扩展Toffoli门及其在多输出电路设计中的应用

用量子计算电路实现布尔逻辑运算是发展量子计算的一个重要目标。提出了量子扩展Toffoli门,及其在实现多输出逻辑电路中的转换算法。该算法将传统PLA文件的SOP积项转换到实现等价逻辑功能的量子Toffoli积项,能够用量子扩展Toffoli门实现。通过MCNC基准电路的测试结果表明,与经典PLA描述相比,用扩展Toffoli门能够更有效地描述多输出逻辑函数。     

混合多值可逆逻辑中广义Toffoli门仅用CNOT门的实现

混合多值量子可逆逻辑电路综合问题中,Toffoli门的合成是整个合成过程中最为关键的一步。针对混合多值5-qubits量子可逆逻辑电路综合问题,构造了PMX量子门,验证了CNOT门的合成能力,实现了对Toffoli门的合成,并设计了双向的BDS搜索算法,高效实现了量子电路的最优或者较优综合。     

基于矩阵初等变换的量子可逆逻辑电路双向综合算法

基于矩阵初等变换,提出了量子可逆逻辑电路双向综合算法。该算法依据两数字间的汉明距离,通过交换矩阵行号或矩阵元素对量子可逆逻辑电路的矩阵进行初等行变换。在变换的过程中,利用邻接矩阵的电路转化规则,生成任意给定置换的量子可逆逻辑电路。与其它同类算法相比,由于不需要穷尽搜索,该算法的时空复杂度有大幅降低;又由于采用任意n量子扩展通用Toffoli门,该算法可综合任一置换(奇或偶置换)的量子可逆逻辑电路,并且电路中门的数量有所减少。     

Toffoli门及相位估计的分解

给出了Toffoli门和量子相位估计第一阶段运算P这两个受控运算的分解及相应的图示说明,使得人们可以更好地从矩阵论和算子论的角度理解与应用Toffoli门和量子相位估计。     

改进TR门级联的量子比较器设计

量子比较器是量子算法设计中的重要组成部分,其对于量子算法的物理实现具有重要意义。针对比较器的量子代价与垃圾输出优化问题,分成三个阶段提出了改进TR门级联的量子比较器设计方案：第一个阶段使用布尔逻辑推导了方案的实现,并对其进行简化;第二个阶段设计了1位的量子比较器;第三个阶段将比较器进行级联,并实现[n]位的一般性比较器。通过迭代式的推导证明了其正确性,对比其他文献,该设计减少了近12.6%的量子代价,同时节约了47.6%的垃圾输出。通过实验仿真,证明其可以正常运行。与其他类型比较器相比,该设计所需的量子代价与垃圾输出有明显的减少,且构造简单易于实现。     

基于控制K次平方根非门的类Toffoli门构造方法

在量子电路综合算法中,由于非置换量子门比置换量子门具有更复杂的规则,直接使用非置换量子门会大幅度提高综合算法的复杂性,因此可先使用非置换量子门生成相应的置换量子门,然后再用这些置换量子门综合所求量子可逆逻辑电路,从而提高算法性能。本文重点研究如何用非置换量子门构造新的置换量子门,为此吸收了格雷码的思想,提出了一种高效的递归构造方法,实现使用控制非门和控制K次平方根非门(非置换量子门),快速生成最优的类Toffoli门(置换量子门)。     

一种求倒数近似值的量子算法及其量子电路

求取一个无符号数的倒数在数值计算中有着重要的应用.如何在量子电路中高效准确地求出倒数,影响着许多量子算法的性能.在此提出了一种求倒数近似值的量子算法及其量子电路的设计方法.首先将输入的二进制数存储在输入寄存器中;通过添加Toffoli门将两个n位二进制数每一位相乘的结果保存在2n个辅助量子比特中;再重复利用基础量子门设...     

参数化的广义量子通用相位门

主要研究参数化的广义量子通用相位门,给出了单比特量子门、双比特量子门以及三比特量子门的参数化构造。证明参数化的广义量子门和M.Nielsen给出的广义量子门是等价的。举例说明了参数化的广义量子通用门在量子计算中的作用。     

基于通用量子门的量子遗传算法及应用

为加快量子遗传算法的参数更新速度,简化遗传操作步骤,提出了一种基于通用量子门的量子遗传算法（Quantum Genetic Algorithm with Universal Quantum Gate,UQGA）。该方法以通用量子门为逻辑计算单位,对染色体进行遗传操作。利用Hadamard门进行基础变换;通用量子门通过新的旋转角度函数,对各个基因位进行选择、变异操作;通过求解适应度函数,得到全局最优解;同时,算法经数学证明是收敛的。该算法应用到函数极值搜索和Iris数据集特征选择中。实验结果表明,UQGA具有较好的全局搜索和特征选择性能,尤其是在收敛速度、运算时间和分类准确率方面明显优于普通量子遗传算法和普通遗传算法。     

SAT问题在量子体系计算机上的计算方法

本文从AMP方法解SAT问题入手,在量子体系计算机上寻求求解SAT问题的完备解的计算方法。从量子力学理论和Deutch的量子计算理论出发讨论通用量子逻辑门和构建布尔与门和或门的方法,最后,本文给出在量子模拟器上运用量子逻辑门阵列求解SAT问题的计算步骤。     

三值量子基本门及其对量子Fourier变换的电路实现

理论上可以把量子基本门组合在一起来实现任何量子电路和构建可伸缩的量子计算机。但由于构建量子线路的量子基本门数量庞大,要正确控制这些量子门十分困难。因此,如何减少构建量子线路的基本门数量是一个非常重要和非常有意义的课题。提出采用三值量子态系统构建量子计算机,并给出了一组三值量子基本门的功能定义、算子矩阵和量子线路图。定义的基本门主要包括三值量子非门、三值控制非门、三值Hadamard门、三值量子交换门和三值控制CR_k门等。通过把量子Fourier变换推广到三值量子态,成功运用部分三值量子基本门构建出能实现量子Fourier变换的量子线路。通过定量分析发现,三值量子Fourier变换的线路复杂度比二值情况降低了至少50%,表明三值量子基本门在降低量子计算线路复杂度方面具有巨大优势。     

Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

We have designed efficient quantum circuits for the three-qubit Toffoli (controlled–controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the “Luck-Choose” mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.     

On figures of merit in reversible and quantum logic designs

Five figures of merit including number of gates, quantum cost, number of constant inputs, number of garbage outputs, and delay are used casually in the literature to compare the performance of different reversible or quantum logic circuits. In this paper we propose new definitions and enhancements, and identify similarities between these figures of merit. We evaluate these measures to show their strength and weakness. Instead of the number of gates, we introduce the weighted number of gates, where a weighting factor is assigned to each quantum or reversible gate, based on its type, size and technology. We compare the quantum cost with weighted number of gates of a circuit and show three major differences between these measures. It is proved that it is not possible to define a universal reversible logic gate without adding constant inputs. We prove that there is an optimum value for number of constant inputs to obtain a circuit with minimum quantum cost. Some reversible logic benchmarks have been synthesized using Toffoli and Fredkin gates to obtain their optimum values of number of constant inputs. We show that the garbage outputs can also be used to decrease the quantum cost of the circuit. A new definition of delay in quantum and reversible logic circuits is proposed for music line style representation. We also propose a procedure to calculate the delay of a circuit, based on the quantum cost and the depth of the circuit. The results of this research show that to achieve a fair comparison among designs, figures of merit should be considered more thoroughly.      

Improved quantum ripple-carry addition circuit

A serious obstacle to large-scale quantum algorithms is the large number of elementary gates, such as the controlled-NOT gate or Toffoli gate. Herein, we present an improved linear-depth ripple-carry quantum addition circuit, which is an elementary circuit used for quantum computations. Compared with previous addition circuits costing at least two Toffoli gates for each bit of output, the proposed adder uses only a single Toffoli gate. Moreover, our circuit may be used to construct reversible circuits for modular multiplication, Cx mod M with x < M, arising as components of Shor’s algorithm. Our modular-multiplication circuits are simpler than previous constructions, and may be used as primitive circuits for quantum computations.     

Implementing gate operations between uncoupled qubits in linear nearest neighbor arrays using a learning algorithm

We propose a new scheme to implement gate operations in a one dimensional linear nearest neighbor array, by using dynamic learning algorithm. This is accomplished by training quantum system using a back propagation technique, to find the system parameters that implement gate operations directly. The key feature of our scheme is that, we can reduce the computational overhead of a quantum circuit by finding the parameters to implement the desired gate operation directly, without decomposing them into a sequence of elementary gate operations. We show how the training algorithm can be used as a tool for finding the parameters for implementing controlled-NOT (CNOT) and Toffoli gates between next-to-nearest neighbor qubits in an Ising-coupled linear nearest neighbor system. We then show how the scheme can be used to find parameters for realizing swap gates first, between two adjacent qubits and then, between two next-to-nearest-neighbor qubits, in each case without decomposing it into 3 CNOT gates. Finally, we show how the scheme can be extended to systems with non-diagonal interactions. To demonstrate, we train a quantum system with Heisenberg interactions to find the parameters to realize a swap operation.     

基于3D角度编码的量子遗传算法

为了充分利用量子态在算法中的量子特性,提高算法的搜索效率,减少存储空间,提出了一种基于3D角度编码的量子遗传算法。该算法将量子位描述为3D球面坐标下的一对相位角,充分利用了量子的空间运动特性,并引入一种自适应旋转角大小和方向的确定方案,从而进一步简化了染色体的更新和变异过程,而且使算法的量子特性、存储性能、时间性能都得到很大的提高。仿真结果表明,其在算法优化效率和搜索能力上都优于简单遗传算法和普通量子遗传算法。     

Upper bounds for reversible circuits based on Young subgroups

We present tighter upper bounds on the number of Toffoli gates needed in reversible circuits. Both multiple controlled Toffoli gates and mixed polarity Toffoli gates have been considered for this purpose. The calculation of the bounds is based on a synthesis approach based on Young subgroups that results in circuits using a more generalized gate library. Starting from an upper bound for this library we derive new bounds which improve the existing bound by around 77%.     

基于序列输入的量子神经网络模型及算法

为提高神经网络的逼近能力,提出一种各维输入为离散序列的量子神经网络模型及算法.该模型为3层结构,隐层为量子神经元,输出层为普通神经元.量子神经元由量子旋转门和多位受控非门组成,利用多位受控非门中目标量子位的输出向输入端的反馈,实现对输入序列的整体记忆,利用受控非门输出中多位量子比特的纠缠获得量子神经元的输出.基于量子计算理论设计该模型的学习算法.该模型可从宽度和深度两方面获取输入序列的特征.仿真结果表明,当输入节点数和序列长度满足一定关系时,该模型明显优于普通神经网络.     

Mapping from multiple-control Toffoli circuits to linear nearest neighbor quantum circuits

In recent years, quantum computing research has been attracting more and more attention, but few studies on the limited interaction distance between quantum bits (qubit) are deeply carried out. This paper presents a mapping method for transforming multiple-control Toffoli (MCT) circuits into linear nearest neighbor (LNN) quantum circuits instead of traditional decomposition-based methods. In order to reduce the number of inserted SWAP gates, a novel type of gate with the optimal LNN quantum realization was constructed, namely NNTS gate. The MCT gate with multiple control bits could be better cascaded by the NNTS gates, in which the arrangement of the input lines was LNN arrangement of the MCT gate. Then, the communication overhead measurement model on inserted SWAP gate count from the original arrangement to the new arrangement was put forward, and we selected one of the LNN arrangements with the minimum SWAP gate count. Moreover, the LNN arrangement-based mapping algorithm was given, and it dealt with the MCT gates in turn and mapped each MCT gate into its LNN form by inserting the minimum number of SWAP gates. Finally, some simplification rules were used, which can further reduce the final quantum cost of the LNN quantum circuit. Experiments on some benchmark MCT circuits indicate that the direct mapping algorithm results in fewer additional SWAP gates in about 50%, while the average improvement rate in quantum cost is 16.95% compared to the decomposition-based method. In addition, it has been verified that the proposed method has greater superiority for reversible circuits cascaded by MCT gates with more control bits.