Lower bound for the security of differential phase shift quantum key distribution against a one-pulse-attack

Quantum key distribution is the art of sharing secret keys between two distant parties, and has attracted a lot of attention due to its unconditional security. Compared with other quantum key distribution protocols, the differential phase shift quantum key distribution protocol has higher efficiency and simpler apparatus. Unfortunately, the uncondi- tional security of differential phase shift quantum key distribution has not been proved. Utilizing the sharp continuity of the von Neuman entropy and some basic inequalities, we estimate the upper bound for the eavesdropper Eve＇s infor- mation. We then prove the lower bound for the security of the differential phase shift quantum key distribution protocol against a one-pulse attack with Devatak-Winter＇s secret key rate formula.

APPROXIMATE REPRESENTATION OF THE p-NORM DISTRIBUTION

In surveying data processing,we generally suppose that the observational errors distribute normally.In this case the method of least squares can give the minimum variance unbiased estimation of the parameters.The method of least squares does not have the character of robustness,so the use of it will become unsuitable when a few measurements inheriting gross error mix with others.We can use the robust estimating methods that can avoid the influence of gross errors.With this kind of method there is no need to know the exact distribution of the observations.But it will cause other difficulties such as the hypothesis testing for estimated parameters when the sample size is not so big.For non_normally distributed measurements we can suppose they obey the p _norm distribution law.The p _norm distribution is a distributional class,which includes the most frequently used distributions such as the Laplace,Normal and Rectangular ones.This distribution is symmetric and has a kurtosis between 3 and -6/5 when p is larger than 1.Using p _norm distribution to describe the statistical character of the errors,the only assumption is that the error distribution is a symmetric and unimodal curve.This method possesses the property of a kind of self_adapting.But the density function of the p _norm distribution is so complex that it makes the theoretical analysis more difficult.And the troublesome calculation also makes this method not suitable for practice.The research of this paper indicates that the p _norm distribution can be represented by the linear combination of Laplace distribution and normal distribution or by the linear combination of normal distribution and rectangular distribution approximately.Which kind of representation will be taken is according to whether the parameter p is larger than 1 and less than 2 or p is larger than 2.The approximate distribution have the same first four order moments with the exact one.It means that approximate distribution has the same mathematical expectation,variance,skewness and kurtosis with p _norm distribution.Because every density function used in the approximate formulae has a simple form,using the approximate density function to replace the p _norm ones will simplify the problems of p _norm distributed data processing obviously.

Formal Difference Analysis and Unification on p-Norm Distribution Density Functions

The cause of the formal difference of p-norm distribution density functions is analyzed, two problems in the deduction of p-norm formulating are improved, and it is proved that two different forms of p-norm distribution density functions are equivalent. This work is useful for popularization and application of the p-norm theory to surveying and mapping.

Inference and Properties of Mixture Two Extreme Lower Bound Distributions

In this paper, we discuss the mixture model of two extreme lower bound distributions. First, some properties we obtain of the model with hazard function are discussed. In addition, the estimates of the unknown parameters via the EM algorithm are obtained. The performance of the findings in the paper is showed by demonstrating some numerical illustrations through Monte Carlo simulation.

Cramer-Rao bound and signal-to-noise ratio gain in distributed coherent aperture radar

This paper studies the estimation performance of the coherent processing parameter （CPP）, including time delay differences and phase synchronization errors among different apertures of the distributed coherent aperture radar （DCAR）. Firstly, three architectures of signal processing in the DCAR are introduced. Secondly, the closed-form Cramer-Rao bound （CRB） of the CPP estimation is derived and compared. Then, the closed-form CRB is verified by numerical simulations. Finally, when the next generation radar works in a fully coherent mode, the closed-form signal-to-noise ratio （SNR） gain of the three architectures is presented.

SPECTRUM DISTRIBUTION OF THE SEDOND ORDER GENERALIZED DISTRIBUTED PARAMETER SYSTEMS

Spectrum distribution of the second order generalized distributed parameter system was discussed via the functional analysis and operator theory in Hilbert space. The solutions of the problem and the constructive expression of the solutions are given by the generalized inverse one of bounded linear operator. This is theoretically important for studying the stabilization and asymptotic stability of the second order generalized distributed parameter system.

Countermeasure against probabilistic blinding attack in practical quantum key distribution systems

In a practical quantum key distribution（QKD） system, imperfect equipment, especially the single-photon detector,can be eavesdropped on by a blinding attack. However, the original blinding attack may be discovered by directly detecting the current. In this paper, we propose a probabilistic blinding attack model, where Eve probabilistically applies a blinding attack without being caught by using only an existing intuitive countermeasure. More precisely, our countermeasure solves the problem of how to define the bound in the limitation of precision of current detection, and then we prove security of the practical system by considering the current parameter. Meanwhile, we discuss the bound of the quantum bit error rate（QBER） introduced by Eve, by which Eve can acquire information without the countermeasure.

Security of biased BB84 quantum key distribution with finite resource

In the original BB84 quantum key distribution protocol, the states are prepared and measured randomly, which lose the unmatched detection results. To improve the sifting efficiency, biased bases selection BB84 protocol is proposed. Meanwhile, a practical quantum key distribution protocol can only transmit a finite number of signals, resulting in keys of finite length. The previous techniques for finite-key analysis focus mainly on the statistical fluctuations of the error rates and yields of the qubits. However, the prior choice probabilities of the two bases also have fluctuations by taking into account the finite-size effect. In this paper, we discuss the security of biased decoy state BB84 protocol with finite resources by considering all of the statistical fluctuations. The results can be directly used in the experimental realizations.

Extinction and Stationary Distribution of a Stochastic SIR Epidemic Model with Jumps

A stochastic susceptible-infective-recovered(SIR)epidemic model with jumps was considered.The contributions of this paper are as follows.(1) The stochastic differential equation(SDE)associated with the model has a unique global positive solution;(2) the results reveal that the solution of this epidemic model will be stochastically ultimately bounded,and the non-linear SDE admits a unique stationary distribution under certain parametric conditions;(3) the coefficients play an important role in the extinction of the diseases.

Improved Berry-Esseen Bound for Rademacher Sum

Let X=Σ_(i=1)^(n)a_(i)ξ_(i)be a Rademacher sum with Var(X)=1 and Z be a standard normal random variable.This paper concerns the upper bound of|P(X≤x)−P(Z≤x)|for any x∈R.Using the symmetric properties and R software,this paper gets the following improved Berry-Esseen type bound under some conditions,|P(X≤x)−P(Z≤x)|≤P(Z∈(0,a1)),∀x∈R,which is one of the modified conjecture proposed by Nathan K.and Ohad K.

Optimal subcarrier allocation for cognitive radio with multi-user OFDM and distributed antenna

The subcarrier allocation problem in cognitive radio（CR）networks with multi-user orthogonal frequency-division multiplexing（OFDM）and distributed antenna is analyzed and modeled for the flat fading channel and the frequency selective channel,where the constraint on the secondary user（SU）to protect the primary user（PU）is that the total throughput of each PU must be above the given threshold instead of the ＂interference temperature＂.According to the features of different types of channels,the optimal subcarrier allocation schemes are proposed to pursue efficiency（or maximal throughput）,using the branch and bound algorithm and the 0-1 implicit enumeration algorithm.Furthermore,considering the tradeoff between efficiency and fairness,the optimal subcarrier allocation schemes with fairness are proposed in different fading channels,using the pegging algorithm.Extensive simulation results illustrate the significant performance improvement of the proposed subcarrier allocation schemes compared with the existing ones in different scenarios.

ESTIMATION OF CARRIER FREQUENCY OFFSETS FOR MIMO SYSTEMS WITH DISTRIBUTED TRANSMIT ANTENNAS

The problem of estimating the carrier frequency offsets in Multiple-Input Multiple-Output (MIMO) systems with distributed transmit antennas is addressed. It is supposed that the transmit antennas are distributed while the receive antennas are still centralized, and the general case where both the time delays and the frequency offsets are possibly different for each transmit antenna is considered. The channel is supposed to be frequency flat, and the macroscopic fading is also taken into consideration. A carrier frequency offset estimator based on Maximum Likelihood (ML) is proposed, which can separately estimate the frequency offset for each transmit antenna and exploit the spatial diversity. The Cramer-Rao Bound (CRB) for synchronous MIMO (i.e., the time delays for each transmit antenna are all equal) is also derived. Simulation results are given to illustrate the per- formance of the estimator and compare it with the CRB. It is shown that the estimator can provide satisfactory frequency offset estimates and its performance is close to the CRB for the Signal-to-Noise Ratio (SNR) below 20dB.

Dynamic Relay Selection Method for Distributed MIMO Relay System

The research on distributed MIMO relay system has been attracting much attention. In this paper, a decode-and-forward scheme distributed MIMO relay system is examined. For upper bound of channel capacity, the distance between transceivers is optimized when the propagation loss is brought close to actuality. Additionally, the number of relay is optimized whether total antenna element is fixed or not. When the number of relay is assumed to be infinite, the dynamic relay selection method based on the transmission rate is proposed. We represent that with the proposed method, the transmit power and the number of relays are saving.

An efficient distributed algorithm for game tree search

This paper presents a distributed game tree search algorithm called DDS. Based on communication overhead, st,orage requirement, speed up, and oiller factors, the performance of algorithm DDS* is analysed, and the number of nodes searched with SSS as well as a-b algorithm. The simulation test shows that. DDS* is an efficient and practical search algorithm.

P-norm Semi-parametric Maximum Likelihood Regression Model

In this paper, using the kernel weight function, we obtain the parameter estimation of p-norm distribution in semi-parametric regression model, which is effective to decide the distribution of random errors. Under the assumption that the distribution of observations is unimodal and symmetry, this method can give the estimates of the parametric. Finally, two simulated adjustment problem are constructed to explain this method. The new method presented in this paper shows an effective way of solving the problem; the estimated values are nearer to their theoretical ones than those by least squares adjustment approach.

New results on the robust stability analysis of neural networks with discrete and distributed time delays

Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples.

基于深度学习的实例分割边界框回归方法研究

针对实例分割任务中图像中可能出现相互遮挡或边缘模糊导致边界框定位不准确的问题,本文提出了一种新的边界框回归损失函数。将边界框位置预测转化为估计定位置信度随位置变化的概率分布;考虑坐标点间存在联系,提出一种面积差计算方法;为了证明此方法可以很好地应用于先检测后分割的实例分割模型,本文使用Mask R-CNN作为基线。实验结果表明:在边界框检测及实例分割任务中,本文方法的精度优于其他方法,对于小物体的检测与分割效果更显著,训练和评估速度也更快。

非理想检测下多雷达网络节点选择与辐射资源联合优化分配算法

该文针对分布式相控阵多雷达网络的多目标跟踪场景,研究非理想检测条件下的节点选择与辐射资源联合优化分配算法。首先,根据分布式相控阵多雷达网络构成、目标运动模型、雷达量测模型以及雷达节点检测情况,推导非理想检测下以雷达节点选择、辐射功率和信号带宽为变量的贝叶斯克拉默-拉奥下界(BCRLB)闭式解析表达式,并以此作为多目标跟踪精度衡量指标。在此基础上,以最小化系统各雷达节点对所有目标的总辐射功率为优化目标,以满足目标跟踪精度门限以及给定的系统射频辐射资源限制为约束条件,建立非理想检测条件下多雷达网络节点选择与辐射资源联合优化分配模型,对各时刻雷达节点选择、辐射功率和信号带宽等参数进行联合优化设计,以提升多雷达网络的射频隐身性能。最后,针对上述非线性、非凸优化问题,采用基于障碍函数法和循环最小化算法的4步分解算法进行求解。仿真结果表明,与现有算法相比,所提算法能在满足给定多目标跟踪精度的条件下有效降低分布式相控阵多雷达网络的总辐射功率,至少降低了约32.3%,从而提升其射频隐身性能。

近库仑势垒能区^(7)Li+^(207)Pb体系光学势的阈异常现象

对于紧束缚核反应体系,光学势在近库仑势垒能区呈阈异常的现象。对于弱束缚核(如^(6)Li、9Be和6He)参与的反应,光学势呈反常的阈异常现象。然而,对于弱束缚核^(7)Li参与的反应,光学势行为仍存在争议。为此,本工作在近垒和深垒能区高精度测量了^(7)Li+^(207)Pb体系的弹性散射角分布,采用光学模型拟合并抽取了势参数,结果显示出阈异常的现象。此外,由深垒能区的数据确定了^(7)Li+^(207)Pb体系的反应阈值,约0.82VB(库仑势垒高度),介于典型紧束缚核16O+208Pb体系的0.93VB和弱束缚核^(6)Li+232Th体系的0.73VB之间。这意味着反应阈和破裂阈之间可能存在着关联,值得进一步研究。

Bounding surface model for ballast with additional attention on the evolution of particle size distribution

Particle size distribution significantly influences the mechanical response of the ballast under low confining pressure.However,particle breakage usually occurs and unfavorably degrades the particle size distribution of the ballast when sufficient load is applied.To model the triaxial stress-strain behavior and its associated evolution of particle size distribution of the ballast,a specific bounding surface model is proposed.The proposed model is based on the traditional bounding surface plasticity and a modified particle breakage index,which correlates the initial gradation and the ultimate gradation together with the current gradation.Simulation of the experimental results from the triaxial compression tests shows that the proposed model can predict the strain softening and volumetric expansion of the ballast under relatively lower confining pressure.It is also able to simulate the strain hardening and volumetric compression of the ballast under relatively higher confining pressure.Most importantly,the proposed approach was observed to have a great potential in predicting the evolution of the particle size distribution of the ballast.