Zero and first-order phase shift correction for field map estimation with dual-echo GRE using bipolar gradients

A simple phase error correction technique used for field map estimation with a generally available dual-echo gradient-echo (GRE) sequence is presented. Magnetic field inhomogeneity maps estimated using two separate GRE volume acquisitions at different echo times are prone to dynamic motion errors between acquisitions. By using the dual-echo sequence, the data are collected during two back-to-back readout gradients in opposite polarity after a single radio frequency pulse, and interecho motion artifacts and alignment errors in field map estimation can be factored out. Residual phase error from the asymmetric readout pulses is modeled as an affine term in the readout direction. Results from phantom and human data suggest that the first-order phase correction term stays constant over time and, hence, can be applied to different data acquired with the same protocol over time. The zero-order phase correction term may change with time and is estimated empirically for different scans.     

Test models for improving filtering with model errors through stochastic parameter estimation

The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.     

Dynamical noise filter and conditional entropy analysis in chaos synchronization

It is shown that, in a chaotic synchronization system whose driving signal is exposed to channel noise, the estimation of the drive system states can be greatly improved by applying the dynamical noise filtering to the response system states. If the noise is bounded in a certain range, the estimation errors, i.e., the difference between the filtered responding states and the driving states, can be made arbitrarily small. This property can be used in designing an alternative digital communication scheme. An analysis based on the conditional entropy justifies the application of dynamical noise filtering in generating quality synchronization.     

Filtering skill for turbulent signals for a suite of nonlinear and linear extended Kalman filters

The filtering skill for turbulent signals from nature is often limited by errors due to utilizing an imperfect forecast model. In particular, real-time filtering and prediction when very limited or no a posteriori analysis is possible (e.g. spread of pollutants, storm surges, tsunami detection, etc.) introduces a number of additional challenges to the problem. Here, a suite of filters implementing stochastic parameter estimation for mitigating model error through additive and multiplicative bias correction is examined on a nonlinear, exactly solvable, stochastic test model mimicking turbulent signals in regimes ranging from configurations with strongly intermittent, transient instabilities associated with positive finite-time Lyapunov exponents to laminar behavior. Stochastic Parameterization Extended Kalman Filter (SPEKF), used as a benchmark here, involves exact formulas for propagating the mean and covariance of the augmented forecast model including the unresolved parameters. The remaining filters use the same nonlinear forecast model but they introduce model error through different moment closure approximations and/or linear tangent approximation used for computing the second-order statistics of the augmented stochastic forecast model. A comprehensive study of filter performance is carried out in the presence of various moment closure errors which are enhanced by additional model errors due to incorrect parameters inducing additive and multiplicative stochastic biases. The estimation skill of the unresolved stochastic parameters is also discussed and it is shown that the linear tangent filter, despite its popularity, is completely unreliable in many turbulent regimes for both parameter estimation and filtering; moreover, regimes of filter divergence for the linear tangent filter are identified. The results presented here provide useful guidelines for filtering turbulent, high-dimensional, spatially extended systems with more general model errors, as well as for designing more skillful methods for superparameterization of unresolved intermittent processes in complex multi-scale models. They also provide unambiguous benchmarks for the capabilities of linear and nonlinear extended Kalman filters using incorrect statistics on an exactly solvable test bed with rich and realistic dynamics.     

Quantum key distribution with two-qubit quantum codes

We propose a prepare-and-measure scheme for quantum key distribution with two-qubit quantum codes. The protocol is unconditionally secure under all types of intercept-and-resend attack. Given the symmetric and independent errors to the transmitted qubits, our scheme can tolerate a bit of an error rate up to 26% in four-state protocol and 30% in six-state protocol, respectively. These values are higher than all currently known threshold values for the prepare-and-measure protocols. Moreover, we give a practically implementable linear optics realization for our scheme.     

Analysis of bit rate dependence up to 80 Gbit/s of a simple wavelength converter based on XPM in a SOA and a shifted filtering

This paper provides the analysis of wavelength converted pulses obtained with a simple semiconductor optical amplifier (SOA)-based wavelength conversion scheme, which exploits cross phase modulation (XPM) in an SOA in conjunction with shifted filtering. The analysis includes experimental measurements of the back-to-back system performances as well as frequency-resolved optical gating (FROG) characterisations of the wavelength converted pulses. These measurements are implemented at different bit rates up to 80 Gbit/s and for both red and blue-shifted filtering, particularly showing different patterning effect dependencies of red and blue-shifting techniques. This analysis is developed by the addition of a numerical study which corroborates the experimental results. A further understanding of the different performances of red and blue filtering techniques, presented in the literature, can thus be proposed. The placement of the filter to undertake red-shifted filtering (RSF) allows us to achieve very short pulse widths but high bit rate operation is limited by pattern effects. The blue-shifted filtering (BSF) technique shows optimum performance as regards to patterning effects even if the wavelength converted pulses can be larger.     

最优路径搜索压缩感知水声通信信道估计

将信号恢复中最优路径搜索的A*正交匹配追踪(A*Orthogonal Matching Pursuit,A*OMP)伪贪婪算法引入到水声通信信道估计中,可以有效改善正交匹配追踪(OMP)算法容易陷入局部最优的问题,并提出了一种改进型的A*OMP水声信道估计算法。改进了路径初始化方式,同时为了避免过多迭代引起的未知误差,将前后两次迭代残差之差作为停止准则。在正交频分复用(OFDM)通信体制下,对OMP、A*OMP和本文改进方法的估计误差和误比特率进行了仿真对比,随着信噪比的增加,改进方法未出现误差平台,且受导频间隔影响较小。仿真结果表明相对于OMP算法和传统A*OMP算法,在高信噪比下改进方法的估计误差分别降低约2和1个数量级,海试数据结果验证了改进方法的可行性,其误比特率分别平均降低42.0%和4.7%。      

稳健的高精度单矢量传感器测向方法

针对单矢量传感器各通道之间的相位误差引起已有方法测向不准的问题,提出一种对相位误差稳健的高精度测向方法.该测向方法首先利用单矢量传感器接收信号协方差矩阵的主特征向量与其共轭向量做Hadamard积来构造空间谱,实现对水下目标的方位估计;由于Hadamard积消除了相位误差,此估计值与相位误差无关,但存在方位估计模糊。然后利用相位误差的估计值进行解模糊操作,从而得到正确的方位估计。该测向方法的测向性能独立于相位误差,估计精度高。仿真和试验数据处理结果验证了该测向方法对相位误差稳健;在相位误差条件下,其方位估计精度高于平均声强法、CAPON测向方法以及MUSIC测向方法。而且仿真结果表明,该测向方法的测向精度接近克拉美洛下界(CRB)。      

Robust direction-of-arrival estimation method with high accuracy for single vector sensor

The phase errors among the components of a single acoustic vector sensor cause the direction-of-arrival(DOA) estimation error of the existing methods.In order to address this issue,a DOA estimation method is proposed,which is robust to the phase errors.The proposed method first utilizes the Hadamard product of the principal eigenvector of the covariance matrix of the received signal by the single vector sensor and its conjugate vector to construct the spatial spectrum in order to estimate the DOA of the underwater target.Since the Hadamard product eliminates the phase errors,this estimation is independent of the phase errors.However,it is ambiguous.Afterwards,the phase-error estimate is explored to eliminate the ambiguity and get the correct DOA estimate.The proposed method performs independently of the phase errors and obtains high accuracy.The simulation results and the experimental result demonstrate the proposed method is robust to the phase errors.Furthermore,in the presence of the phase errors,it performs better than the average acoustic intensity method,the CAPON method,and the MUSIC method,in terms of estimation accuracy.In addition,the simulation results indicate that the estimation accuracy of the proposed method approaches to the Cramer-Rao bound(CRB).     

Demultiplexing of OTDM-DPSK signals based on a single semiconductor optical amplifier and optical filtering

We propose and demonstrate the use of a single semiconductor optical amplifier (SOA) and optical filtering to time demultiplex tributaries from an optical time division multiplexing-differential phase shift keying (OTDM-DPSK) signal. The scheme takes advantage of the fact that phase variations added to the target channel by cross-phase modulation from the control signal are effectively subtracted in the differential demodulation scheme employed for DPSK signals. Demultiplexing from 80 to 40 Gbit/s is demonstrated with moderate power penalty using an SOA with recovery time twice as long as the bit period at 80 Gbit/s. Large dynamic ranges for the input power and SOA current are experimentally demonstrated. The scheme is expected to be scalable toward higher bit rates.     

Distinguishability and Disturbance in the Quantum Key Distribution Protocol Using the Mean Multi-Kings’ Problem

We introduce a quantum key distribution protocol using mean multi-kings’ problem. Using this protocol, a sender can share a bit sequence as a secret key with receivers. We consider a relation between information gain by an eavesdropper and disturbance contained in legitimate users’ information. In BB84 protocol, such relation is known as the so-called information disturbance theorem. We focus on a setting that the sender and two receivers try to share bit sequences and the eavesdropper tries to extract information by interacting legitimate users’ systems and an ancilla system. We derive trade-off inequalities between distinguishability of quantum states corresponding to the bit sequence for the eavesdropper and error probability of the bit sequence shared with the legitimate users. Our inequalities show that eavesdropper’s extracting information regarding the secret keys inevitably induces disturbing the states and increasing the error probability.     

Useful multiparticle entanglement and sub-shot-noise sensitivity in experimental phase estimation

We experimentally demonstrate a general criterion to identify entangled states useful for the estimation of an unknown phase shift with a sensitivity higher than the shot-noise limit. We show how to exploit this entanglement on the examples of a maximum likelihood as well as of a Bayesian phase estimation protocol. Using an entangled four-photon state we achieve a phase sensitivity clearly beyond the shot-noise limit. Our detailed comparison of methods and quantum states for entanglement enhanced metrology reveals the connection between multiparticle entanglement and sub-shot-noise uncertainty, both in a frequentist and in a Bayesian phase estimation setting.     

Cryptographic robustness of a quantum cryptography system using phase-time coding

A cryptographic analysis is presented of a new quantum key distribution protocol using phase-time coding. An upper bound is obtained for the error rate that guarantees secure key distribution. It is shown that the maximum tolerable error rate for this protocol depends on the counting rate in the control time slot. When no counts are detected in the control time slot, the protocol guarantees secure key distribution if the bit error rate in the sifted key does not exceed 50%. This protocol partially discriminates between errors due to system defects (e.g., imbalance of a fiber-optic interferometer) and eavesdropping. In the absence of eavesdropping, the counts detected in the control time slot are not caused by interferometer imbalance, which reduces the requirements for interferometer stability.     

Phase detection at the quantum limit with multiphoton Mach-Zehnder interferometry

We study a Mach-Zehnder interferometer fed by a coherent state in one input port and vacuum in the other. We explore a Bayesian phase estimation strategy to demonstrate that it is possible to achieve the standard quantum limit independently from the true value of the phase shift and specific assumptions on the noise of the interferometer. We have been able to implement the protocol by using parallel operation of two photon-number-resolving detectors and multiphoton coincidence logic electronics at the output ports of a weakly illuminated Mach-Zehnder interferometer. This protocol is unbiased, saturates the Cramer-Rao phase uncertainty bound, and, therefore, is an optimal phase estimation strategy.     

穿越深海会聚区的声源定位方法研究

基于WKBZ近似深海会聚区预报模型和方位滤波方法建立了穿越会聚区声源运动参数的估计模型，模拟结果表明，方位误差较小时，在前三个会聚区内，目标运动参数估计结果与模拟设定参数符合较好。     

Contrast reversal and enhancement of phase spot array/grid with an intensity-dependent refractive index medium as phase filter

We report on a complete contrast reversal and contrast enhancement of a holographically recorded phase spot array/grid achieved by phase filtering, using an intensity-dependent refractive index medium, zinc tetraphenyl porphyrin as phase filter placed in the Fourier plane of the 4-f imaging system. We show that the contrast enhancement is robust and insensitive to local errors in the phase array and can be used to repair a damaged portion of the input phase array.     

基片缺陷与磁光盘原始误码

分析了基片缺陷导致磁光盘产生原始误码的原因。首次建立了磁光读出光场与基片杂质特性的数学模型，利用数值分析方法研究了读出信号畸变、误码长度与杂质特性的关系。分析结果表明，一定大小的基片杂质是否产生误码，与杂质距记录层的距离、杂质距读写光斑的距离以及读出阈值电平等因素有关。     

Carrier squeezing interferometry: suppressing phase errors from the inaccurate phase shift

The carrier squeezing interferometry algorithm is proposed to retrieve the phase from interferograms with phase shift errors. A linear carrier is introduced in the interferograms, and the image data is rearranged by the squeezing interferometry technology. In the spectrum of the rearranged image, the error lobe and the phase lobe are separated so the error-free phase can be retrieved by filtering. The simulated interferograms with phase shift errors are computed, and the precisions are better than 8.4×10(-4)λ. Its validation is verified by experiments, where a mean precision of 0.0040λ is obtained.     

量子稳定子码的差错纠正与译码网络构建

寻找差错症状与差错算子之间映射关系是量子译码网络的核心内容,也是量子译码网络实现纠错功能的关键.给出了比特翻转差错症状矩阵和相位翻转差错症状矩阵的定义,将任意Pauli差错算子的差错症状表示为比特翻转差错症状矩阵和相位翻转差错症状矩阵的线性组合.研究发现,量子稳定子码的差错症状矩阵由其校验矩阵所决定,从而可将差错症状矩阵与差错算子之间的映射关系转化为校验矩阵与差错算子之间的映射关系,使得所有关于差错症状的分析都可以通过分析其校验矩阵来实现.这与经典线性码的差错症状与奇偶校验矩阵之间的关系类似,因此可以将经 关键词： 稳定子码 校验矩阵 差错症状 Pauli算子     

Phase-Matching Quantum Key Distribution with Discrete Phase Randomization

The twin-field quantum key distribution (TF-QKD) protocol and its variations have been proposed to overcome the linear Pirandola–Laurenza–Ottaviani–Banchi (PLOB) bound. One variation called phase-matching QKD (PM-QKD) protocol employs discrete phase randomization and the phase post-compensation technique to improve the key rate quadratically. However, the discrete phase randomization opens a loophole to threaten the actual security. In this paper, we first introduce the unambiguous state discrimination (USD) measurement and the photon-number-splitting (PNS) attack against PM-QKD with imperfect phase randomization. Then, we prove the rigorous security of decoy state PM-QKD with discrete phase randomization. Simulation results show that, considering the intrinsic bit error rate and sifting factor, there is an optimal discrete phase randomization value to guarantee security and performance. Furthermore, as the number of discrete phase randomization increases, the key rate of adopting vacuum and one decoy state approaches infinite decoy states, the key rate between discrete phase randomization and continuous phase randomization is almost the same.