基于Sigmoid函数局部视觉适应模型的真实影像再现

为解决图像采集与显示设备之间的动态范围差异,色调映射技术试图建立一种由高到低的动态范围映射关系,可用于一般图像的真实影像再现.在不同亮度适应水平下,人眼能产生不同的响应特性及对比度敏感性,从而同时响应不同明暗的光强.由此建立了一种局部视觉适应的再现算法,采用具有参数控制的Sigmoid函数来模拟视觉适应的S形非线性特点,得到不同局部亮度适应水平下的压缩曲线,因此能较好地协调图像整体对比度、亮度调整与局部增强之间的关系,在增强图像较暗区域的同时,极大程度地保持亮区细节.经主观评价与特征统计参数相结合的方法验证,该算法能有效地实现动态范围压缩,保持图像细节而避免伪像,具有一定的色彩恒定性,且复杂度低,具有很好的实用性.     

一个可解的1+1维U(1)规范模型

本文提出一个1+1维U(1)规范模型,准确求解了其能谱及相应的用费米子算符表示的能量本征态.     

量子生成模型

近年来,很多基于生成模型的机器学习算法,如生成对抗网络、玻尔兹曼机、自编码器等,在数据生成、概率模拟等方面有广泛的应用.另一方面,融合量子计算和经典机器学习的量子机器学习算法也不断被提出.特别地,量子生成模型作为量子机器学习的分支,目前已有很多进展.量子生成算法是一类量子-经典混合算法,算法中引入参数量子线路,通过执行...     

基于Sigmoid-iCAM色貌模型的真实影像再现算法

为了模拟人类视觉系统成像机制,真实再现人眼对外界场景的视觉感知,为机器视觉提供符合生物视觉特性的理想图像,从色度学的角度研究了彩色图像的真实影像再现技术。针对色貌模型存在图像模糊、对比度低的缺点,在iCAM色貌模型的基础上,引入了人工神经网络的非线性Sigmoid函数,提出了基于Sigmoid-iCAM色貌模型的真实影像再现算法,并给出了该模型处理不同类型图像的控制参数统计规律。与基于CIECAM02、iCAM色貌模型的真实影像再现算法相比,该算法在对色调失真图像实现颜色复原的同时,有效地提高了图像的对比度和局部细节,很好地实现了视觉系统的颜色恒定性。     

计算的量子飞跃

利用量子力学的迭加和纠缠等特性进行的量子计算是计算技术的巨大飞跃。它能够比经典计算远为有效地解决一些问题。例如最为著名的Ｓｈｏｒ的算法原则上能够以多项式的时间因子化大的合数,从而使得经典计算机难以计算的这一问题得以解决。文章介绍了至今所发现的主要量子算法的基本原理和步骤,并且概述了量子计算的优越性、现状和发展前景,同时讨论了量子计算在物理学上的应用和意义。     

不同环境模型下Bell型纠缠态衰退行为的比较

通过建立三种不同的环境模型(单一热库模型,共同热库模型和独立热库模型),利用赝模理论的方法,分析讨论了初始处于Bell型纠缠态系统的纠缠演化特性.研究发现在单一热库模型中Bell型初始纠缠态cosθ|ee〉+sinθ|gg〉的纠缠保持时间最长,而cosθ|eg〉+sinθ|ge〉态的纠缠演化对具体的环境模型依赖很大;同时对这两种不同类型的Bell型纠缠态在相同环境模型中的纠缠衰退行为进行了比较.     

法拉第镜不完善对连续变量量子密钥分发系统的影响（英文）

采用连续变量量子密钥分发的纠缠模型,在反向协商情况下,研究法拉第镜不完善对系统安全密钥速率的影响.结果表明,不完善的法拉第镜会降低系统实际的密钥速率,并且降低安全通信距离,且随着法拉第镜失偏角度的增大而增大.此外,使用大的调制方差,可以降低法拉第镜不完善对系统的影响.     

感性神经元模型及其动力学特性研究

神经元的大小属于介观尺度范围,本文考虑神经元的电感特性,建立了由细胞膜电感、膜电容、钾离子忆阻器和氯离子电阻构成的神经元经典电路模型和介观电路模型.利用经典电路理论和介观电路的量子理论,推导了在外部冲击激励下神经元细胞膜电压响应的表达式.将枪乌贼神经元的电生理参数代入膜电压表达式并计算可知,两种模型下的膜电压均先增大后减小,最后达到零值的静息状态,且其能量主要集中在0—30 Hz的脑电频率范围内.进一步比较发现,介观电路模型下膜电压的峰值及达到峰值所需的时间(达峰时间)均低于经典电路模型下的值,并与枪乌贼轴突受到刺激后的实验结果更接近,说明介观电路模型更能反应神经元受到刺激后的生理特征.基于介观电路模型,随着外部激励强度的增加,膜电压的峰值增加且达峰时间变短.膜电压峰值及达峰时间等参数更易受神经元膜电容的影响.神经元的介观电路模型对于理解神经元受到刺激后的兴奋性,推动受大脑功能启发的量子神经网络的发展等具有重要意义.     

感性神经元模型及其动力学特性研究

神经元的大小属于介观尺度范围,本文考虑神经元的电感特性,建立了由细胞膜电感、膜电容、钾离子忆阻器和氯离子电阻构成的神经元经典电路模型和介观电路模型.利用经典电路理论和介观电路的量子理论,推导了在外部冲击激励下神经元细胞膜电压响应的表达式.将枪乌贼神经元的电生理参数代入膜电压表达式并计算可知,两种模型下的膜电压均先增大后减小,最后达到零值的静息状态,且其能量主要集中在0—30 Hz的脑电频率范围内.进一步比较发现,介观电路模型下膜电压的峰值及达到峰值所需的时间(达峰时间)均低于经典电路模型下的值,并与枪乌贼轴突受到刺激后的实验结果更接近,说明介观电路模型更能反应神经元受到刺激后的生理特征.基于介观电路模型,随着外部激励强度的增加,膜电压的峰值增加且达峰时间变短.膜电压峰值及达峰时间等参数更易受神经元膜电容的影响.神经元的介观电路模型对于理解神经元受到刺激后的兴奋性,推动受大脑功能启发的量子神经网络的发展等具有重要意义.     

囚禁离子非线性J-C模型量子态保真度

用全量子理论研究驻波激光场与囚禁离子相互作用系统中量子态保真度,详细讨论离子质心在驻波激光场中位置及离子初始状态对保真度的影响.结果表明:随着囚禁离子从远离驻波激光场波节处向波节处移动,量子态保真度振荡频率越来越高,振荡幅度几乎不变,且保真度到达第一个极小值所用时间越来越短,但不会出现信息完全失真;随着囚禁离子处于基态概率增加,量子态保真度振荡频率几乎不变,振荡幅度越来越小,也不会出现信息完全失真;在信息储存或传递过程中,囚禁离子量子态失真比系统和驻波场量子态失真小.     

Identical particles, projectors and probabilities

In this Letter we reanalyze the old problem of the probability interpretation of the wave function in the case of identical particles. It is shown that, although the construction of observable single particle position (or momentum) operators is not easy nor natural, it is possible to bypass the problem through the construction of projectors that make probability computations completely systematic, easy to understand and adequate to the spirit of Quantum Mechanics.     

Particle mixing, flavor condensate and dark energy

The mixing of neutrinos and quarks generate a vacuum condensate that, at the present epoch, behaves as a cosmological constant. The value of the dark energy is constrained today by the very small breaking of the Lorentz invariance.     

采用视觉细胞响应模型的小目标复杂背景抑制

为了提高地面和云层等红外复杂背景下弱小目标的检测性能,提出了一种基于视觉细胞响应模型的红外弱小目标背景抑制新方法.首先利用简单细胞的感受野计算模型将原始图像采用Gabor函数卷积获得相同大小的两幅图像|然后采用设计的复杂细胞响应的非线性汇聚策略函数对获得的两幅图像进行融合处理,从而将红外图像中弱小目标和背景杂波分离,达到抑制背景的目的|最后采用自适应阈值分割技术得到目标点,实现了对红外弱小目标的检测跟踪.实验结果显示,与去局部均值和最大中值滤波两种滤波方法相比较,该方法能有效地检测出信杂比较低的弱小目标信号.     

采用视觉细胞响应模型的小目标复杂背景抑制

为了提高地面和云层等红外复杂背景下弱小目标的检测性能,提出了一种基于视觉细胞响应模型的红外弱小目标背景抑制新方法.首先利用简单细胞的感受野计算模型将原始图像采用Gabor函数卷积获得相同大小的两幅图像;然后采用设计的复杂细胞响应的非线性汇聚策略函数对获得的两幅图像进行融合处理,从而将红外图像中弱小目标和背景杂波分离,达...     

Model apparatus for quantum measurements

We present a model system that behaves as a measurement apparatus for quantum systems should. The device is macroscopic, it interacts with the microscopic system to be measured, and the results of that interaction affect the macroscopic device in a macroscopic, irreversible way. Everything is treated quantum mechanically: the apparatus is defined in terms of its (many) coordinates, the Hamiltonian is given, and time evolution follows Schrödinger's equation. It is proposed that this model be itself used as a laboratory for testing ideas on the measurement process.     

Quantum Kinetic Theory of a Massless Scalar Model in the Presence of a Schwarzschild Black Hole

We employ quantum kinetic theory to investigate local quantum physics in the background of spherically symmetric and neutral black holes formed through the gravitational collapse. For this purpose in mind, we derive and study the covariant Wigner distribution function near to and far away from the black‐hole horizon. We find that the local density of the particle number is negative in the near‐horizon region, while the entropy density is imaginary. These pose a question whether kinetic theory is applicable in the near‐horizon region. We elaborate on that and propose a possible interpretation of how this result might nevertheless be self‐consistently understood.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.     

与两等同Bell态纠缠原子相互作用光场的量子场熵

利用全量子理论,并通过数值计算,研究了初始处于Fock态的单模光场与两等同双能级纠缠原子单光子共振相互作用过程中单模光场量子场熵的时间演化特性.结果发现:当两原子初始处于第一种Bell态时,光场量子场熵的时间演化周期为π/g2(2n+1);随着初始光强的增大,光场与原子之间的量子纠缠现象减弱;特别是当时间t为演化周期的整数倍时,场－原子系统处于退纠缠状态.当两原子初始处于第二种Bell态时,光场量子场熵不随时间变化,恒为零.当两原子初始分别处于第三种和第四种Bell态时,光场量子场熵的时间演化曲线呈现不等幅周期振荡现象;并且随着初始光场光子数的增加,光场量子场熵的振荡周期逐渐增大,但振荡幅值逐渐减小.     

Application of image enhancement method for digital images based on Retinex theory

The image enhancement and implementation of the methods for the digital image enhancement were studied. The characteristics of different image enhancement methods, including contrast enhancement, linear transformation, piecewise linear transformation, grayscale slice transformation and Retinex clearing algorithms were analyzed in detail. Retinex enhancement algorithms were studied and the implementation process for the Retinex algorithm is given. Finally, an example of image enhancement using the multi scale Retinex algorithm (MSR) is achieved. It is shown that MSR can realize the image color constancy, local dynamic range compression, color enhancement and the overall dynamic range compression under certain circumstances.     

Particle diagrams and statistics of many-body random potentials

We present a method using Feynman-like diagrams to calculate the statistical properties of random many-body potentials. This method provides a promising alternative to existing techniques typically applied to this class of problems, such as the method of supersymmetry and the eigenvector expansion technique pioneered in Benet et al. (2001). We use it here to calculate the fourth, sixth and eighth moments of the average level density for systems with m$m$ bosons or fermions that interact through a random k$k$-body Hermitian potential (k≤m$k\le m$); the ensemble of such potentials with a Gaussian weight is known as the embedded Gaussian Unitary Ensemble   (eGUE) (Mon and French, 1975). Our results apply in the limit where the number l$l$ of available single-particle states is taken to infinity. A key advantage of the method is that it provides an efficient way to identify only those expressions which will stay relevant in this limit. It also provides a general argument for why these terms have to be the same for bosons and fermions. The moments are obtained as sums over ratios of binomial expressions, with a transition from moments associated to a semi-circular level density for m<2k$m<2k$ to Gaussian moments in the dilute limit k?m?l$k?m?l$. Regarding the form of this transition, we see that as m$m$ is increased, more and more diagrams become relevant, with new contributions starting from each of the points m=2k,3k,…,nk$m=2k,3k,\dots ,nk$ for the 2n$2n$th moment.