Smaller Ge Quantum Dots Obtained by ArF Excimer Laser Annealing

Ge self-assembled quantum dots （SAQDs） are grown with a self-assembled UHV/CVD epitaxy system. Then, the as-grown Ge quantum dots are annealed by ArF excimer laser. In the ultra-shot laser pulse duration, -20ns, bulk diffusion is forbidden,and only surface diffusion occurs, resulting in a laser induced quantum dot （LIQD）. The diameter of the LIQD is 20-25nm which is much smaller than the as-grown dot and the LIQD has a higher density of about 6 ×10^10cm^-2. The surface morphology evolution is investigated by AFM.

Research on the photoluminescence of spectral broadening by rapid thermal annealing on InAs/GaAs quantum dots

Photoluminescence (PL) test was conducted to investigate the effect of rapid thermal annealing (RTA) on the opticalperformance of self-assembled InAs/GaAs quantum dots (QDs) at the temperatures of 16 and 300 K. It was found that after RTAtreatment, the PL spectrum of the QDs sample had a large blue-shift and significantly broadened at 300 K. Compared with theas-grown InAs QDs sample, the PL spectral width has increased by 44.68 meV in the InAs QDs sample RTA-treated at800 ℃. The excitation power-dependent PL measurements showed that the broadening of the PL peaks of the RTA-treatedInAs QDs should be related to the emission of the ground state (GS) of different-sized InAs QDs, the InAs wetting layer (WL)and the In0.15Ga0.85As strain reduction layer (SRL) in the epitaxial InAs/GaAs layers.

On the time-independent Hamiltonian in real-time and imaginary-time quantum annealing

We present the analog analogue of Grover's problem as an example of the time-independent Hamiltonian for applying the speed limit of the imaginary-time Schrödinger equation derived by Okuyama and Ohzeki and the new class of energy-time uncertainty relation proposed by Kieu. It is found that the computational time of the imaginary-time quantum annealing of this Grover search can be exponentially small, while the counterpart of the quantum evolution driven by the real-time Schrödinger equation could only provide square root speedup, compared with classic search. The present results are consistent with the cases of the time-dependent quantum evolution of the natural Grover problem in previous works. We once again emphasize that the logarithm and square root algorithmic performances are generic in imaginary-time quantum annealing and quantum evolution driven by real-time Schrödinger equation, respectively. Also, we provide evidences to search deep reasons why the imaginary-time quantum annealing can lead to exponential speedup and the real-time quantum annealing can make square root speedup.

Quantum annealing for semi-supervised learning

Recent advances in quantum technology have led to the development and the manufacturing of programmable quantum annealers that promise to solve certain combinatorial optimization problems faster than their classical counterparts.Semi-supervised learning is a machine learning technique that makes use of both labeled and unlabeled data for training,which enables a good classifier with only a small amount of labeled data.In this paper,we propose and theoretically analyze a graph-based semi-supervised learning method with the aid of the quantum annealing technique,which efficiently utilizes the quantum resources while maintaining good accuracy.We illustrate two classification examples,suggesting the feasibility of this method even with a small portion(30%) of labeled data involved.

Revenue Optimization of Pipelines Construction and Operation Management Based on Quantum Genetic Algorithm and Simulated Annealing Algorithm

For the optimization of pipelines, most researchers are mainly concerned with designing the most reasonable section to meet the requirements of strength and stiffness, and at the same time reduce the cost as much as possible. It is undeniable that they do achieve this goal by using the lowest cost in design phase to achieve maximum benefits. However, for pipelines, the cost and incomes of operation management are far greater than those in design phase. Therefore, the novelty of this paper is to propose an optimization model that considers the costs and incomes of the construction and operation phases, and combines them into one model. By comparing three optimization algorithms (genetic algorithm, quantum genetic algorithm and simulated annealing algorithm), the same optimization problem is solved. Then the most suitable algorithm is selected and the optimal solution is obtained, which provides reference for construction and operation management during the whole life cycle of pipelines.

Room-Temperature Annealing of 1 MeV Electron Irradiated Lattice Matched In0.53Ga0.47As/InP Multiple Quantum Wells

Long-term room-temperature annealing effects of InGaAs/InP quantum wells with different wells （namely triple wells and five wells embedded） and bulk InCaAs are investigated after high energy electron irradiation. It is observed that the photoluminescence （PL） intensity of bulk InGaAs materials is enhanced after low dose electron irradiation and the PL intensity for all the three samples is degraded dramatically when the electron dose is relatively high. With respect to the room-temperature annealing, we find that the PL intensity for both samples recovers relatively fast at the initial stage. The PL performance of multiple quantum-well samples shows better recovery after irradiation compared with the results of bulk InGaAs materials. Meanwhile, the recovery speed factors of multiple quantum-well samples are relatively faster than those of the bulk InGaAs materials as well. We infer that the recovery difference between the quantum-well materials and bulk materials originates from the fact that the radiation induced defects are confined in the quantum wells as a consequence of the free energy barrier between the In0.53Ga0.47 As wells and InP barrier layers.

Enhancement of Crystalline Quality of Strained InAs／InP Quantum Well Structures by Rapid Thermal Annealing

The effect of rapid thermal annealing on the optical properties of astrained InAs/InP single quantum well structrure has been investigated in this paper.The luminescence intensity of the quantum well at 8 K was increased by a factor of 4 and 1.55 meV blue shift of the quantum well photoluminescence peak was observed after annealing at the optimal condition of 700℃ for 5 s. Furthermore,we found that the luminescence efficiency of the deep radiative levels in the samples was also affected by rapid thermal annealing.Our experimental results have demonstrated that Rapid thermal annealing significantly improves the crystalline quality of strained quantum well structures after growth and is an important way for enhancement of the performance of the laser device.

A New Path to Create Solutions for Quantum Annealing Problems

Quantum computing has already become a technology to be used by large companies in finance, distribution, health care, chemistry, etc. Among the different approaches, quantum annealing is one of the most promising in the short term. However, software development platforms do not offer user-friendly interfaces for the definition of annealing problems. In this paper we present a solution to this problem: QPath®’s Annealer Compositor that facilitates the definition and execution of annealing algorithms in either quantum annealing or digital annealing computers. An example based on a nurse work schedule is used for illustrating this special interface.

Quantum control based on three forms of Lyapunov functions

This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.

Effects of T-Factor on Quantum Annealing Algorithms for Integer Factoring Problem

The hardness of the integer factoring problem(IFP)plays a core role in the security of RSA-like cryptosystems that are widely used today.Besides Shor’s quantum algorithm that can solve IFP within polynomial time,quantum annealing algorithms(QAA)also manifest certain advantages in factoring integers.In experimental aspects,the reported integers that were successfully factored by using the D-wave QAA platform are much larger than those being factored by using Shor-like quantum algorithms.In this paper,we report some interesting observations about the effects of QAA for solving IFP.More specifically,we introduce a metric,called T-factor that measures the density of occupied qubits to some extent when conducting IFP tasks by using D-wave.We find that T-factor has obvious effects on annealing times for IFP:The larger of T-factor,the quicker of annealing speed.The explanation of this phenomenon is also given.

混合量子-经典算法的配电网灾后拓扑重构方法

为及时有效地制定配电网拓扑重构策略以提升负荷快速恢复能力,基于量子计算的优越性,提出混合量子-经典(HQC)算法的弹性配电网灾后拓扑重构方法。首先,构建基于HQC算法的灾后配电网拓扑重构模型,以实现实际场景、优化问题、嵌入算法相应模块在量子计算和经典计算环境下的协作交互过程。然后,将配电网拓扑重构问题构造为无约束离散优化子问题和有约束连续优化子问题,提出量子退火嵌入式交替方向乘子(QA-ADMM)算法,将离散子问题等效映射成量子可解释的伊辛模型后,部署在D-Wave量子退火计算机中,并与经典计算机中连续子问题迭代求解,采用自适应惩罚因子调节机制加速算法收敛。最后,通过IEEE 14、33、69、123以及改进的205节点的不同规模配电系统,分析验证了QA-ADMM算法的有效性、稳定性与可扩展性。结果表明,惩罚因子、目标函数惩罚项系数、量子退火中采样读取次数会影响所提算法的精度和收敛速度;优化问题规模扩大后,所提混合量子-经典算法计算优势更加明显,205节点配电系统算例下,计算效率较经典计算可提升约34%。

Effects of Interdiffusion on Luminescence of InAs/GaAs Quantum Dots Covered by InGaAs Overgrowth Layer

WT8.BZ]The effects of postgrowth rapid thermal annealing have been studied on the optical properties of 3-nm-height InAs/GaAs quantum dots covered by 3-nm-thick In xGa 1-x As (x=0,0 1 and 0 2) overgrowth layer.At a higher annealing temperature (T≥750℃),the photoluminescence peak of InGaAs layer has been observed at the lower-energy side of InAs quantum-dot peak.In addition,a similar blueshift in photoluminescence (PL) emission energy is observed for all samples when the annealing temperature increases from 650 to 850℃.However,the trend of photoluminescence linewidth towards narrowing is totally different for InAs quantum dots with different In mole fraction in InGaAs overgrowth layer.The results suggest that the intermixing in the lateral direction plays an important role in obtaining a better understanding of the modification of optical properties induced by the rapid thermal annealing.

Research on quantum well intermixing of 680 nm AlGaInP/GaInP semiconductor lasers induced by composited Si-Si_(3)N_(4) dielectric layer

The optical catastrophic damage that usually occurs at the cavity surface of semiconductor lasers has become the main bottleneck affecting the improvement of laser output power and long-term reliability.To improve the output power of 680 nm AlGaInP/GaInP quantum well red semiconductor lasers,Si-Si_(3)N_(4)composited dielectric layers are used to induce its quantum wells to be intermixed at the cavity surface to make a non-absorption window.Si with a thickness of 100 nm and Si_(3)N_(4)with a thickness of 100 nm were grown on the surface of the epitaxial wafer by magnetron sputtering and PECVD as diffusion source and driving source,respectively.Compared with traditional Si impurity induced quantum well intermixing,this paper realizes the blue shift of 54.8 nm in the nonabsorbent window region at a lower annealing temperature of 600 ℃ and annealing time of 10 min.Under this annealing condition,the wavelength of the gain luminescence region basically does not shift to short wavelength,and the surface morphology of the whole epitaxial wafer remains fine after annealing.The application of this process condition can reduce the difficulty of production and save cost,which provides an effective method for upcoming fabrication.

Quantum Computational Techniques for Prediction of Cognitive State of Human Mind from EEG Signals

The utilization of quantum states for the representation of information and the advances in machine learning is considered as an efficient way of modeling the working of complex systems.The states of mind or judgment outcomes are highly complex phenomena that happen inside the human body.Decoding these states is significant for improving the quality of technology and providing an impetus to scientific research aimed at understanding the functioning of the human mind.One of the key advantages of quantum wave-functions over conventional classical models is the existence of configurable hidden variables,which provide more data density due to its exponential state-space growth.These hidden variables correspond to the amplitudes of each probable state of the system and allow for the modeling of various intricate aspects of measurable and observable physical quantities.This makes the quantum wave-functions powerful and felicitous to model cognitive states of the human mind,as it inherits the ability to efficiently couple the current context with past experiences temporally and spatially to approach an appropriate future cognitive state.This paper implements and compares some techniques like Variational Quantum Classifiers(VQC),quantum annealing classifiers,and hybrid quantum-classical neural networks,to harness the power of quantum computing for processing cognitive states of the mind by making use of EEG data.It also introduces a novel pipeline by logically combining some of the aforementioned techniques,to predict future cognitive responses.The preliminary results of these approaches are presented and are very encouraging with upto 61.53%validation accuracy.

喷墨打印量子点薄膜制备的影响因素研究

目的为了通过喷墨打印技术很好地实现量子点薄膜图案化,需要调节量子点薄膜制备工艺的各项参数以获得表面均匀、厚度适宜和无咖啡环结构的量子点薄膜。方法基板和退火是影响量子点薄膜成膜性能的2个重要参数,分别研究基板的清洗、材料和温度以及退火的温度和时间对喷墨打印量子点薄膜成膜性能的影响。结果选择3种不同类型的溶剂依次清洗可提高基板表面能,有利于墨水的铺展;PVK基板的量子点面薄膜形貌相较于Pedot:Pss更均匀;当基板温度为50℃、退火温度为80℃或90℃、退火时间为15 min时,咖啡环效应最弱,可获得表面均匀、厚度适宜和无咖啡环结构的量子点薄膜。结论基板的清洗、自身材料以及温度都会影响墨水的铺展性能,从而影响量子点薄膜的成膜性能;控制退火温度与退火时间,以使马兰戈尼流起作用,咖啡环效应被明显抑制,可以获得表面均匀的量子点薄膜。

基于D-Wave Advantage的量子退火公钥密码攻击算法研究

D-Wave专用量子计算机的原理量子退火凭借独特的量子隧穿效应可跳出传统智能算法极易陷入的局部极值,可视为一类具有全局寻优能力的人工智能算法.本文研究了两类基于量子退火的RSA公钥密码攻击算法(分解大整数N=pq):一是将密码攻击数学方法转为组合优化问题或指数级空间搜索问题,通过Ising模型或QUBO模型求解,提出了乘法表的高位优化模型,建立新的降维公式,使用D-Wave Advantage分解了 200万整数2269753.大幅度超过普渡大学、Lockheed Martin和富士通等实验指标,且Ising模型系数h范围缩小了 84%,系数J范围缩小了 80%,极大地提高了分解成功率,这是一类完全基于D-Wave量子计算机的攻击算法;二是基于量子退火算法融合密码攻击数学方法优化密码部件的攻击,采用量子退火优化CVP问题求解,通过量子隧穿效应获得比Babai算法更近的向量,提高了 CVP问题中光滑对的搜索效率,在D-Wave Advantage上实现首次50比特RSA整数分解.实验表明,在通用量子计算机器件进展缓慢情况下,D-Wave表现出更好的现实攻击能力,且量子退火不存在NISQ量子计算机VQA算法的致命缺陷贫瘠高原问题:算法会无法收敛且无法扩展到大规模攻击.

一种模拟绝热量子计算的适应度地形探索算法

将优化问题抽象成目标函数后,目标函数和启发式优化算法的匹配程度决定了优化求解的效率.为反映目标函数的优化特征并指导优化算法及其参数的选择,本文模拟绝热量子计算中的多基态演化,提出了一种适应度地形探索算法.根据基态波函数倾向于向势能较小处收敛且收敛程度受量子效应强度影响的特性,用目标函数编码势能场后算法引入了一个量子效应递减的多基态演化过程,用其持续收敛的基态波函数簇反映目标函数的适应度地形.根据量子路径积分,算法由尺度递减的扩散蒙特卡罗(diffusion Monte Carlo,DMC)实现.实验表明算法综合直观地反映了适应度地形的众多特征,所得信息能直接指导后续优化,其计算模式和启发式优化相似,无需引入其他计算,这为适应度地形研究引入了新的视角.

基于模拟退火量子遗传算法的焊接机器人轨迹规划

针对焊接机器人在焊接过程中经常出现的轨迹规划问题,以六自由度机械臂PUMA 560为研究对象,采用笛卡尔空间规划轨迹,并利用混合算法,以关节惯性力矩变化量最小为优化目标,对不同末端位置的各个关节惯性力矩进行优化,从而消除了机械臂焊接过程中的运行不稳定、关节运动不平稳等问题。克服了模拟退火算法收敛速度慢及量子遗传算法局部寻优能力差等问题,成功规划出机械臂关节惯性力矩最优轨迹。MATLAB仿真结果表明,模拟退火量子遗传算法收敛时间相比传统遗传算法缩短30.56%,并且优化了关节惯性力矩,验证了该算法的可行性,可为后续研究奠定基础。

Multipath Selection Algorithm Based on Dynamic Flow Prediction

Traditional traffic management techniques appear to be incompetent in complex data center networks, so proposes a load balancing strategy based on Long Short-Term Memory (LSTM) and quantum annealing by Software Defined Network (SDN) to dynamically predict the traffic and comprehensively consider the current and predicted load of the network in order to select the optimal forwarding path and balance the network load. Experiments have demonstrated that the algorithm achieves significant improvement in both system throughput and average packet loss rate for the purpose of improving network quality of service.

基于QUBO模型的信用卡最优获利组合规划

在银行信用卡或相关的贷款业务中,为最大化银行收益、方便银行对客户授信,针对不同信用卡设定不同阈值的情况下进行投资组合,对模拟数据进行归一化处理,建立信用卡最优投资组合二次无约束二值优化(QUBO)模型,使用模拟退火算法求解模型得到单一信用卡与三张信用卡的最大收益阈值组合。进一步通过量子降维方法优化二次无约束二值优化(QUBO)模型,最终得到信用卡选择与阈值的双重最优组合,得出最大收益,辅助提高银行的业务竞争能力。