从原子到超原子的原子层次新机遇

为何超原子如此重要？从发展过程来体会，是因为终于可以把纷繁复杂的团簇结构以量子力学属性实现物理规律把握，从而为以团簇作为基元的物性表征与调控包括相关的制造和功能应用提供了基于原子层次的抓手. 因此可以认为，由团簇科技发展到超原子的物理学研究是必然的，所以，我们提出了超原子物理学的概念和范畴. 超原子作为归属于分子的多原子复杂系统，它的电子结构与原子有相近性，凸显了超原子系统中相互作用有深刻且丰富的物理内涵. 依托于原子物理学的巨大成就，将原子层次的科技能力结合到超原子研究上，将开辟新的领域方向，促进从结构出发的传统研究思路转变到以功能为核心的研究范式，从而带来新的发展机遇.     

A hierarchical feature graph matching method for recognition of complex human activities

Complex human activities in natural videos are often composed of several atomic-level actions organized hierarchically. We should not only consider the appearance variability of these action units, but also model the spatiotemporal relationships between them when recognizing such high-level complex activities. In this paper, we focus on the problem of recognition of complex human activities in an example-based video retrieval framework and propose a new method based on hierarchical feature-graph matching. A video depicting an activity is represented as a high-level feature graph (HLFG), and each node of the HLFG is a mid-level feature graph (MLFG) constructed on a local collection of spatiotemporal interest points. MLFG, the first level of our two-level graph structure, describes the local feature contents and spatiotemporal arrangements of interest points. HLFG, the second level, describes the appearance variability and spatiotemporal arrangements of atomic-level actions in a way. Final recognition is accomplished by matching the HLFGs of the query and test videos, and matching two HLFGs involves matching the MLFGs between them. We use an efficient spectral method to solve these two graph-matching problems. Our method does not require any preprocessing and gives reasonable results with even a small number of query examples. We evaluate our approach with one publicly available complex human activity dataset and achieve results comparable to other systems that have studied this problem.     

Magnetic Coupling Induced Self-Assembly at Atomic Level

Developing accurate self-assembly is the key for constructing functional materials from a bottom-up approach.At present, it is mainly hindered by building blocks and driving modes. We design a new self-assembly method based on the magnetic coupling between spin-polarized electrons. First-principles calculations show that spinpolarized electrons from different endohedral metallofullerene(EMF) superatoms can pair each other to ensure a one-dimensional extending morphology. Furthermore, without ligand passivation, the EMF superatoms maintain their electronic structures robustly in self-assembly owing to the core-shell structure and the atomic-like electron arrangement rule. Therefore, it should noted that the magnetic coupling of monomeric electron spin polarization can be an important driving mechanism for high-precision self-assembly. These results represent a new paradigm for self-assembly and offer fresh opportunities for functional material construction at the atomic level.     

Improving direct state measurements by using rebits in real enlarged Hilbert spaces

We propose a protocol to improve the accuracy of direct complex state measurements (DSM) by using rebits in real Hilbert spaces. We show that to improve the accuracy, the initial complex state should be decomposed into the real and imaginary parts and stored in an extended state (rebit) which can be tracked individually by two bases of an extra qubit. For pure states, the numerical calculations show that the trace distances between the true state and the reconstructed state obtained from the rebit method are more precise than those ones obtained from the usual DSM and quantum state tomography (SQT) because the number of projective measurements is reduced. For mixed states, the rebit method gives the same accuracy in comparison to the usual DSM, while it is less precise than QST. Its precision is also significantly improved when using nearly-pure states. Our proposal holds promises as a reliable tool for quantum computation, testing of quantum circuits by using only real amplitudes.     

量子相干态的二维电子光谱测量的原理、应用和发展

二维电子光谱是一种同时具有高的时间分辨率和光谱分辨率的非线性光谱学方法.它不仅可以对凝聚相分子复杂动力学过程进行直接测量,还可以测量不同电子态、电子态-振动态之间的量子相干过程.2007年,Flemming课题组利用二维电子光谱于低温77 K的条件下在捕光天线蛋白Fenna-Matthews-Olson中发现了能量传递过程存在量子相干现象.尽管后续的实验研究表明,该体系中实验观测到的量子相干现象不可能是由单纯的电子态相干引起的,然而这一实验现象的报道极大地激发了人们对天然或人工模拟光合系统中存在量子相干传能途径的探索,目前还是一个相当活跃的研究领域.本文旨在通过介绍二维电子光谱学原理、装置及其在光合作用体系能量传递中量子相干现象的应用,使二维电子光谱这种实验方法能够在更多的研究领域得以普及与推广.     

Molecular dynamics study of temperature-dependent ripples in monolayer and bilayer graphene on 6H—SiC surfaces

Using classical molecular dynamics and a simulated annealing technique,we show that microscopic corrugations occur in monolayer and bilayer graphene on 6H-SiC substrates.From an analysis of the atomic configurations,two types of microscopic corrugations are identified,namely periodic ripples at room temperature and random ripples at high temperature.Two different kinds of ripple morphologies,each with a periodic structure,occur in the monolayer graphene due to the existence of a coincidence lattice between graphene and the SiC terminated surface(Si-or C-terminated surface).The effect of temperature on microscopic ripple morphology is shown through analysing the roughness of the graphene.A temperature-dependent multiple bonding conjugation is also shown by the broad distribution of the carbon-carbon bond length and the bond angle in the rippled graphene on the SiC surface.These results provide atomic-level information about the rippled graphene layers on the two polar faces of the 6H-SiC substrate,which is useful not only for a better understanding of the stability and structural properties of graphene,but also for the study of the electronic properties of graphene-based devices.     

Pulse coding off-chip learning algorithm for memristive artificial neural network

Memristive neural network has attracted tremendous attention since the memristor array can perform parallel multiply-accumulate calculation (MAC) operations and memory-computation operations as compared with digital CMOS hardware systems. However, owing to the variability of the memristor, the implementation of high-precision neural network in memristive computation units is still difficult. Existing learning algorithms for memristive artificial neural network (ANN) is unable to achieve the performance comparable to high-precision by using CMOS-based system. Here, we propose an algorithm based on off-chip learning for memristive ANN in low precision. Training the ANN in the high-precision in digital CPUs and then quantifying the weight of the network to low precision, the quantified weights are mapped to the memristor arrays based on VTEAM model through using the pulse coding weight-mapping rule. In this work, we execute the inference of trained 5-layers convolution neural network on the memristor arrays and achieve an accuracy close to the inference in the case of high precision (64-bit). Compared with other algorithms-based off-chip learning, the algorithm proposed in the present study can easily implement the mapping process and less influence of the device variability. Our result provides an effective approach to implementing the ANN on the memristive hardware platform.     

Density function study transition metal chromium-doped alkali clusters: the finding of magnetic superatom

The structures, stabilities and magnetic properties of CrX_n (X = Na, Rb and Cs; n up to 9) clusters are studied using density functional theory to search for the stable magnetic superatoms. The geometrical optimisations indicate the ground-state structures of CrX_n evolve toward a close packed structure with an interior Cr atom surrounded by X atoms as the cluster size increase. Their stabilities are analysed by the relative energy, gain in energy (ΔE(n)) and the highest unoccupied molecular orbital and lowest unoccupied molecular orbital gaps. Furthermore, the magnetic moments of CrX_n clusters show an odd–even oscillation. Here, we mainly focus on the CrX₇ (X = Na, Rb and Cs) clusters due to the same valence count as the known stable magnetic superatoms VNa₈, VCs₈ and TiNa₉. Although these clusters all have a filled electronic configuration 1S²1P⁶ and large magnetic moment 5 μ_B, our studies indicate that only CrNa₇ is highly stable compared to its nearest neighbours, while CrRb₇ and CrCs₇ clusters are less stable. This suggests that Cr-doped Na₇ is most appropriate for filled electronic configuration and CrNa₇ is shown to be a stable magnetic superatom. More interesting, we find CrRb₈ and CrCs₈ with the filled electronic configuration 1S²1P⁶ have higher stability and large magnetic moment 6 μ_B in their respective series.     

Making and breaking covalent bonds across the magnetic transition in the giant magnetocaloric material Gd5(Si2Ge2)

A temperature-dependent, single crystal x-ray diffraction study of the giant magnetocaloric material, Gd5(Si2Ge2), across its Curie temperature (276 K) reveals that the simultaneous orthorhombic to monoclinic transition occurs by a shear mechanism in which the (Si, Ge)-(Si,Ge) dimers that are richer in Ge increase their distances by 0.859(3) A and lead to twinning. The structural transition changes the electronic structure, and provides an atomic-level model for the change in magnetic behavior with temperature in the Gd5(SixGe1-x)(4).     

Strong lateral growth and crystallization via two-dimensional allotropic transformation of semi-metal Bi film

Two-dimensional (2D) nano-objects, such as metallic nanofilms are the most fundamental building blocks for nanoelectronics devices. However, the fabrication of highly ordered nanofilms has been difficult because of well known Stranski-Krastanov growth, which results in rough growth front and high density grains. Here we report on the unusual high-quality film growth of Bi on a Si surface with atomic-level surface/interface smoothness and high film crystallinity. The formation of a newly discovered 2D allotrope was clarified to initiate its strong 2D growth. Above several-monolayer thickness, the 2D allotrope transforms into a single-crystalline film with bulk-like layered structure. Our study unveils the atomistic growth process of nano-sized Bi, and the obtained knowledge here will be generally applicable for the fabrication of various nano-devices using this intriguing material that shows rich thermal, magnetic, electronic properties in nanometer scale.     

Zero-lag synchronization in coupled time-delayed piecewise linear electronic circuits

We investigate and report an experimental confirmation of zero-lag synchronization (ZLS) in a system of three coupled time-delayed piecewise linear electronic circuits via dynamical relaying with different coupling configurations, namely mutual and subsystem coupling configurations. We have observed that when there is a feedback between the central unit (relay unit) and at least one of the outer units, ZLS occurs in the two outer units whereas the central and outer units exhibit inverse phase synchronization (IPS). We find that in the case of mutual coupling configuration ZLS occurs both in periodic and hyperchaotic regimes, while in the subsystem coupling configuration it occurs only in the hyperchaotic regime. Snapshots of the time evolution of outer circuits as observed from the oscilloscope confirm the occurrence of ZLS experimentally. The quality of ZLS is numerically verified by correlation coefficient and similarity function measures. Further, the transition to ZLS is verified from the changes in the largest Lyapunov exponents and the correlation coefficient as a function of the coupling strength. IPS is experimentally confirmed using time series plots and also can be visualized using the concept of localized sets which are also corroborated by numerical simulations. In addition, we have calculated the correlation of probability of recurrence to quantify the phase coherence. We have also analytically derived a sufficient condition for the stability of ZLS using the Krasovskii-Lyapunov theory.     

Quantitative strain analysis of flip-chip electronic packages using phase-shifting moiré interferometry

In order to gauge the reliability of electronic packages, it is valuable to analyze thermally induced displacements and strains around bimaterial corners and within interconnections. The increased demand for computing performance has created increasingly complex electronic packages with miniaturized features, making it increasingly difficult to extract these quantities. Often, material properties at these length scales are not fully known, making modeling and simulation problematic. Thus, determining displacements and strains experimentally is attractive. In this study, an advanced flip-chip package with fine interconnection features was analyzed using phase-shifting moiré interferometry (PSMI) in conjunction with image analysis software developed for this purpose. Before the analysis, PSMI was qualified using an isotropic solid undergoing uniform thermal contraction, which yielded a displacement precision of ±4 nm. Then a high-magnification, high-resolution displacement and strain analysis was performed for a small cross-sectional region of the flip-chip package containing 20–100 μm sized features. The analysis quantifies these results and gives displacements and strains obtained by differentiating the displacement data using a strain-energy-based finite element formulation.     

A Hyperchaotic Attractor with Multiple Positive Lyapunov Exponents

There are many hyperchaotic systems, but few systems can generate hyperchaotic attractors with more than three PLEs （positive Lyapunov exponents）. A new hyperchaotic system, constructed by adding an approximate time-delay state feedback to a five-dimensional hyperchaotic system, is presented. With the increasing number of phase-shift units used in this system, the number of PLEs also steadily increases. Hyperchaotic attractors with 25 PLEs can be generated by this system with 32 phase-shift units. The sum of the PLEs will reach the maximum value when 23 phase-shift units are used. A simple electronic circuit, consisting of 16 operational amplifiers and two analogy multipliers, is presented for confirming hyperchaos of order 5, i.e., with 5 PLEs.     

基于人工神经网络的制冷系统工况模拟

针对人工神经网络技术在制冷空调系统中的仿真应用,本文建立了单回路制冷系统的性能仿真系统。通过实验模拟制冷系统在夏季的负荷变动情况,得到了用于神经网络模型训练的样本数据。对制冷系统进行多种神经网络结构的建模,并进行了神经网络中各种结构参数对模型精度影响的分析。利用训练好的双隐层神经网络模型,研究了空调机组性能的影响因素,包括压缩机频率、室内外温度等。模拟结果表明,机组EER随着压缩机频率增加先增加后减少,随着室内温度升高而增加,随着室外温度升高而减少。结果表明,人工神经网络方法是分析制冷机组性能的一种有效途径。     

Electronic and transport properties of artificial gold chains

We study the electronic and transport properties of artificial Au atomic chains on a NiAl(110) surface template using state-of-the-art first principles calculations. Au chains display remarkable one-dimensional electronic properties that can be tuned by the selective adsorption of small molecules: a single CO group is shown to modulate the electronic wave functions, acting as a "chemical scissor" along the chain, to strongly modify the coherent transport properties of the system, and to help design one-dimensional nanodevices through artificial profiling of energy barriers.     

Alignment of heavy ion therapy center vertical terminal

ABSTRACT

Wuwei heavy ion therapy center is the first Chinese heavy ion accelerator facility developed for cancer therapy, in which four terminals are distributed and the height of the vertical terminal is up to 18?m. Installation units of vertical terminal are diverse and complex, moreover, these units present poor alignment visibility. Thereby, it is difficult to perform the alignment among these components. Based on the laser tracker and high precision three-dimensional surveying control network, this paper proposes an efficient alignment method using multiple conversion of magnet fiducial data and pre-alignment of complex magnet unit. All the components are successfully aligned, and meanwhile the installation efficiency of vertical terminals is improved. Alignment accuracy of magnets is less than 0.1?mm. Error analysis presents that this alignment method achieves its goal.     

Electromagnetically induced transparency with Rydberg atoms

We present a theory of electromagnetically induced transparency in a cold ensemble of strongly interacting Rydberg atoms. Long-range interactions between the atoms constrain the medium to behave as a collection of superatoms, each comprising a blockade volume that can accommodate at most one Rydberg excitation. The propagation of a probe field is affected by its two-photon correlations within the blockade distance, which are strongly damped due to low saturation threshold of the superatoms. Our model is computationally very efficient and is in quantitative agreement with the results of the recent experiment of Pritchard et al. [Phys. Rev. Lett. 105, 193603 (2010)].     

Two-dimensional matter: order,curvature and defects

Many systems in nature and the synthetic world involve ordered arrangements of units on two-dimensional surfaces. We review here the fundamental role payed by both the topology of the underlying surface and its Gaussian curvature. Topology dictates certain broad features of the defect structure of the ground state but curvature-driven energetics control the detailed structure of the ordered phases. Among the surprises are the appearance in the ground state of structures that would normally be thermal excitations and thus prohibited at zero temperature. Examples include excess dislocations in the form of grain boundary scars for spherical crystals above a minimal system size, dislocation unbinding for toroidal hexatics, interstitial fractionalization in spherical crystals and the appearance of well-separated disclinations for toroidal crystals. Much of the analysis leads to universal predictions that do not depend on the details of the microscopic interactions that lead to order in the first place. These predictions are subject to test by the many experimental soft- and hard-matter systems that lead to curved ordered structures such as colloidal particles self-assembling on droplets of one liquid in a second liquid. The defects themselves may be functionalized to create ligands with directional bonding. Thus, nano- to meso-scale superatoms may be designed with specific valency for use in building supermolecules and novel bulk materials. Parameters such as particle number, geometrical aspect ratios and anisotropy of elastic moduli permit the tuning of the precise architecture of the superatoms and associated supermolecules. Thus, the field has tremendous potential from both a fundamental and materials science/supramolecular chemistry viewpoint.     

人工神经网络在配煤过程状态建模中的应用研究

本文详细介绍了人工神经网络应用于状态建模的方法．对神经网络应用中的一些难点提出了切实可行且有效的解决措施，并举例作了应用示范．同时还介绍了神经网络方法应用于优化动力配煤的情况，并就神经网络方法在优化动力配煤中的进一步应用作了展望．     

基于原子操纵技术的人工量子结构研究

扫描隧道显微镜原子操纵技术是指利用扫描探针在特定材料表面以晶格为步长搬运单个原子或分子的技术.它是纳米尺度量子物理与器件研究领域一种独特而有力的研究手段.利用这种手段,人们能够以原子或分子为单元构筑某些常规生长或微加工方法难以制备的人工量子结构,通过对格点原子、晶格尺寸、对称性、周期性的高度控制,实现对局域电子态、自旋序、以及能带拓扑特性等量子效应的设计与调控.原子操纵技术与超快测量及自动控制技术的结合,使得人们能够进一步研究原子级精准的量子器件,因而该技术成为探索未来器件新机理、新工艺的重要工具.本文首先简介原子操纵方法的发展过程和技术要点,然后分别介绍人工电子晶格、半导体表面人工量子点、磁性人工量子结构、人工结构中的信息存储与逻辑运算、单原子精度原型器件等方面的最新研究进展,以及单原子刻蚀和自动原子操纵等方面的技术进展,最后总结并展望原子操纵技术的应用前景和发展趋势.