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[统计数据] 自旋玻璃的能量景观网络 [推广有奖]

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nandehutu2022 在职认证  发表于 2022-3-8 19:28:00 来自手机 |AI写论文

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摘要翻译:
我们研究了自旋玻璃模型能量景观的拓扑结构,并通过观察固有结构的连通性和非连通性图研究了挫折对其的影响。连通性网络表示能量极小值的邻接性,而非连通性网络则表示能量屏障的高度。这两个图都是通过精确计数最近邻相互作用达到27个自旋大小的受挫自旋玻璃的二维正方形晶格来构造的。能量景观极小值的计数和解析平均场近似表明,这些极小值服从高斯分布,连通图的log-Weibull度分布为形状$kappa=8.22$和尺度$lambda=4.84$。为了研究挫折对这些结果的影响,我们引入了一个无挫折自旋玻璃模型,证明了它的连通度分布呈现幂律行为,指数为-3.46,这类似于蛋白质和Lennard-Jones团簇的幂律形式。
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英文标题:
《The energy landscape networks of spin-glasses》
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作者:
Hamid Seyed-allaei, Hamed Seyed-allaei, Mohammad Reza Ejtehadi
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最新提交年份:
2008
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分类信息:

一级分类:Physics        物理学
二级分类:Statistical Mechanics        统计力学
分类描述:Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变,热力学,场论,非平衡现象,重整化群和标度,可积模型,湍流
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一级分类:Physics        物理学
二级分类:Disordered Systems and Neural Networks        无序系统与神经网络
分类描述:Glasses and spin glasses; properties of random, aperiodic and quasiperiodic systems; transport in disordered media; localization; phenomena mediated by defects and disorder; neural networks
眼镜和旋转眼镜;随机、非周期和准周期系统的性质;无序介质中的传输;本地化;由缺陷和无序介导的现象;神经网络
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英文摘要:
  We have studied the topology of the energy landscape of a spin-glass model and the effect of frustration on it by looking at the connectivity and disconnectivity graphs of the inherent structure. The connectivity network shows the adjacency of energy minima whereas the disconnectivity network tells us about the heights of the energy barriers. Both graphs are constructed by the exact enumeration of a two-dimensional square lattice of a frustrated spin glass with nearest-neighbor interactions up to the size of 27 spins. The enumeration of the energy-landscape minima as well as the analytical mean-field approximation show that these minima have a Gaussian distribution, and the connectivity graph has a log-Weibull degree distribution of shape $\kappa=8.22$ and scale $\lambda=4.84$. To study the effect of frustration on these results, we introduce an unfrustrated spin-glass model and demonstrate that the degree distribution of its connectivity graph shows a power-law behavior with the -3.46 exponent, which is similar to the behavior of proteins and Lennard-Jones clusters in its power-law form.
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PDF链接:
https://arxiv.org/pdf/710.5403
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关键词:connectivity distribution localization interactions Statistical glass effect landscape 蛋白质 挫折

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