对称噪声信道下利用多纠缠态实现量子密钥分配

研究了对称噪声信道下的量子密钥分配(Quantum Key Distribution,QKD)过程，并得到了其误码率和信道保真度的关系式。基于量子态的局域区分原理，我们提出了使用“多纠缠态”进行噪声信道下的密钥分配的新方案。应用这个新方案，我们可以获得和在理想无噪声信道下使用最大纠缠态(四个Bell态之一)进行QKD一样好的结果。     

正交频分复用无源时间反转信道均衡方法研究

针对水声信道多途信号引起的正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信系统符号间干扰的问题,提出了无源时间反转均衡的方法,将发送的探测信号时间反转与OFDM信号做卷积,利用无源时间反转镜的时间聚焦原理减小信道多途带来的符号间干扰,在OFDM符号中不使用导频的情况下实现信道均衡,简化了均衡步骤并提高了OFDM符号频带利用率。分析比较了无源时反均衡方法与最小平方信道均衡在水声多途信道下的误码性能。仿真研究和湖上实验表明,无源时反信道均衡算法可以有效的减小多途信道对OFDM水声通信系统带来的影响。     

正交频分复用无源时间反转信道均衡方法研究

针对水声信道多途信号引起的正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信系统符号间干扰的问题,提出了无源时间反转均衡的方法,将发送的探测信号时间反转与OFDM信号做卷积,利用无源时间反转镜的时间聚焦原理减小信道多途带来的符号间干扰,在OFDM符号中不使用导频的情况下实现信道均衡,简化了均衡步骤并提高了OFDM符号频带利用率。分析比较了无源时反均衡方法与最小平方信道均衡在水声多途信道下的误码性能。仿真研究和湖上实验表明,无源时反信道均衡算法可以有效的减小多途信道对OFDM水声通信系统带来的影响。      

数字时间相关积累(Ⅰ)——自相关积累

本文论述一种独特的信号处理方式——数字时间相关积累及其在浅海声信道中的应用。共分三部份:(Ⅰ)自相关积累;(Ⅱ)互相关积累;(Ⅲ)抗多途径性能分析。本文(Ⅰ)论述数字自相关积累。首先实验研究了浅水信道中信号和噪声的统计特性,进而讨论了自相关积累的工作原理和基本结构,侧重地估算几种典型声呐系统的虚警概率、检测概率和输入信噪比及其关系。理论估算和实验证明,自相关积累信号处理方式适用于随机时-空变、强多途和高噪声级的复杂浅水信道,对于低速率的情况具有普遍意义。     

利用单个三粒子最大GHZ态或两个EPR态隐形传送任意三粒子GHZ态

提出利用单个三粒子最大Greenberger-Horne-Zeilinger (GHZ)态或两个Einstein-Podolsky-Rosen (EPR)态作为量子信道确定性隐形传送任意三粒子GHZ态的两个方案，并将方案推广至隐形传送任意n(n≥4)粒子GHZ态的情况.讨论了量子信道受噪声影响时隐形传态的保真度.研究发现，当作为量子信道的单个三粒子最大GHZ态受到噪声影响时，隐形传态的保真度仅与量子信道的纠缠度有关，而当作为量子信道的两个EPR态受到噪声影响时，隐形传态的保真度不仅与量子信道的纠缠度有关，还与待传送态的纠缠度有关.所提出的方案具有节省量子信道纠缠资源的特点. 关键词： 隐形传态 三粒子Greenberger-Horne-Zeilinger态 量子逻辑门 保真度     

基于UKF的多用户混沌通信

为克服信道噪声、系统参数误配及多用户干扰对混沌通信系统的影响,本文组合不同的状态空间模型并结合盲提取算法,提出了一种双无先导卡尔曼滤波器 (dual unscented Kalman filter, DUKF),以实现多用户的混沌通信.仿真结果表明,在多输入多输出信道的多用户通信环境下,该算法有较快的收敛速度,并能有效地实现多用户的混沌通信. 关键词： 混沌通信 多输入多输出 双无先导卡尔曼滤波器 盲提取     

可见光通信系统的符号定时偏移估计方法

同步模块作为正交频分复用(OFDM)系统中的关键模块,是数据解调和信道估计的基本前提。由于基于OFDM的可见光通信(VLC)系统对同步误差敏感,符号定时偏移(STO)估计的准确性直接影响系统性能。针对直流偏置光OFDM(DCO-OFDM)系统,提出了一种基于奇偶对称性的符号定时偏移估计方法。该方法通过设计具有奇偶对称结构的训练符号,使其能够产生理想的类脉冲定时度量,从而实现出色的符号定时估计精度。通过计算机仿真测量定时偏移估计的均方根误差(RMSE)、平均绝对误差(MAE)和误码率(BER),以评估所提方法的性能,并与两个基线方法(Park方法和Guerra方法)进行比较。仿真结果表明,这种新的符号定时同步方法在加性高斯白噪声(AWGN)信道和多径衰落信道上均优于上述方法,这验证了该方法在DCO-OFDM系统中的有效性。     

噪声对双势阱玻色-爱因斯坦凝聚体系自俘获现象的影响

研究了对称双势阱玻色-爱因斯坦凝聚体系(BEC)存在均匀噪声或高斯噪声时的自俘获现象.结果发现噪声的存在破坏了自俘获现象的临界行为特征，使得原来约瑟夫森振荡和自俘获之间的临界点变成了一个过渡区域，而且噪声强度越大，这个过渡区域展得越宽.同时发现，对于确定的相互作用强度，当噪声强度增大到一定程度时，相平面会出现混乱，如果这时固定噪声强度增大相互作用强度，相平面中的轨道会重新出现.对纯量子系统加噪声后，自俘获同样不存在临界值，而是存在一个临界区域，且随噪声的增强临界区域会展宽.与平均场近似情况下不同的是，纯量子情况下噪声促进自俘获的产生，且噪声越强自俘获越明显. 关键词： 玻色-爱因斯坦凝聚 自俘获 双势阱 噪声     

一维谐振子势阱中二全同粒子的空间关联

针对一维谐振子势阱中由两个全同粒子组成的体系,假设其空间波函数分别具有以下3种交换对称性:1)没有交换对称性,2)对于交换是反对称情况,3)对于交换是对称情况,讨论了二粒子空间相对位置的分布概率.并由此将量子力学教材中自由粒子情况下的结论推广至一维谐振子束缚态情形,即两个全同粒子无论是处于自由态还是束缚态,在空间波函数交换对称的情况下,两个粒子靠拢的概率最大,而交换反对称情况下,两个粒子靠近(r→0)的概率趋于零.论文结论有助于加深对量子力学中全同粒子交换对称性及其物理效应的理解.     

光源相位噪声对高斯玻色采样的影响

高斯玻色采样是实现量子计算优势的主要途径之一,同时也有望应用于加速稠密子图、量子化学等问题.然而,实验中必不可少的噪声却可能阻碍高斯玻色采样的量子优势.此前的研究主要关注于光子损失和光子非全同噪声.本文通过数值模拟研究了另一种噪声——光源相位噪声对高斯玻色采样的影响.采用蒙特卡罗方法近似计算相位噪声下高斯玻色采样的输出概率分布,发现随着探测光子数的增加,相位噪声带来的误差逐渐加大.同时,相位噪声会导致采样出大概率样本的能力,即HOG (heavy output generation)值显著降低.最后发现,在输入平均光子数相同时,有光子损失的高斯玻色采样相比无损失情形对于相位噪声有更大的容忍性.本文的研究有助于大规模高斯玻色采样中更好地抑制相位噪声.     

Error Exponents of LDPC Codes under Low-Complexity Decoding

This paper deals with the specific construction of binary low-density parity-check (LDPC) codes. We derive lower bounds on the error exponents for these codes transmitted over the memoryless binary symmetric channel (BSC) for both the well-known maximum-likelihood (ML) and proposed low-complexity decoding algorithms. We prove the existence of such LDPC codes that the probability of erroneous decoding decreases exponentially with the growth of the code length while keeping coding rates below the corresponding channel capacity. We also show that an obtained error exponent lower bound under ML decoding almost coincide with the error exponents of good linear codes.     

Mutual Information of Pauli Channels with Correlated Noise

A general formula for the mutual information of the Paufi channels with memory modelled by correlated noise is derived. It is shown that the mutual information depends on the channel shrinking factor, the input state parameter and the channel memory coefficient. The analyses based on the general formula reveal that the entanglement is always a useful resource to enhance the mutual information of some Pauli channels, such as the bit flip channel and the bit-phase flip channel. Our analyses also show that the entanglement is not advantageous to the reliable transmission of classical information for some Pauli channels at any time, such as the phase flip channel and the phase damping channel.     

Entanglement enhanced bit rate over multiple uses of a lossy bosonic channel with memory

We present a study of the achievable rates for classical information transmission via a lossy bosonic channel with memory, using homodyne detection. A comparison with the memoryless case shows that the presence of memory enhances the bit rate if information is encoded in collective states, i.e., states which are entangled over different uses of the channel.     

Feedback in the problem of distinguishing between two nonorthogonal coherent states

Feedback is proposed for distinguishing between two weak coherent states with phases differing by ∼π. The mutual nonorthogonality of such states gives rise to a discrimination error, which can be reduced by using feedback. An optical quantum channel is discussed where the input is classical information encoded in two weak coherent states. For a channel with feedback, the discrimination error probability is calculated, and the mutual entropy that quantifies the fidelity between input and output is evaluated. We find that the use of a feedback loop in a quantum communication channel can increase the mutual entropy when canonical position or photon number is measured.     

Stochastic resonance in Hopfield neural networks for transmitting binary signals

We investigate the stochastic resonance phenomenon in a discrete Hopfield neural network for transmitting binary amplitude modulated signals, wherein the binary information is represented by two stored patterns. Based on the potential energy function and the input binary signal amplitude, the observed stochastic resonance phenomena involve two general noise-improvement mechanisms. A suitable amount of added noise assists or accelerates the switch of the network state vectors to follow input binary signals more correctly, yielding a lower probability of error. Moreover, at a given added noise level, the probability of error can be further reduced by the increase of the number of neurons. When the binary signals are corrupted by external heavy-tailed noise, it is found that the Hopfield neural network with a large number of neurons can outperform the matched filter in the region of low input signal-to-noise ratios per bit.     

On the Non-Adaptive Zero-Error Capacity of the Discrete Memoryless Two-Way Channel

We study the problem of communicating over a discrete memoryless two-way channel using non-adaptive schemes, under a zero probability of error criterion. We derive single-letter inner and outer bounds for the zero-error capacity region, based on random coding, linear programming, linear codes, and the asymptotic spectrum of graphs. Among others, we provide a single-letter outer bound based on a combination of Shannon’s vanishing-error capacity region and a two-way analogue of the linear programming bound for point-to-point channels, which, in contrast to the one-way case, is generally better than both. Moreover, we establish an outer bound for the zero-error capacity region of a two-way channel via the asymptotic spectrum of graphs, and show that this bound can be achieved in certain cases.     

Directed Data-Processing Inequalities for Systems with Feedback

We present novel data-processing inequalities relating the mutual information and the directed information in systems with feedback. The internal deterministic blocks within such systems are restricted only to be causal mappings, but are allowed to be non-linear and time varying, and randomized by their own external random input, can yield any stochastic mapping. These randomized blocks can for example represent source encoders, decoders, or even communication channels. Moreover, the involved signals can be arbitrarily distributed. Our first main result relates mutual and directed information and can be interpreted as a law of conservation of information flow. Our second main result is a pair of data-processing inequalities (one the conditional version of the other) between nested pairs of random sequences entirely within the closed loop. Our third main result introduces and characterizes the notion of in-the-loop (ITL) transmission rate for channel coding scenarios in which the messages are internal to the loop. Interestingly, in this case the conventional notions of transmission rate associated with the entropy of the messages and of channel capacity based on maximizing the mutual information between the messages and the output turn out to be inadequate. Instead, as we show, the ITL transmission rate is the unique notion of rate for which a channel code attains zero error probability if and only if such an ITL rate does not exceed the corresponding directed information rate from messages to decoded messages. We apply our data-processing inequalities to show that the supremum of achievable (in the usual channel coding sense) ITL transmission rates is upper bounded by the supremum of the directed information rate across the communication channel. Moreover, we present an example in which this upper bound is attained. Finally, we further illustrate the applicability of our results by discussing how they make possible the generalization of two fundamental inequalities known in networked control literature.     

Detection of nuclear resonance signals: modification of the receiver operating characteristics using feedback

The performance of a nuclear resonance detection system can be quantified using binary detection theory. Within this framework, signal averaging increases the probability of a correct detection and decreases the probability of a false alarm by reducing the variance of the noise in the average signal. In conjunction with signal averaging, we propose another method based on feedback control concepts that further improves detection performance. By maximizing the nuclear resonance signal amplitude, feedback raises the probability of correct detection. Furthermore, information generated by the feedback algorithm can be used to reduce the probability of false alarm. We discuss the advantages afforded by feedback that cannot be obtained using signal averaging. As an example, we show how this method is applicable to the detection of explosives using nuclear quadrupole resonance.     

Interpreting Social Accounting Matrix (SAM) as an Information Channel

Information theory, and the concept of information channel, allows us to calculate the mutual information between the source (input) and the receiver (output), both represented by probability distributions over their possible states. In this paper, we use the theory behind the information channel to provide an enhanced interpretation to a Social Accounting Matrix (SAM), a square matrix whose columns and rows present the expenditure and receipt accounts of economic actors. Under our interpretation, the SAM’s coefficients, which, conceptually, can be viewed as a Markov chain, can be interpreted as an information channel, allowing us to optimize the desired level of aggregation within the SAM. In addition, the developed information measures can describe accurately the evolution of a SAM over time. Interpreting the SAM matrix as an ergodic chain could show the effect of a shock on the economy after several periods or economic cycles. Under our new framework, finding the power limit of the matrix allows one to check (and confirm) whether the matrix is well-constructed (irreducible and aperiodic), and obtain new optimization functions to balance the SAM matrix. In addition to the theory, we also provide two empirical examples that support our channel concept and help to understand the associated measures.     

Quantum Capacity under Adversarial Quantum Noise: Arbitrarily Varying Quantum Channels

We investigate entanglement transmission over an unknown channel in the presence of a third party (called the adversary), which is enabled to choose the channel from a given set of memoryless but non-stationary channels without informing the legitimate sender and receiver about the particular choice that he made. This channel model is called an arbitrarily varying quantum channel (AVQC). We derive a quantum version of Ahlswede’s dichotomy for classical arbitrarily varying channels. This includes a regularized formula for the common randomness-assisted capacity for entanglement transmission of an AVQC. Quite surprisingly and in contrast to the classical analog of the problem involving the maximal and average error probability, we find that the capacity for entanglement transmission of an AVQC always equals its strong subspace transmission capacity. These results are accompanied by different notions of symmetrizability (zero-capacity conditions) as well as by conditions for an AVQC to have a capacity described by a single-letter formula. In the final part of the paper the capacity of the erasure-AVQC is computed and some light shed on the connection between AVQCs and zero-error capacities. Additionally, we show by entirely elementary and operational arguments motivated by the theory of AVQCs that the quantum, classical, and entanglement-assisted zero-error capacities of quantum channels are generically zero and are discontinuous at every positivity point.