Alpha-Beta Hybrid Quantum Associative Memory Using Hamming Distance

This work presents a quantum associative memory (Alpha-Beta HQAM) that uses the Hamming distance for pattern recovery. The proposal combines the Alpha-Beta associative memory, which reduces the dimensionality of patterns, with a quantum subroutine to calculate the Hamming distance in the recovery phase. Furthermore, patterns are initially stored in the memory as a quantum superposition in order to take advantage of its properties. Experiments testing the memory’s viability and performance were implemented using IBM’s Qiskit library.     

Spectrally Improved Controllable Frequency Comb Quantum Memory

Optics and Spectroscopy - We propose a scheme of a universal block of broadband quantum memory consisting of three ring microresonators forming a controllable frequency comb and interacting with...     

Robust Quantum Private Queries

We propose a new quantum private query protocol with the technique of decoherence-free states, which is a theoretical study of how decoherence-free states can be used for the protection of quantum information in such a protocol. This protocol can solve the noise problem that will make the user obtain a wrong answer and hence give rise to a bad influence on the reputation of the database provider. Furthermore, this protocol is also flexible, loss-resistant and easily generalized to a large database similar to the previous works.     

Quantum Associative Neural Network with Nonlinear Search Algorithm

Based on analysis on properties of quantum linear superposition, to overcome the complexity of existing quantum associative memory which was proposed by Ventura, a new storage method for multiply patterns is proposed in this paper by constructing the quantum array with the binary decision diagrams. Also, the adoption of the nonlinear search algorithm increases the pattern recalling speed of this model which has multiply patterns to O( log₂^{2n -t} ) = O( n - t )O( {log_{2}}^{2^{n -t}} ) = O( n - t ) time complexity, where n is the number of quantum bit and t is the quantum information of the t quantum bit. Results of case analysis show that the associative neural network model proposed in this paper based on quantum learning is much better and optimized than other researchers’ counterparts both in terms of avoiding the additional qubits or extraordinary initial operators, storing pattern and improving the recalling speed.     

Multiresonator Quantum Memory with Switcher

JETP Letters - A scheme of multiresonator quantum memory based on a system of four interacting resonators connected through a common resonator to an external carrier by means of switchable coupling...     

Applications of Singh-Rajput Mes in Recall Operations of Quantum Associative Memory for a Two- Qubit System

Recall operations of quantum associative memory (QuAM) have been conducted separately through evolutionary as well as non-evolutionary processes in terms of unitary and non- unitary operators respectively by separately choosing our recently derived maximally entangled states (Singh-Rajput MES) and Bell’s MES as memory states for various queries and it has been shown that in each case the choices of Singh-Rajput MES as valid memory states are much more suitable than those of Bell’s MES. it has been demonstrated that in both the types of recall processes the first and the fourth states of Singh-Rajput MES are most suitable choices as memory states for the queries ‘11’ and ‘00’ respectively while none of the Bell’s MES is a suitable choice as valid memory state in these recall processes. It has been demonstrated that all the four states of Singh-Rajput MES are suitable choice as valid memory states for the queries ‘1?’, ‘?1’, ‘?0’ and ‘0?’ while none of the Bell’s MES is suitable choice as the valid memory state for these queries also.     

On a Quantum System with Memory

We consider the integro-differential equation for the classical trajectory of an oscillator coupled to another one. On the quantum level the elimination of the coordinate A of the “unvisible” oscillator leads to an effective path integral (X, Ξ, μ) for the associated imaginary time stochastic process t ?, (-∞,∞) → x(t). We prove reflection positivity of the measure dμ ≈ F · dξ, where dξ governes the free oscillator x and F is the counterpart of Feynman's influence functional. Finally, realizing the Hamiltonian semigroup exp(-tH), t ≧ 0, in the physical Hilbert space ?? = L²(X, Γ, μ), where Γ ? Ξ₊, we try to understand what is memory.     

Multiresonator Quantum Memory with Single Atoms

JETP Letters - Quantum memory based on a system of resonators each containing one atom and connected to an external waveguide through a common resonator has been proposed. The parameters of the...     

利用猫式自泵浦位相共轭镜的光学联想存储器

报道了以快速响应（１５０ｍｓ），成像质量高（分辨率＞５０ｐｌ／ｍｍ）的１６°切掺铜钾钠铌酸锶钡（Ｃｕ：ＫＮＳＢＮ）晶体猫式自泵浦位相共轭境作为取阈反馈器件，以低吸收薄晶体Ｃｅ：Ｆｅ：ＬｉＮｂＯ３作为存储介质的光学全息联想存储器，利用２５％原信息寻址，可得出完整的联想输出．     

Processes of Quantum Associative Memory (QuAM) Through New Maximally Entangled States (Singh-Rajput MES)

Using Singh-Rajput MES as memory states in the evolutionary process of pattern storage and the non-evolutionary process of pattern recall (the two fundamental constituents of QuAM), the suitability and superiority of these MES over Bell’s MES have been demonstrated in both these processes. It has been shown that, under the operations of all the possible memorization operators for a two-qubit system, the first two states of Singh-Rajput MES are useful for storing the pattern |11> and the last two of these MES are useful in storing the pattern |10> while Bell’s MES are not much suitable as memory states in a valid memorization process. The recall operations have also been conducted by separately choosing Singh-Rajput MES and Bell’s MES as memory states for possible various queries and it has been shown that in each case the choices of Singh-Rajput MES as valid memory states are much more suitable than those of Bell’s MES.     

On a Model of Associative Memory with Huge Storage Capacity

In Krotov et al. (in: Lee (eds) Advances in Neural Information Processing Systems, Curran Associates, Inc., Red Hook, 2016) Krotov and Hopfield suggest a generalized version of the well-known Hopfield model of associative memory. In their version they consider a polynomial interaction function and claim that this increases the storage capacity of the model. We prove this claim and take the ”limit” as the degree of the polynomial becomes infinite, i.e. an exponential interaction function. With this interaction we prove that model has an exponential storage capacity in the number of neurons, yet the basins of attraction are almost as large as in the standard Hopfield model.     

Multi-channel Associative Memory Using Liquid Crystal Photoelectric Switches

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Integrated Image Associative Memory and Its Optical Implementation

We present the concept of integrated processing to combine intuitive processing of neural networks with logical processing of the conventional digital computer. We investigate a way to embody the concept in the neural network system by introducing external constraints in terms of external input. The effect of the external input is analyzed using the generalized projection method. The concept of integrated processing is applied to an image associative memory system, and the system is optically implemented for high-speed parallel processing incorporating it with the computer. The experimental result is presented to illustrate the effectiveness of the external input to control the output of the image associative memory.     

Finite-Time Stability for Fractional-Order Bidirectional Associative Memory Neural Networks with Time Delays

This paper is concerned with fractional-order bidirectional associative memory(BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results.     

基于联想存储级联WTA模型的旋转不变识别

提出一种多目标旋转不变分类识别的新方法，其基本思想是多对一导联想存储模型，为便于光学实现、充分利用系统的时间、空间带宽积，采用了全单极形成，并对权重进行了二值化截取。一个分布阈值用来克服单极联想存储模型０，１状态分布几率不等时存储空量急剧下降的缺点，同时通过巧妙地选取目标所对应的异联想码将异联想模型和ＷＴＡ模型有机地结合起来，提高了整个系统的存储容量和容错性。本文给出了计算机仿真模拟及一个光电混合     

Quantum Maps with Memory from Generalized Lindblad Equation

In this paper, we proposed the exactly solvable model of non-Markovian dynamics of open quantum systems. This model describes open quantum systems with memory and periodic sequence of kicks by environment. To describe these systems, the Lindblad equation for quantum observable is generalized by taking into account power-law fading memory. Dynamics of open quantum systems with power-law memory are considered. The proposed generalized Lindblad equations describe non-Markovian quantum dynamics. The quantum dynamics with power-law memory are described by using integrations and differentiation of non-integer orders, as well as fractional calculus. An example of a quantum oscillator with linear friction and power-law memory is considered. In this paper, discrete-time quantum maps with memory, which are derived from generalized Lindblad equations without any approximations, are suggested. These maps exactly correspond to the generalized Lindblad equations, which are fractional differential equations with the Caputo derivatives of non-integer orders and periodic sequence of kicks that are represented by the Dirac delta-functions. The solution of these equations for coordinates and momenta are derived. The solutions of the generalized Lindblad equations for coordinate and momentum operators are obtained for open quantum systems with memory and kicks. Using these solutions, linear and nonlinear quantum discrete-time maps are derived.     

高阶局域互联神经网络的关联存储

给出了高阶局域互联神经网络的数学模型。在计算机上对其关联存储能力进行了模拟计算。结果表明，这种局域互联神经网络的互联权重数大大减少，同时依然具有良好的关联存储能力；另一方面，如果限定了互联权重矩阵的大小，利用本文给出的高阶局域互联神经网络模型可构造较大的人工神经网络。     

击中击不中变换在光学全息关联存储中的应用

应用形态击中周不中变换，提出了一种提高光学全息关联存储寻址准确性的方法，并给出了实验演示。     

增强型双通道实时联想存储系统的研究

首次将多通道并行处理的概念引入联想存储系统中，提出一个带有ＣＣＤ摄像机、图像卡、微机及液晶光阈等控制与输入设备，并以液晶电光开关作为取阈反馈装置的双通道联想系统。系统存储方式采用计算机磁盘充当外部图像库存储大量参考图像，而在系统内一点只存储一幅图像。