一类不确定混沌系统的观测器同步

基于降维观测器的方法实现了一类具有外部扰动的混沌系统的同步. 无需知道系统外部扰动项的任何信息，就可对驱动系统设计基于降维观测器的响应系统，从而实现了混沌系统的同步. 数值仿真表明该方法是有效的. 关键词： 混沌同步 混沌系统 观测器     

〈111〉晶向冲击加载下单晶铜中纳米孔洞增长的早期动力学行为

利用分子动力学方法模拟计算了单晶铜中纳米孔洞在沿〈111〉晶向冲击加载下增长的早期过程.测量发现不同加载强度下等效孔洞半径随时间近似成线性变化.观测到单孔洞增长的两种位错生长机理：加载强度较低时，只在沿着冲击加载方向的孔洞顶点附近区域有位错的成核和运动；而随着加载强度超过一定阈值，在沿冲击加载和其垂直方向的孔洞顶点区域都观察到位错的成核和运动.在前一种机理作用下，孔洞只沿加载方向增长；在后一种机理作用下，孔洞同时沿加载和垂直于加载方向增长.分析孔洞表面原子的位移历史，发现沿加载及与其垂直方向的孔洞顶点沿径向的速度基本恒定，由此提出了一个孔洞生长模型，可以解释孔洞增长的线性生长规律. 关键词： 纳米孔洞 分子动力学 冲击加载 位错     

双色激光场中1维共线氢分子离子的经典动力学研究

 运用经典理论方法,并采用辛算法数值求解了双色激光场作用下1维共线氢分子离子(H₂⁺)的哈密顿正则方程,得到了氢分子离子在激光场下的经典轨迹。计算了单色场和双色场下氢分子离子(H₂⁺)的存活几率、电离几率、解离几率、库仑爆炸几率随时间的演化,分析了双色场的相位、强度、强度比及倍频的变化对氢分子离子动力学行为的影响,并给出了相应的物理解释。     

多体相互作用对高压固氦状态方程的影响

采用量子化学自洽场方法及原子团簇理论对固氦晶格原子势能进行多体展开，定量确定了最近邻原子间距R在0.26—0.175nm之间，短程的两体到五体相互作用对晶体结合能及压缩特性的贡献，并对不同间距下多体展开式的截断位置进行了讨论. 结果表明：当最近邻原子间距R在0.26—0.175 nm之间取值，在具有hcp相结构的晶格中，氦原子势能的多体展开式是一收敛的交错型级数，该级数中两体项、四体项为正值，而三体项、五体项为负值. 当R在0.26—0.23 nm之间取值时, 仅保留级数中两体和三体项就能很好地描述晶格原子势能；当R在0.23—0.20 nm之间取值，多体展式需要展开到四体相互作用项；当R在0.20—0.175 nm之间取值必须再加入五体项贡献. 考虑到五体相互作用后，理论计算已能圆满地解释目前固氦等温压缩数据，其最大压力达 60GPa. 关键词： 固氦 状态方程 多体相互作用     

外应力场下铁磁/反铁磁双层膜系统的铁磁共振性质

从系统能量出发，采用Smith和Beljers理论方法研究了铁磁/反铁磁双层膜系统在外应力场下的铁磁共振现象.本模型中铁磁薄层具有单轴磁晶各向异性和立方磁晶各向异性，而反铁磁层非常薄因而其能量可忽略.推导出了该系统的铁磁共振频率和频谱宽度的解析式.结果表明：外应力场仅在低磁场下对具有立方磁晶各向异性系统的铁磁共振有影响，且区分弱磁场和强磁场的临界场依赖于外应力场的方向. 关键词： 铁磁/反铁磁双层膜 交换偏置 铁磁共振 应力场     

A new quantum group associated with a ‘nonstandard’ braid group representation

A new quantum group is derived from a nonstandard braid group representation by employing the Faddeev-Reshetikhin-Takhtajan constructive method. The classical limit is not a Lie superalgebra, despite relations like x ²–y ²=0. We classify all finite-dimensional irreducible representations of the new Hopf algebra and find only one- and two-dimensional ones.     

超短脉冲激光微束对细胞作用的研究

本文详细地介绍了我们自己设计和安装的一个Nd:YAG超短脉冲激光微束系统,该系统分成二个部分:激光源和显微镜。由电光调Q非稳腔Nd:YAG激光倍频后得到355nm紫外光进入显微镜并由物镜聚焦。同时,这超短脉冲激光微束照射在细胞上并且在细胞上产生一个可以自恢复的小孔。在文中我们还讨论了超短脉冲激光微束与细胞之间作用效应及机理。     

Few-photon routing via chiral light-matter couplings

A quantum router is one of the essential elements in the quantum network. Conventional routers only direct a single photon from one quantum channel into another. Here, we propose a few-photon router. The active element of the router is a single qubit chirally coupled to two independent waveguides simultaneously, where each waveguide mode provides a quantum channel. By introducing the operators of the scatter-free space and the controllable space, the output state of the one-photon and two-photon scattering are derived analytically. It is found that the qubit can direct one and two photons from one port of the incident waveguide to an arbitrarily selected port of the other waveguide with unity, respectively. However, two photons cannot be simultaneously routed to the same port due to the anti-bunch effect.     

Multi-bright-dark soliton solutions to the AB system in nonlinear optics

The AB system is the basic integrable model to describe unstable baroclinic wave packets in geophysical fluids and the propagation of mesoscale gravity flows in nonlinear optics. On the basis of the spectral analysis of a Lax pair and the inverse scattering method, we establish the Riemann–Hilbert problem of the AB system. Then, the inverse problems are formulated and solved with the aid of the Riemann–Hilbert problem, from which the potentials can be reconstructed according to the asymptotic expansion of the sectional analytic function and the related symmetry relations. As an application, we obtain the multi-bright-dark soliton solutions to the AB system in the reflectionless case and discuss the dynamic behavior of elastic soliton collisions by choosing appropriate free parameters.     

Machine learning-based direct solver for one-to-many problems on temporal shaping of relativistic electron beams

To control the temporal profile of a relativistic electron beam to meet requirements of various advanced scientific applications like free-electron-laser and plasma wakefield acceleration, a widely-used technique is to manipulate the dispersion terms which turns out to be one-to-many problems. Due to their intrinsic one-to-many property, current popular stochastic optimization approaches on temporal shaping may face the problems of long computing time or sometimes suggesting only one solution. Here we propose a real-time solver for one-to-many problems of temporal shaping, with the aid of a semi-supervised machine learning method, the conditional generative adversarial network (CGAN). We demonstrate that the CGAN solver can learn the one-to-many dynamics and is able to accurately and quickly predict the required dispersion terms for different custom temporal profiles. This machine learning-based solver is expected to have the potential for wide applications to one-to-many problems in other scientific fields.