Fast implementation of length-adaptive privacy amplification in quantum key distribution

Post-processing is indispensable in quantum key distribution （QKD）, which is aimed at sharing secret keys between two distant parties. It mainly consists of key reconciliation and privacy amplification, which is used for sharing the same keys and for distilling unconditional secret keys. In this paper, we focus on speeding up the privacy amplification process by choosing a simple multiplicative universal class of hash functions. By constructing an optimal multiplication algorithm based on four basic multiplication algorithms, we give a fast software implementation of length-adaptive privacy amplification. ＂Length-adaptive＂ indicates that the implementation of privacy amplification automatically adapts to different lengths of input blocks. When the lengths of the input blocks are 1 Mbit and 10 Mbit, the speed of privacy amplification can be as fast as 14.86 Mbps and 10.88 Mbps, respectively. Thus, it is practical for GHz or even higher repetition frequency QKD systems.

An Adaptive Time-Step Backward Differentiation Algorithm to Solve Stiff Ordinary Differential Equations: Application to Solve Activated Sludge Models

A backward differentiation formula (BDF) has been shown to be an effective way to solve a system of ordinary differential equations (ODEs) that have some degree of stiffness. However, sometimes, due to high-frequency variations in the external time series of boundary conditions, a small time-step is required to solve the ODE system throughout the entire simulation period, which can lead to a high computational cost, slower response, and need for more memory resources. One possible strategy to overcome this problem is to dynamically adjust the time-step with respect to the system’s stiffness. Therefore, small time-steps can be applied when needed, and larger time-steps can be used when allowable. This paper presents a new algorithm for adjusting the dynamic time-step based on a BDF discretization method. The parameters used to dynamically adjust the size of the time-step can be optimally specified to result in a minimum computation time and reasonable accuracy for a particular case of ODEs. The proposed algorithm was applied to solve the system of ODEs obtained from an activated sludge model (ASM) for biological wastewater treatment processes. The algorithm was tested for various solver parameters, and the optimum set of three adjustable parameters that represented minimum computation time was identified. In addition, the accuracy of the algorithm was evaluated for various sets of solver parameters.

Adaptive frame length algorithm for inter-satellite links

In view of the low ranging efficiency of the conventional fixed frame-length algorithm in the inter-satellite link,an adaptive frame-length algorithm is proposed. The frame length is adjusted adaptively according to the results of ranging and velocity measuring to improve ranging efficiency. Buffers which enable the frame length to be selected discretely and adaptively are introduced to avoid frequent hopping of the frame-length.Frame length marker is created to automatically identify the frame-length for frame synchronization procedures in receivers. The feasibility and the validity of the proposed algorithm to improve the efficiency of ranging are verified through both theoretic analysis and simulation,and the efficiency improves up to 88% when there are five buffers. This improvement can be further enhanced by increasing the number of buffers. Proper allocation of inter-satellite buffers is required to make a balance between the ranging efficiency and the system complexity.

Adaptive smoothing length method based on weighted average of neighboring particle density for SPH fluid simulation

Background In the smoothed particle hydrodynamics(SPH)fluid simulation method,the smoothing length affects not only the process of neighbor search but also the calculation accuracy of the pressure solver.Therefore,it plays a crucial role in ensuring the accuracy and stability of SPH.Methods In this study,an adaptive SPH fluid simulation method with a variable smoothing length is designed.In this method,the smoothing length is adaptively adjusted according to the ratio of the particle density to the weighted average of the density of the neighboring particles.Additionally,a neighbor search scheme and kernel function scheme are designed to solve the asymmetry problems caused by the variable smoothing length.Results The simulation efficiency of the proposed algorithm is comparable to that of some classical methods,and the variance of the number of neighboring particles is reduced.Thus,the visual effect is more similar to the corresponding physical reality.Conclusions The precision of the interpolation calculation performed in the SPH algorithm is improved using the adaptive-smoothing length scheme;thus,the stability of the algorithm is enhanced,and a larger timestep is possible.

Optimal Time-Frequency Atom Search Based on Adaptive Genetic Algorithm

Adaptive signal decomposition is an important signal processing method.The chirp-based signal representation,for example,the Gaussian chirplet decomposition,has been an active research topic in the field of signal processing.A main challenge of the Gaussian chirplet decomposition is the numerical implementation of the matching pursuit,which is an adaptive signal decomposition scheme,and the challenge remains an open research topic.In this paper,a new optimal time-frequency atom search method based on the adaptive genetic algorithm is proposed,aiming to the low precision problem of the traditional methods.Firstly,a discrete formula of finite length time-frequency atom sequence is derived.Secondly,an algorithm based on the adaptive genetic algorithm is described in detail.Finally,a simulation is carried out,and the result displays its validity and stability.

Development of a Balanced Adaptive Time‑Stepping Strategy Based on an Implicit JFNK‑DG Compressible Flow Solver

A balanced adaptive time-stepping strategy is implemented in an implicit discontinuous Galerkin solver to guarantee the temporal accuracy of unsteady simulations.A proper relation between the spatial,temporal and iterative errors generated within one time step is constructed.With an estimate of temporal and spatial error using an embedded RungeKutta scheme and a higher order spatial discretization,an adaptive time-stepping strategy is proposed based on the idea that the time step should be the maximum without obviously infuencing the total error of the discretization.The designed adaptive time-stepping strategy is then tested in various types of problems including isentropic vortex convection,steady-state fow past a fat plate,Taylor-Green vortex and turbulent fow over a circular cylinder at Re=3900.The results indicate that the adaptive time-stepping strategy can maintain that the discretization error is dominated by the spatial error and relatively high efciency is obtained for unsteady and steady,well-resolved and under-resolved simulations.

Use of Delayed Channel Estimation Results in Adaptive Modulation

In this paper,potential use of perfect but delayed channel estimates for variable-power discrete-rate adaptive modulation is explored.Research is concentrated on block by block adaptation.At first,a new quantity-TAUD(Tolerable Average Use Delay)is defined,it quantifies the performance of an adaptation scheme in tolerating the delay of channel estimates.Then,the research on TAUD shows that the delay tolerating performance declines with the increase in average power,the scheme working with more modulation modes can tolerate a longer delay,and such improvement will be more significant with the increase of average power.Finally,it shows that,as the delay tolerating performance determines the maximum block length,it has a great effect on the maximum spectral efficiency.The criterion for determining the block length appropriate for the target BER is described and a simple method of calculating the maximum block length is presented.

ADAPTIVE STRATEGIES FORNC MACHINING COMPOUND FREE-FORM SURFACES

This paper treats adaptation to the machining precision and productivity of compound free-form surfaces. The principle of a mixed NC machining method (surface direct interpolating (SDI[1])and discrete NC programming) is introduced- Three adaptive procedures are discussed : ( 1 ) adaptivedivision of the machining areas, (2) adaptive triangulation for generating interference-free tool pathsfrom compound surfaces, (3) machining along surface/surface intersection (SSI ) curves with anadaptive step length. They upgrade the intelligence of machining compound surfaces.

A local pseudo arc-length method for hyperbolic conservation laws

A local pseudo arc-length method（LPALM）for solving hyperbolic conservation laws is presented in this paper.The key idea of this method comes from the original arc-length method,through which the critical points are bypassed by transforming the computational space.The method is based on local changes of physical variables to choose the discontinuous stencil and introduce the pseudo arc-length parameter,and then transform the governing equations from physical space to arc-length space.In order to solve these equations in arc-length coordinate,it is necessary to combine the velocity of mesh points in the moving mesh method,and then convert the physical variable in arclength space back to physical space.Numerical examples have proved the effectiveness and generality of the new approach for linear equation,nonlinear equation and system of equations with discontinuous initial values.Non-oscillation solution can be obtained by adjusting the parameter and the mesh refinement number for problems containing both shock and rarefaction waves.

列车大小交路通信协同运行自适应控制方法

针对列车运输能力与客流时空分布不匹配的问题,提出列车灵活编组方案和短编组小间隔自适应控制方法。首先,根据新型列控系统的特点,设计列车自适应闭环控制框架,构建列车最小追踪间隔模型,提出大小交路列车在小交路通信协同运行的编组方案。其次,根据列车编组方案短编组小间隔控制需求,基于深度确定性策略梯度(Deep Deterministic Policy Gradient,DDPG)算法设计列车自适应控制模型,模型中通过设置奖励函数实现列车多目标控制,通过设计神经网络输出列车最优控制策略。然后,利用Matlab/Simulink仿真平台,以上海地铁2号线2A-2A列车通信协同运行为例,设置其追踪间隔为10 s,搭建加入随机阻力扰动的列车自适应控制模型并进行训练。研究结果表明:列车停车误差为0.1 m,准时误差为0.2 s,协同速度差小于2 km/h,区间最小追踪间隔为180.6 m,满足列车精准停车、速度协同和间隔安全性要求。针对DDPG算法估值过高而导致列车运行速度波动的问题,将神经网络中的Critic网络进行改进,改进后训练仿真表明:列车停车误差为0.03 m,准时误差为0.1 s,协同速度差小于2 km/h,区间最小追踪间隔为181.1 m,列车停车精度和间隔安全性均有提高,且速度波动相对平稳。最后,为验证该控制方法的实时性和安全性,假设前车在意外情况下减速停车,经仿真验证:后车停车误差为1.3 s,停车间隔为220.8 m,满足实时性和安全性的要求。研究成果可为城市轨道交通提供一种灵活匹配客流量的行车编组方案,为新型列控系统列车短编组小间隔运行提供一种安全高效的自适应控制方法。

AOS中基于最优帧长的链路自适应联合优化方法

针对AOS中数据传输误码率高的问题,导致系统吞吐量低的问题,提出基于最优帧长的链路自适应联合优化方法。该方法以系统吞吐量最大化为目标,联合可变帧长,自适应编码调制和混合自动重传请求技术进行优化,根据信道状态信息分配下一帧传输最佳的帧长和编码调制方式,并对出错数据进行纠错和重传,最终提升系统吞吐量。仿真验证表明,与AMC-HARQ和AMC-ARQ方法相比,该方法在保证系统误帧率的同时,提高了系统的吞吐量。

非参数自适应EWMA SR控制图及其变采样间隔设计

本文基于Wilcoxon符号秩(Signed Rank, SR)检验统计量,提出了一种非参数自适应指数加权移动平均(Adaptive Exponentially Weighted Moving Average, AEWMA)控制图。所提出的AEWMA SR控制图结合了非参数统计量的稳健受控性能以及自适应控制图良好的整体偏移检测特性。同时,为了提高固定采样间隔下的非参数AEWMA SR静态控制图对异常偏移的检测效率,本文进一步研究了可变采样间隔(Variable Sampling Intervals, VSI)下的非参数AEWMA SR动态控制图设计问题。使用了Markov链方法计算控制图的精确平均运行链长(Average Run Length, ARL)和平均报警时间(Average Time to Signal, ATS)等性能指标。通过仿真分析比较了VSI AEWMA SR控制图、FSI AEWMA SR控制图和VSI EWMA SR控制图的统计性能。结果表明,所提出的VSI AEWMA SR控制图能兼顾对于不同大小偏移的敏感性,且变采样间隔的动态策略能显著提高控制图的检测效率。

基于椭圆方向和半轴长度的多伯努利扩展目标跟踪

针对杂波环境下扩展目标外形难以估计、新生目标先验信息未知等问题,在扩展目标势均衡多目标多伯努利(ET-CBMeMBer)滤波器的基础上,开展基于椭圆方向和半轴长度(OAL)的参数化多扩展目标跟踪研究。借助乘性噪声构造考虑目标空间信息的显式量测方程,并推导OAL-CBMeMBer滤波器高斯混合实现的封闭形式解;基于显式的量测方程,利用已知的量测数据自适应构造考虑了质心位置和外形状态的新生目标先验信息,并提出自适应新生OAL-CBMeMBer滤波器。仿真实验结果表明:所提OAL-CBMeMBer滤波器提高了目标数目和状态的估计精度,能够有效地对多扩展目标进行跟踪。

An Adaptive Time-Stepping Strategy for the Cahn-Hilliard Equation

This paper studies the numerical simulations for the Cahn-Hilliard equation which describes a phase separation phenomenon.The numerical simulation of the Cahn-Hilliardmodel needs very long time to reach the steady state,and therefore large time-stepping methods become useful.The main objective of this work is to construct the unconditionally energy stable finite difference scheme so that the large time steps can be used in the numerical simulations.The equation is discretized by the central difference scheme in space and fully implicit second-order scheme in time.The proposed scheme is proved to be unconditionally energy stable and mass-conservative.An error estimate for the numerical solution is also obtained with second order in both space and time.By using this energy stable scheme,an adaptive time-stepping strategy is proposed,which selects time steps adaptively based on the variation of the free energy against time.The numerical experiments are presented to demonstrate the effectiveness of the adaptive time-stepping approach.

A High Order Adaptive Time-Stepping Strategy and Local Discontinuous Galerkin Method for the Modified Phase Field Crystal Equation

In this paper,we will develop a first order and a second order convex splitting,and a first order linear energy stable fully discrete local discontinuous Galerkin(LDG)methods for the modified phase field crystal(MPFC)equation.In which,the first order linear scheme is based on the invariant energy quadratization approach.The MPFC equation is a damped wave equation,and to preserve an energy stability,it is necessary to introduce a pseudo energy,which all increase the difficulty of constructing numerical methods comparing with the phase field crystal(PFC)equation.Due to the severe time step restriction of explicit timemarchingmethods,we introduce the first order and second order semi-implicit schemes,which are proved to be unconditionally energy stable.In order to improve the temporal accuracy,the semi-implicit spectral deferred correction(SDC)method combining with the first order convex splitting scheme is employed.Numerical simulations of the MPFC equation always need long time to reach steady state,and then adaptive time-stepping method is necessary and of paramount importance.The schemes at the implicit time level are linear or nonlinear and we solve them by multigrid solver.Numerical experiments of the accuracy and long time simulations are presented demonstrating the capability and efficiency of the proposed methods,and the effectiveness of the adaptive time-stepping strategy.

窗口长度自适应调整的策略迭代最优控制

在系统模型参数未知的最优控制问题中,策略迭代能否快速收敛到最优控制策略的关键在于值函数的估计.为了提升值函数的估计精度以及收敛速度,本文提出一种窗口长度自适应调整的策略迭代最优控制算法.充分利用一段时间内的历史样本数据,通过影响力函数构建窗口长度与值函数估计性能之间的定量关系,根据数据窗口长度对估计性能影响力的不同,实现窗口长度的自适应调整.最后,将本文所提方法应用到连续发酵过程,结果表明,本文所提方法能够加快最优控制策略的收敛,克服参数变化或外部扰动对控制性能的影响,从而提升控制精度.

基于威布尔分布函数的自适应MEWMA图多目标优化设计

为了提高MEWMA控制图的监控效率,提出了一种基于威布尔分布函数的自适应MEWMA图构造方法,以平均产品长度和单位产品质量成本为目标函数,从统计性和经济性两方面建立了自适应MEWMA图优化设计模型,并采用逼近理想解排序法给出了面向一个偏移区间范围的多目标优化步骤。最后,将本文提出的自适应MEWMA图方法与其它两种自适应多元控制图和已有的MEWMA经济统计设计分别进行比较,结果表明该自适应MEWMA图多目标优化设计在统计性能和经济性能上均具有明显的优势。

基于SIMP变密度法的结构拓扑优化及应用

在结构拓扑优化过程中,为了解决复杂结构计算速度慢、效率低的问题,提出了一种基于固体各向同性材料密度惩罚模型(SIMP)的步长自适应优化算法,该算法可根据SIMP惩罚因子P值自适应选择佳步长移动参数,并根据得到的目标函数的迭代值,自适应改变每次迭代的移动步长,在保证迭代精度的同时,以更快的速度逼近迭代目标,并利用经典MBB简支梁算例进行仿真实验,通过划分不同网格数量,横向对比分析另外三种步长迭代公式,得出最终迭代结果准确且迭代速度最快可提高100%的结论。此外,为满足汽车领域的轻量化需求,用拓扑优化技术,针对汽车油门支架结构进行重新优化设计,使优化后的模型体积减小35%;在此基础上,利用增材制造技术,采用双喷头连续纤维打印机,以长碳纤维体积分数为35%的复合材料(基体为短切碳纤维填充尼龙丝材)替代传统的铝合金材料进行增材制造,实现减重的目的,最终得到力学性能与原结构相当、质量减轻48%的油门支架结构,可进一步实现汽车的轻量化制造。

大语言模型引导的文本摘要技术与系统

在实际业务中时,常面临文本与它对应的其他模态在时间响应上难以同步的问题。例如,数字人实时手语表演无法与新闻口播同步播放。为了解决长度可控问题,提出一种基于大语言模型(LLM)的文本摘要解决方案,旨在保持原文语义不变的前提下将文本压缩至指定长度。首先通过模板调优和人工评估的方式,确定最适合长度可控文本摘要的LLM和模板;在此基础上,利用ChatGPT得到一定量优质的满足长度需求的文本摘要训练样本;其次,结合低秩自适应微调(LoRA)技术,利用生成的数据样本集对选定的大语言模型Baichuan-13B-Chat进行微调。在推理阶段,通过微调后的LLM生成多个结果和文本筛选模块打分,最终得到语义相对完整且长度满足要求的摘要文本。实验结果表明,所提方案在亚运手语新闻数据中指标显著提升,人工评估的平均满意度达到88.53%,整体压缩达标率达到73.7%,基本满足实际生产应用的需求。

基于C形梁质量控制的国产T300级碳纤维匹配性研究

以大长径比C形梁为研究对象,针对其表面质量、厚度、外形轮廓、金相分析等问题,制定工艺研究路线。通过比对国产T300级碳纤维织物及单向带预浸料的制造效果,明确了与大长径比、小R结构C形梁相匹配的国产T300级碳纤维预浸料的类型。通过设计直观的研究目标及高效的比对方案,阐明了国产T300级碳纤维单向带预浸料与大长径比C形梁构型的工艺匹配性强,为国产复合材料后续的研究方向提供借鉴,缩短了国产复合材料研究应用的周期。