双色激光场中激光强度和脉宽对线性多原子分子离子电离的影响

利用强激光场电离和离解分子来研究分子激发态的波包结构是强场物理的重要研究方向。利用短时指数传播子对称分割法和快速傅里叶变换技术。数值求解了一维含时Schr（oe）dinger方程，探讨了双色激光场中激光的基波和谐波强度之间的不同配比以及脉宽对线性多原子分子离子电离的影响。理论计算结果表明：基波和谐波的相对相位为π时，尽管随着激光的基波和谐波强度之间配比的变化，电离几率随原子间距变化的趋势基本保持不变，但在一定的激光基波强度下(1．2×10^13～1．2×10^15W／cm^2)，激光基波强度的变化可以明显

非传播孤立波及其相互作用的数值模拟

通过数值求解由Miles导出的目前公认的非传播孤立波的控制方程——一个带复共轭项的非线性立方Schr〖AKo¨〗dinger方程,对非传播孤立波进行研究.讨论了Miles方程中的线性阻尼系数α的值,模拟了两个非传播孤立波的相互作用,数值模拟表明,两个波的作用模式依赖于系统的参数,对不同的初始扰动及其演化的计算表明,只有适当的初始扰动才能形成单个稳定的非传播孤立波,否则扰动可能消失或发展成多个孤立波.

超短激光脉冲在不同色散参量光子晶体光纤中传输的数值模拟

为了使得数值模拟更为精确, 采用广义非线性薛定谔方程(GNSE)描述超短激光脉冲在光子晶体光纤中的传输演化过程, 并利用二阶分步傅里叶方法通过求解方程, 数值计算了相同脉宽和能量的超短脉冲在不同色散参量的光子晶体光纤中非线性传输和超连续谱的产生。比较了超短脉冲在光纤不同色散区传输时, 高阶色散和非线性效应对超连续谱的产生以及对脉冲波形演化的影响。结果表明, 相对于超短脉冲中心波长位于光子晶体光纤的正常和反常色散区, 可以相应获得短波波段和长波波段的超连续谱输出, 当超短脉冲中心波长位于零色散波长点时, 通

高功率激光系统中B积分的研究

通过对非线性薛定谔方程的求解,数值模拟了高功率激光系统中钕玻璃的B积分传输规律,并理论分析了B积分对光脉冲的波形和频谱的影响,详细介绍了几种消除B积分影响的方法。这对高功率激光系统中光放大有一定指导意义。

非均匀交换各向异性铁磁介质的非线性表面自旋波

利用Landau Lifshitz方程 ,研究了具有非均匀交换各向异性的半无限大铁磁体的非线性表面自旋波理论。导出了部分钉扎纯交换铁磁介质的磁化强度所满足的边界条件和非线性表面自旋波的色散关系 ,并获得了自旋波振幅沿z方向驻波的一维非线性Schr dinger方程和包络振幅沿平面传播的二维非线性Schr dinger方程 ,结果表明铁磁体磁化强度的包络振幅随时空变化的性质是由二维非线性Schr dinger方程决定的。因此预言铁磁介质的表面非线性激发应是二维孤波的形式。对于弱非线性表面自旋波 ,对非线性Schr dinger方程存在孤子形式解的可能性作了讨论 .

基于量子蒙特卡罗的地震波反演方法

The primary approaches for people to understand the inner properties of the earth and the distribution of the mineral resources are mainly coming from surface geology survey and geophysical/geochemical data inversion and interpretation. The purpose of seismic inversion is to extract information of the subsurface stratum geometrical structures and the distribution of material properties from seismic wave which is used for resource prospecting, exploitation and the study for inner structure of the earth and its dynamic process. Although the study of seismic parameter inversion has achieved a lot since 1950s, some problems are still persisting when applying in real data due to their nonlinearity and ill-posedness. Most inversion methods we use to invert geophysical parameters are based on iterative inversion which depends largely on the initial model and constraint conditions. It would be difficult to obtain a believable result when taking into consideration different factors such as environmental and equipment noise that exist in seismic wave excitation, propagation and acquisition. The seismic inversion based on real data is a typical nonlinear problem, which means most of their objective functions are multi-minimum. It makes them formidable to be solved using commonly used methods such as general-linearization and quasi-linearization inversion because of local convergence. Global nonlinear search methods which do not rely heavily on the initial model seem more promising, but the amount of computation required for real data process is unacceptable. In order to solve those problems mentioned above, this paper addresses a kind of global nonlinear inversion method which brings Quantum Monte Carlo (QMC) method into geophysical inverse problems. QMC has been used as an effective numerical method to study quantum many-body system which is often governed by Schrödinger equation. This method can be categorized into zero temperature method and finite temperature method. This paper is subdivided into four parts. In the first one, we briefly review the theory of QMC method and find out the connections with geophysical nonlinear inversion, and then give the flow chart of the algorithm. In the second part, we apply four QMC inverse methods in 1D wave equation impedance inversion and generally compare their results with convergence rate and accuracy. The feasibility, stability, and anti-noise capacity of the algorithms are also discussed within this chapter. Numerical results demonstrate that it is possible to solve geophysical nonlinear inversion and other nonlinear optimization problems by means of QMC method. They are also showing that Green’s function Monte Carlo (GFMC) and diffusion Monte Carlo (DMC) are more applicable than Path Integral Monte Carlo (PIMC) and Variational Monte Carlo (VMC) in real data. The third part provides the parallel version of serial QMC algorithms which are applied in a 2D acoustic velocity inversion and real seismic data processing and further discusses these algorithms’ globality and anti-noise capacity. The inverted results show the robustness of these algorithms which make them feasible to be used in 2D inversion and real data processing. The parallel inversion algorithms in this chapter are also applicable in other optimization. Finally, some useful conclusions are obtained in the last section. The analysis and comparison of the results indicate that it is successful to bring QMC into geophysical inversion. QMC is a kind of nonlinear inversion method which guarantees stability, efficiency and anti-noise. The most appealing property is that it does not rely heavily on the initial model and can be suited to nonlinear and multi-minimum geophysical inverse problems. This method can also be used in other filed regarding nonlinear optimization.