Non-Markovian Quantum Error Deterrence by Dynamical Decoupling in a General Environment

A dynamical decoupling(DD) scheme for the prevention of errors in the non-Markovian (usually corresponding to low temperature, short time, and strong coupling) regimes suitable for qubits constructed out of a multilevel structure is studied. We use the effective spin-boson model (ESBM) introduced recently [K. Shiokawa and B. L. Hu, Phys. Rev. A70, 062106 (2004)] as a low temperature limit of the quantum Brownian oscillator model, where one can obtain exact solutions for a general environment with colored noises. In our decoupling scheme, a train of pairs of strong pulses are used to evolve the interaction Hamiltonian instantaneously. Using this scheme we show that the dynamical decoupling method can suppress 1/f noise with slower and hence more accessible pulses than previously studied, but it still fails to decouple super-Ohmic types of environments.      

Implementing Qubits with Superconducting Integrated Circuits

Superconducting qubits are solid state electrical circuits fabricated using techniques borrowed from conventional integrated circuits. They are based on the Josephson tunnel junction, the only non-dissipative, strongly non-linear circuit element available at low temperature. In contrast to microscopic entities such as spins or atoms, they tend to be well coupled to other circuits, which make them appealling from the point of view of readout and gate implementation. Very recently, new designs of superconducting qubits based on multi-junction circuits have solved the problem of isolation from unwanted extrinsic electromagnetic perturbations. We discuss in this review how qubit decoherence is affected by the intrinsic noise of the junction and what can be done to improve it. PACS: 03.67.-a, 03.65.Yz, 85.25.-j, 85.35.Gv     

From Dirac to Diffusion: Decoherence in Quantum Lattice Gases

We describe a model for the interaction of the internal (spin) degree of freedom of a quantum lattice-gas particle with an environmental bath. We impose the constraints that the particle-bath interaction be fixed, while the state of the bath is random, and that the effect of the particle-bath interaction be parity invariant. The condition of parity invariance defines a subgroup of the unitary group of actions on the spin degree of freedom and the bath. We derive a general constraint on the Lie algebra of the unitary group which defines this subgroup, and hence guarantees parity invariance of the particle-bath interaction. We show that generalizing the quantum lattice gas in this way produces a model having both classical and quantum discrete random walks as different limits. We present preliminary simulation results illustrating the intermediate behavior in the presence of weak quantum noise     

Quantum Computing and Information Extraction for Dynamical Quantum Systems

We discuss the simulation of complex dynamical systems on a quantum computer. We show that a quantum computer can be used to efficiently extract relevant physical information. It is possible to simulate the dynamical localization of classical chaos and extract the localization length with quadratic speed up with respect to any known classical computation. We can also compute with algebraic speed up the diffusion coefficient and the diffusion exponent, both in the regimes of Brownian and anomalous diffusion. Finally, we show that it is possible to extract the fidelity of the quantum motion, which measures the stability of the system under perturbations, with exponential speed up. The so-called quantum sawtooth map model is used as a test bench to illustrate these results. PACS: 03.67.Lx, 05.45.Mt     

Quantum Algorithms for Learning and Testing Juntas

In this article we develop quantum algorithms for learning and testing juntas, i.e. Boolean functions which depend only on an unknown set of k out of n input variables. Our aim is to develop efficient algorithms: (1) whose sample complexity has no dependence on n, the dimension of the domain the Boolean functions are defined over; (2) with no access to any classical or quantum membership (“black-box”) queries. Instead, our algorithms use only classical examples generated uniformly at random and fixed quantum superpositions of such classical examples; (3) which require only a few quantum examples but possibly many classical random examples (which are considered quite “cheap” relative to quantum examples). Our quantum algorithms are based on a subroutine FS which enables sampling according to the Fourier spectrum of f; the FS subroutine was used in earlier work of Bshouty and Jackson on quantum learning. Our results are as follows: (1) We give an algorithm for testing k-juntas to accuracy ε that uses O(k/ϵ) quantum examples. This improves on the number of examples used by the best known classical algorithm. (2) We establish the following lower bound: any FS-based k-junta testing algorithm requires queries. (3) We give an algorithm for learning k-juntas to accuracy ϵ that uses O(ϵ⁻¹ k log k) quantum examples and O(2 ^k log(1/ϵ)) random examples. We show that this learning algorithm is close to optimal by giving a related lower bound. Supported in part by NSF award CCF-0347282, by NSF award CCF-0523664, and by a Sloan Foundation Fellowship.     

Noiseless Subsystems and the Structure of the Commutant in Quantum Error Correction

The effect of noise on a quantum system can be described by a set of operators obtained from the interaction Hamiltonian. Recently it has been shown that generalized quantum error correcting codes can be derived by studying the algebra of this set of operators. This led to the discovery of noiseless subsystems. They are described by a set of operators obtained from the commutant of the noise generators. In this paper we derive a general method to compute the structure of this commutant in the case of unital noise. PACS: 03.67.–a, 03.67.Pp     

量子遗传算法及其在多用户检测中的应用

量子计算与遗传算法相结合的量子遗传算法是当今计算智能领域的一个前沿课题。文章从研究遗传算法在并行实现上的困难和改进方法出发,探讨了量子计算与遗传算法结合的理论基础,分析了量子遗传算法的理论和结构,最后提出了一种基于量子遗传算法的多用户检测方法。仿真结果表明,基于量子遗传算法的多用户检测器抗多址干扰的能力明显优于经典遗传算法多用户检测器。     

基于量子遗传算法的盲源分离算法研究

在改进遗传量子算法的基础上，提出了一种新的量子遗传算法并从理论上证明了算法的全局收剑性．提出了基于量子遗传算法与独立分量分析算法相结合的盲源分离新算法．仿真结果表明：新方法比采用常规遗传算法的盲源分离方法具有明显的高效性．     

超导磁共振主磁体励磁测控系统设计与开发

医用超导磁共振主磁体在励磁过程中出现的交流损耗和传导漏热等情况,是超导磁体失超的根本原因;为了控制和保证励磁过程的稳定性、可靠性和安全性,开发和完善励磁的测控系统就显得格外重要;设计并开发了基于LabVIEW平台的超导磁共振主磁体励磁测控系统;系统数据通过在虚拟仪器平台上调用动态链接库文件(DLL),控制泰克公司KE2700系列集成式采集卡采集得到;传感器选择根据相应功能需要配置;操作台仪器控制、数据采集程序和人机界面由LabVIEW编写;搭配保护电路,保护超导线圈,降低失超损失;实现数据采集、参数控制、失超保护、匀场测试等功能。系统满足设计开发目的,平台搭建稳定可靠;功能相对完善,具体操作简易,交互界面友好,后期修改和功能扩展灵活;经工程实际运行测试验证,提高了研究和工作效率,达到设计要求,有实际应用价值。     

格点量子色动力学组态产生和胶球测量的大规模并行及性能优化

格点量子色动力学（Lattice Quantum Chromo Dynamics,LQCD）是目前已知能系统研究夸克及胶子间低能强相互作用的非微扰计算方法.计算结果的统计和系统误差原则上都是可控的,并能逐步减少.基于格点QCD的基本原理,更大的格子体积意味着可以计算更大空间的物理过程,并且可以对空间进行更加精细的划分,从而得到更加精确的结果.因而大体系的格点计算对QCD理论研究有着重要意义,但对程序计算性能提出了更高要求.本文针对格点QCD组态生成和胶球测量的基本程序,进行了其大规模并行分析和性能优化的研究.基于格点QCD模拟采用的blocking和even-odd算法,我们设计了基于MPI和OpenMP的并行化算法,同时设计优化数据通信模块：针对复矩阵的矩阵乘等数值计算,提出了向量化的计算优化方法：针对组态文件输出瓶颈,提出了并行输出组态文件的实施方法.模拟程序分别在Intel KNL和“天河2号”超级计算机x86_64队列进行了测试分析,证实了相应的优化措施的有效性,并进行了相应的并行计算效率分析,最大测试规模达到了1728个节点（即41472 CPU核）.     

系统LT码在删除信道下的渐进性能分析及度分布设计

首先基于与或树分析法,对系统LT码在删除信道下的渐进性能公式进行推导,并给出其下限。仿真结果表明当开销足够大时,实际误码率,渐进性能与下限三者 完美匹配。然后根据渐进性能,提出改进的优化模型（Improved systematic linear programming,ISLP）对度分布进行优化设计。优化所得的度分布明显优于鲁棒孤波分布(Robust soliton distribution,RSD)分布与截断度分布(Truncated degree distribution,TDD)分布。另外,优化后的度分布其渐进性能可由设定的开销与误码率进行控制,即在所设置的开销之内达到理想的误码率,这一特性可进一步影响完全译码时所需开销。仿真结果表明,数据恢复时所需的开销与所设置的开销相近。对比系统LT码和LT码的误码率与恢复原始数据时所需的开销和编译码时间,表明系统LT码能比LT码更快地恢复原始数据,具有更优的性能。     

Updating method for the computation of orbits in parallel and sequential dynamical systems

In this article, we provide a matrix method in order to compute orbits of parallel and sequential dynamical systems on Boolean functions. In this sense, we develop algorithms for systems defined over directed (and undirected) graphs when the evolution operator is a general minterm or maxterm and, likewise, when it is constituted by independent local Boolean functions, so providing a new tool for the study of orbits of these dynamical systems.     

量子遗传算法在口腔种植定位中的研究与应用

口腔种植体设计方案的制定时间较长、智能程度不高,口腔医学数据信息量较大。为此,对种植体模型进行研究,提出一种改进的量子遗传算法。把种群细分为不同的特征群体,各特征群体实施自适应调整进化步长的量子旋转门操作,以及个体间信息交流的交叉操作。实验结果表明,与经典的遗传算法以及Bloch量子遗传算法相比,该算法能有效地优化种植体定位参数,搜索能力和收敛性能较好。     

某大学机房管理信息系统设计与实现

介绍了某大学机房管理信息系统的设计与实现情况 ,对该机房管理信息系统的功能结构作了详细的描述 ,介绍了该系统体系结构、开发和运行环境 ,最后对其特点进行了阐述     

基于改进量子差分进化的含分布式电源的配电网无功优化

差分进化算法（DE）已被证明为解决无功优化问题的有效方法.随着越来越多的分布式电源并网,对配电网潮流、电压均有一定改变,同时也影响了DE的鲁棒性和性能.本文在研究DE基础上,针对其收敛过早、局部搜索能力较差的缺陷,分析了量子计算思想和人工蜂群算法的优势,提出改进量子差分进化混合算法（IQDE）.通过量子编码思想提高了种群个体的多样性,人工蜂群算法的观察蜂加速进化操作和侦查蜂随机搜索操作分别提高了算法的局部搜索和全局搜索性能.建立以有功网损最小为目标的数学模型,将IQDE算法和DE算法分别用于14节点和30节点标准数据集进行大量仿真实验.实验结果表明,IQDE算法用更少的收敛时间、更小的种群规模便可以获得与DE算法相同甚至更佳的优化效果,并且可以很好的应用于解决难分布式电源的配电网无功优化问题.     

Design strategies for direct multi-scale and multi-orientation feature extraction in the log-polar domain

Despite the well known advantages that a space-variant representation of the visual signal offers, the required adaptation of the algorithms developed in the Cartesian domain, before applying them in the log-polar space, has limited a wide use of such representation in visual processing applications. In this paper, we present a set of original rules for designing a discrete log-polar mapping that allows a direct application in the log-polar domain of the algorithms, based on spatial multi-scale and multi-orientation filtering, originally developed for the Cartesian domain. The advantage of the approach is to gain, without modifications, an effective space-variance and data reduction. Such design strategies are based on a quantitative analysis of the relationships between the spatial filtering and the space-variant representation. We assess the devised rules by using a distributed approach based on a bank of band-pass filters to compute reliable disparity maps, by providing quantitative measures of the computational load and of the accuracy of the computed visual features.