An overview of quantum error mitigation formulas

Minimizing the effect of noise is essential for quantum computers.The conventional method to protect qubits against noise is through quantum error correction.However,for current quantum hardware in the so-called noisy intermediate-scale quantum(NISQ)era,noise presents in these systems and is too high for error correction to be beneficial.Quantum error mitigation is a set of alternative methods for minimizing errors,including error extrapolation,probabilistic error cancella-tion,measurement error mitigation,subspace expansion,symmetry verification,virtual distillation,etc.The requirement for these methods is usually less demanding than error correction.Quantum error mitigation is a promising way of reduc-ing errors on NISQ quantum computers.This paper gives a comprehensive introduction to quantum error mitigation.The state-of-art error mitigation methods are covered and formulated in a general form,which provides a basis for comparing,combining and optimizing different methods in future work.

Simple Mitigation Strategy for a Systematic Gate Error in IBMQ

In this paper, we report the observation and characterisation of a systematic error in the implementation of U3 gates in the IBM quantum computers. By measuring the effect of this gate for various rotation angles the error appears as an over-rotation, whose magnitude does not correlate with IBM’s cited errors calculated using Clifford randomized benchmarking. We propose a simple mitigation procedure to limit the effects of this error. We show that using a simple mitigation strategy one can obtain improved results in the observed value for the CHSH inequality, measured in a cloud-based quantum computer. This work highlights the utility of simple mitigation strategies for short-depth quantum circuits.

Passive location estimation using scatterer information for non-line-of-sight environments

In order to improve the performance of the traditional hybrid time-of-arrival（TOA）/angle-of-arrival（AOA）location algorithm in non-line-of-sight（NLOS）environments,a new hybrid TOA/AOA location estimation algorithm by utilizing scatterer information is proposed.The linearized region of the mobile station（MS）is obtained according to the base station（BS）coordinates and the TOA measurements.The candidate points（CPs）of the MS are generated from this region.Then,using the measured TOA and AOA measurements,the radius of each scatterer is computed.Compared with the prior scatterer information,true CPs are obtained among all the CPs.The adaptive fuzzy clustering（AFC）technology is adopted to estimate the position of the MS with true CPs.Finally,simulations are conducted to evaluate the performance of the algorithm.The results demonstrate that the proposed location algorithm can significantly mitigate the NLOS effect and efficiently estimate the MS position.

Near-term quantum computing techniques: Variational quantum algorithms, error mitigation, circuit compilation, benchmarking and classical simulation

Quantum computing is a game-changing technology for global academia,research centers and industries including computational science,mathematics,finance,pharmaceutical,materials science,chemistry and cryptography.Although it has seen a major boost in the last decade,we are still a long way from reaching the maturity of a full-fledged quantum computer.That said,we will be in the noisy-intermediate scale quantum(NISQ)era for a long time,working on dozens or even thousands of qubits quantum computing systems.An outstanding challenge,then,is to come up with an application that can reliably carry out a nontrivial task of interest on the near-term quantum devices with non-negligible quantum noise.To address this challenge,several near-term quantum computing techniques,including variational quantum algorithms,error mitigation,quantum circuit compilation and benchmarking protocols,have been proposed to characterize and mitigate errors,and to implement algorithms with a certain resistance to noise,so as to enhance the capabilities of near-term quantum devices and explore the boundaries of their ability to realize useful applications.Besides,the development of near-term quantum devices is inseparable from the efficient classical sim-ulation,which plays a vital role in quantum algorithm design and verification,error-tolerant verification and other applications.This review will provide a thorough introduction of these near-term quantum computing techniques,report on their progress,and finally discuss the future prospect of these techniques,which we hope will motivate researchers to undertake additional studies in this field.

Analysis and mitigation of bump magnetic field tracking errors in a multiturn injection system

Purpose The Space Environment Simulation and Research Infrastructure(SESRI)is a cluster of accelerators designed to simulate the cosmic radiation environment by generating particles of various types and energies.Among these accelerators,a synchrotron in the 300 MeV proton and heavy ion accelerator complex utilizes a multiturn injection scheme with four bump magnets to accumulate proton and heavy ion beams effectively.However,the bump magnetic field experiences a rapid drop rate of up to 1000 T/s,inevitably leading to a deviation(field tracking error)from the ideal magnetic field.The injection efficiency and particle distribution are significantly affected by this field tracking error,as evaluated by the ACCSIM code.Method During the device testing stage,the sources of field tracking errors were identified by analysis of the bump power supplies and the field of the magnets.Mitigation techniques were then implemented to reduce the field tracking error from[Math Processing Error]to[Math Processing Error]throughout the entire power supply,transmission cable,and magnet chain.Results Moreover,the successful injection and accumulation of beams during the operational phase of the synchrotron confirmed the effectiveness of the proposed mitigation methods.Additionally,a magnetic field measurement system was developed to monitor the magnetic field tracking error online.Conclusion The combination of the field tracking error mitigation methods and the measurement system provides valuable guidance for optimizing the magnetic fields with rapid drop rates.

Characterization of Blue-Green Light Non-Line-of-Sight Transmission in Seawater

The blue-green light in the 450 nm to 550 nm band is usually used in underwater wireless optical communication (UWOC). The blue-green light transmission in seawater is scattered by the seawater effect and can achieve communication in non-line-of-sight (NLOS) transmission mode. Compared to line-of-sight (LOS) transmission, NLOS transmission does not require alignment and can be adapted to various underwater environments. The scattering coefficients of seawater at different depths are different, which makes the scattering of light in different depths of seawater different. In this paper, the received optical power and bit error rate (BER) of the photodetector (PD) were calculated when the scattering coefficients of blue-green light in seawater vary from large to small with increasing depth for NLOS transmission. The results show that blue-green light in different depths of seawater in the same way NLOS communication at the same distance, the received optical power and BER at the receiver are different, and the received optical power of green light is greater than that of blue light. Increasing the forward scattering coverage of the laser will suppress the received optical power of the PD, so when performing NLOS communication, appropriate trade-offs should be made between the forward scattering coverage of the laser and the received optical power.

HUID:DBN-Based Fingerprint Localization and Tracking System with Hybrid UWB and IMU

High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID system.In particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization precision.To tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS conditions.Then,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization precision.The experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.

NLOS error mitigation with information fusion algorithm for UWB ranging systems

This article puts forward a scalar weighting information fusion （IF） smoother with modified biased Kalman filter （BKF） and maximum likelihood estimation （MLE） to mitigate the ranging errors in ultra wide band （UWB） systems. The information fusion algorithm uses both the time of arrival （TOA） and received signal strength （RSS） measurement data to improve the ranging accuracy. At first, the ranging protocol of IEEE 802.15.4a acts as a multi-sensor system with multi-scale sampling. Then the scalar-based IF smoother accurately estimates the range measurement in the line of sight （LOS） and non-line of sight （NLOS） condition of UWB sensor network, during which the effectiveness of the IF in mitigating errors is especially focused during the LOS/NLOS transitions. Simulation results show that the proposed hybrid TOA-RSS fusion approach indicates a performance improvement compared with the usual TOA-only and other IF method, and the estimated ranging metrics can be used for achieving higher accuracy in location estimation and target tracking.

无线定位系统的误差分析

影响无线定位系统应用的关键因素是系统的误差源和误差抑制方法。本文针对TOA/TDOA(timeofarrival/timedifferenceofarrival)定位算法,对定位系统的误差源:TOA参数估计误差、信号传播误差、基站误差、移动台误差、定位算法误差进行了详细的分析,对部分误差提出了抑制的方法,并且描述了相应误差的大小。

基于Kalman滤波器的非视距误差抑制算法

针对蜂窝网定位中影响定位精度的非视距传播误差问题,提出一种基于Kalman滤波器的非视距(NLOS)误差抑制算法,将到达时间(TOA)测量值及非视距误差作为Kalman滤波器的状态变量,根据TOA测量值的结构特点和NLOS误差的统计特性,确定Kalman滤波器过程方程的状态转移矩阵。以NLOS误差服从指数分布的情况为例进行仿真,结果表明,该算法在精度估计和算法计算量方面具有明显优势。

运用最优化原理的新型非视距抑制无线定位算法

无线定位中非视距(NLOS)误差的存在会显著降低传统定位算法的精度,因此论文提出了一种运用最优化原理的定位算法以对抗NLOS误差。该算法适用于存在固定节点与移动节点的无线传感网系统,并结合距离加权思想将NLOS环境中的定位建模为二次规划问题,最终得到节点的最小二乘位置估计。分析表明在固定节点数量较多或者存在视距(LOS)传输固定节点时,该算法可以显著削弱NLOS误差的影响。计算机仿真证实了这一分析,其结果表明,在NLOS环境下论文所提出的算法性能优于现有其他定位算法,同时该算法还具有不受固定节点数目限制和复杂度较低等优点。

GNSS接收机多径抑制性能检测技术

多径干扰信号会导致GNSS接收机伪距、载波相位和多普勒等测量精度降低,多径信号对GNSS接收机观测数据的影响与多径信号的延迟、幅度、相位等特性参数有关,造成的伪距测量误差高于载波相位测量误差2个数量级。多径抑制是GNSS接收机关键性能指标之一,GNSS接收机主要从试验室模拟环境和实际工作环境两方面检测多径抑制性能,多径误差包络检测技术利用模拟导航信号源完成多径抑制性能检测,码减载波和多径误差分析都是通过接收观测卫星导航信号并进行数据分析完成多径抑制性能的检测。

电离层延迟估计下的AltBOC信号联合跟踪方法

针对电离层分离效应使Galileo系统E5 Alt BOC信号上下2个边带码相位不同步的问题,提出了一种基于电离层延迟估计的Alt BOC联合跟踪的方法。该方法根据双频电离层延迟差估计结果调整Alt BOC信号上下2个边带信号的通道时延,使2个频点信号码相位同步。通过组合上下边带各自的伪随机码,实现Alt BOC信号的双边带联合跟踪。理论分析得出该算法可以有效补偿由电离层导致的Alt BOC信号上下边带信号码相位分离,仿真结果表明,该方法能够有效利用Alt BOC信号尖锐的自相关函数,改善了信号接收的抗多径性能,尤其是在高信噪比下的抗多径性能。

基于小波滤波及载噪比估计的GPS接收机多径抑制

为了抑制城市环境GPS(global positioning system)导航应用中由复杂信号反射引起的多径效应,提出了一种基于假设检验小波阈值滤波处理并联合载噪比估计的GPS接收机多径抑制方法.这种方法作用于GPS导航接收机的码和载波跟踪环路,通过估计由多径引起的跟踪误差,补偿伪距估计量,进而消除多径效应引起的定位误差.仿真实验结果表明,对于城市环境典型导航应用的多径场景,所提出的方法显著改善用户定位精度,能够将定位误差从标准接收机处理下的15.95 m降至1.75 m,而计算量无明显增加.

物证鉴定错误减少对策研究

物证鉴定若存在错误风险则会危害严重。恰当的物证鉴定错误管理可以有效减少物证鉴定错误的发生,有助于及时发现物证鉴定错误并将损害减至最小。本文探讨了在物证鉴定全部过程中有效管理物证鉴定错误的十二条措施:1)以有组织方式有条理的开展物证发现、提取、标记、记录、包装、保存和送检工作;2)持续强化物证鉴定科学基础研究和方法确认;3)在物证鉴定检验过程中实施多人平行鉴定、技术评审和管理审核程序;4)建立透明的鉴定意见冲突解决和鉴定结论表述机制;5)采用适当程序和方法有效管理和控制物证鉴定认知偏见信息;6)实施物证鉴定结论例行核查机制;7)建立检验留样和全面记录机制;8)有效评估物证鉴定结论错误风险;9)建立有效的用户培训和交流机制;10)及时发现和整改物证鉴定错误;11)构建物证鉴定科学文化;12)加强物证鉴定人培训。

基于稀疏贝叶斯学习的MIMO电力线脉冲噪声消除

为提高多输入多输出(MIMO)电力线通信系统对抗脉冲噪声的能力,基于稀疏贝叶斯学习的理论,利用脉冲噪声在电力线上的相关性,提出了一种消除MIMO电力线脉冲噪声的方案。方案使用全部子载波来联合估计脉冲噪声和可用子载波上的信号,无需训练脉冲噪声的统计信息。仿真中脉冲噪声拟合采用Bivariate Middleton Class A模型,结果表明该方案抗脉冲噪声性能比只使用空子载波的多观测向量稀疏贝叶斯学习(MSBL)方案提升了11dB。

基于改进CHAN的超宽带定位误差校正算法

短距离无线通信是构建物联网的重要技术之一,其中超宽带技术被认为是未来短距离无线通信的主流技术。如今,室内定位已经成为超宽带技术一个重要的应用领域。在基于到达时间差的定位误差校正算法中,CHAN算法具有在LOS环境下精度较高和计算复杂度较低等优点。在室内环境中,由于地形复杂和遮挡物增多,非视距问题使CHAN算法的定位精度明显下降。为了实现高精度的实时室内定位,提出一种基于残差加权和CHAN算法的误差校正算法。该算法的重点是通过CHAN算法初步计算出移动台位置的中间估计结果,并建立残差函数来衡量中间结果的准确程度,通过残差加权的方式优化CHAN算法在非视距环境中的性能。在不同噪声水平下进行了对比实验,结果表明该算法与CHAN算法相比对超宽带定位的NLOS误差有显著的抑制作用,改善了定位的性能。

基于自适应滤波的干扰消除方法研究

射电天文信号非常微弱,电磁环境对射电望远镜观测至关重要,通常可以利用地形、建立无线电宁静区、进行电磁屏蔽与防护等手段来减小电磁干扰.然而,仍有一些干扰难以屏蔽.故提出了一种基于自适应滤波的干扰消除方法,可用于复杂噪声环境中天文信号的提取.该方法借助自适应横向滤波器,采用最小均方(Least Mean Square,LMS)误差算法,以系统误差和收敛性为评判标准,通过改变步长与阶数对滤波效果进行优化,仿真结果显示该滤波器能在保证算法收敛的前提下有效提取信号.为了检验该算法的有效性,选取了新疆天文台南山26 m射电望远镜和Parkes 64 m射电望远镜记录的观测数据,采用设计的滤波器分别对不同的实测数据进行测试,验证了该滤波器的有效性.理论分析与实验结果一致表明该方法能有效消除天文观测中的干扰信号,具有一定的实用性.

NAND闪存错误缓解技术综述

NAND闪存以其高存储密度、高速、低功耗等优点被广泛应用于数据存储。三维堆叠闪存技术的出现和多值存储技术的发展进一步提高了密度,降低了存储成本,同时也带来了更加严重的可靠性问题。闪存主控厂商一直采用更强大的纠错码(ECC),如BCH和LDPC码来对闪存中的数据错误进行纠正。但当NAND闪存中的错误数超出ECC纠错能力时,错误将无法被纠正,因此研究人员提出了多种基于NAND闪存的错误缓解技术作为ECC的补充方案。本文介绍了NAND闪存的工作原理和错误模式,对最新的错误缓解技术进行综述,为设计更加可靠的存储解决方案提供了有益参考。

一组用于UWB室内定位的新信道特征参数

针对现有超宽带(UWB)信道识别参数精度低及鲁棒性差的问题,提出一组基于信道脉冲响应的新信道特征参数,并结合支持向量机构建非视距信道识别算法,然后根据波形特征分类测距误差并制定优化策略。在优化定位精度的基础上,本文引入模糊度为原始定位结果提供可信度评估。实验结果表明:引入新参数后信道识别算法的平均精度为93.94%;视距、非视距数据的准确率分别为90.13%、96.96%;修正后视距测距精度平均提高22.84%;非视距测距误差平均减低1 m以上;动态定位结果中厘米级精度占比提升41.5%。