spark框架实现了GPPR算法,并在阿里云中构建真实的跨域环境,在8个开源大图数据上与现有的多个代表性分布式个性化PageRank算法进行了对比实验.结果显示,GPPR的通信数据量在跨域环境中较其他算法平均减少30%.在算法运行效率方面,GPPR较其他算法平均提升2.5倍.     

Linking Classical and Quantum Key Agreement: Is There a Classical Analog to Bound Entanglement?

Abstract. After carrying out a protocol for quantum key agreement over a noisy quantum channel, the parties Alice and Bob must process the raw key in order to end up with identical keys about which the adversary has virtually no information. In principle, both classical and quantum protocols can be used for this processing. It is a natural question which type of protocol is more powerful. We show that the limits of tolerable noise are identical for classical and quantum protocols in many cases. More specifically, we prove that a quantum state between two parties is entangled if and only if the classical random variables resulting from optimal measurements provide some mutual classical information between the parties. In addition, we present evidence which strongly suggests that the potentials of classical and of quantum protocols are equal in every situation. An important consequence, in the purely classical regime, of such a correspondence would be the existence of a classical counterpart of so-called bound entanglement, namely ``bound information' that cannot be used for generating a secret key by any protocol. This stands in contrast to what was previously believed.     

Continuous-time quantum walks on semi-regular spidernet graphs via quantum probability theory

We analyze continuous-time quantum and classical random walk on spidernet lattices. In the framework of Stieltjes transform, we obtain density of states, which is an efficiency measure for the performance of classical and quantum mechanical transport processes on graphs, and calculate the spacetime transition probabilities between two vertices of the lattice. Then we analytically show that there are two power law decays ∼ t ⁻³ and ∼ t ^−1.5 at the beginning of the transport for transition probability in the continuous-time quantum and classical random walk, respectively. This results illustrate the decay of quantum mechanical transport processes is quicker than that of the classical one. Due to the result, the characteristic time t _c , which is the time when the first maximum of the probabilities occur on an infinite graph, for the quantum walk is shorter than that of the classical walk. Therefore, we can interpret that the quantum transport speed on spidernet is faster than that of the classical one. In the end, we investigate the results by numerical analysis for two examples.     

A quantum Jensen–Shannon graph kernel for unattributed graphs

In this paper, we use the quantum Jensen–Shannon divergence as a means of measuring the information theoretic dissimilarity of graphs and thus develop a novel graph kernel. In quantum mechanics, the quantum Jensen–Shannon divergence can be used to measure the dissimilarity of quantum systems specified in terms of their density matrices. We commence by computing the density matrix associated with a continuous-time quantum walk over each graph being compared. In particular, we adopt the closed form solution of the density matrix introduced in Rossi et al. (2013) 27 and 28 to reduce the computational complexity and to avoid the cumbersome task of simulating the quantum walk evolution explicitly. Next, we compare the mixed states represented by the density matrices using the quantum Jensen–Shannon divergence. With the quantum states for a pair of graphs described by their density matrices to hand, the quantum graph kernel between the pair of graphs is defined using the quantum Jensen–Shannon divergence between the graph density matrices. We evaluate the performance of our kernel on several standard graph datasets from both bioinformatics and computer vision. The experimental results demonstrate the effectiveness of the proposed quantum graph kernel.     

Quantum models of cognition and decision

Abstract

The purpose of this article is to discuss principle ideas of quantum cognition research program, which comprise elements of the formalism of quantum mechanics (mainly Hilbert space theory and quantum probability theory) for modeling human cognition and decision processes. In the opinion of authors of this program, paradox empirical findings in psychological literature may be explained based on concepts of quantum mechanics. Formally, there is described a discrete-time random chain χ which is defined on a finite interval [0, T] and χ(t) can assume only finite number of values. The space H of such processes will be finite-dimensioned. Then some properties and applications of the quantum probability space on H are studied.     

Generating and using truly random quantum states in Mathematica

The problem of generating random quantum states is of a great interest from the quantum information theory point of view. In this paper we present a package for Mathematica computing system harnessing a specific piece of hardware, namely Quantis quantum random number generator (QRNG), for investigating statistical properties of quantum states. The described package implements a number of functions for generating random states, which use Quantis QRNG as a source of randomness. It also provides procedures which can be used in simulations not related directly to quantum information processing.Program summaryProgram title: TRQSCatalogue identifier: AEKA_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKA_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 7924No. of bytes in distributed program, including test data, etc.: 88 651Distribution format: tar.gzProgramming language: Mathematica, CComputer: Requires a Quantis quantum random number generator (QRNG, http://www.idquantique.com/true-random-number-generator/products-overview.html) and supporting a recent version of MathematicaOperating system: Any platform supporting Mathematica; tested with GNU/Linux (32 and 64 bit)RAM: Case dependentClassification: 4.15Nature of problem: Generation of random density matrices.Solution method: Use of a physical quantum random number generator.Running time: Generating 100 random numbers takes about 1 second, generating 1000 random density matrices takes more than a minute.     

Quantum Random Walks in One Dimension

This letter treats the quantum random walk on the line determined by a 2 × 2 unitary matrix U. A combinatorial expression for the mth moment of the quantum random walk is presented by using 4 matrices, P, Q, R and S given by U. The dependence of the mth moment on U and initial qubit state is clarified. A new type of limit theorems for the quantum walk is given. Furthermore necessary and sufficient conditions for symmetry of distribution for the quantum walk is presented. Our results show that the behavior of quantum random walk is striking different from that of the classical ramdom walk. PACS: 03.67.Lx; 05.40.Fb; 02.50.Cw     

Establishing the equivalence between Szegedy’s and coined quantum walks using the staggered model

Coined quantum walks (QWs) are being used in many contexts with the goal of understanding quantum systems and building quantum algorithms for quantum computers. Alternative models such as Szegedy’s and continuous-time QWs were proposed taking advantage of the fact that quantum theory seems to allow different quantized versions based on the same classical model, in this case the classical random walk. In this work, we show the conditions upon which coined QWs are equivalent to Szegedy’s QWs. Those QW models have in common a large class of instances, in the sense that the evolution operators are equal when we convert the graph on which the coined QW takes place into a bipartite graph on which Szegedy’s QW takes place, and vice versa. We also show that the abstract search algorithm using the coined QW model can be cast into Szegedy’s searching framework using bipartite graphs with sinks.     

惰性随机游走视觉显著性检测算法

目的 鉴于随机游走过程对人类视觉注意力的良好描述能力,提出一种基于惰性随机游走的视觉显著性检测算法。方法 首先通过对背景超像素赋予较大的惰性因子,即以背景超像素作为惰性种子节点,在由图像超像素组成的无向图上演化惰性随机游走过程,获得初始显著性图;然后利用空间位置先验及颜色对比度先验信息对初始显著图进行修正;最终通过基于前景的惰性随机游走产生鲁棒的视觉显著性检测结果。结果 为验证算法有效性,在MSRA-1000数据库上进行了仿真实验,并与主流相关算法进行了定性与定量比较。本文算法的Receiver ROC（operating characteristic）曲线及F值均高于其他相关算法。结论 与传统基于随机过程的显著性检测算法相比,普通随机游走过程无法保证收敛到稳定状态,本文算法从理论上有效克服了该问题,提高了算法的适用性;其次,本文算法通过利用视觉转移的往返时间来刻画显著性差异,在生物视觉的模拟上更加合理贴切,与普通随机游走过程采用的单向转移时间相比,效果更加鲁棒。