“自组织临界性”的版本间的差异
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− | + | 在物理学中,'''自组织临界性 Self-organized criticality (SOC)</font>'''是动力系统的一种特性,动力系统有一个临界点作为吸引子 Attractor。它们在相变临界点的宏观行为因此显示了空间或时间尺度不变特性,但不需要把控制参数调整到一个精确的值,因为系统有效地自我调整趋向于临界状态。 | |
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− | + | 这个概念是由 Per Bak,Chao Tang 和 Kurt Wiesenfeld (简称“BTW”)在1987年的《物理评论快报 Physical Review Letters》上的论文中提出的,<ref name=Bak1987>{{cite journal | author =Per Bak, Chao Tang and Kurt Wiesenfeld | year = 1987 | title = Self-organized criticality: an explanation of 1/''f'' noise | journal = Physical Review Letters | volume = 59 | issue = 4 | pages = 381–384 | doi = 10.1103/PhysRevLett.59.381| pmid = 10035754 | bibcode=1987PhRvL..59..381B}} | |
+ | Papercore summary: [https://archive.is/20130704122906/http://papercore.org/Bak1987 http://papercore.org/Bak1987].</ref> 其被认为是复杂性在自然界出现的机制之一。<ref name=Bak1995> | ||
+ | {{cite journal | author =Per Bak, and Maya Paczuski | year = 1995 | title = Complexity, contingency, and criticality | journal =Proc Natl Acad Sci U S A | volume = 92 | pages = 6689–6696 | pmid = 11607561 | doi = 10.1073/pnas.92.15.6689 | issue = 15 | pmc = 41396|bibcode = 1995PNAS...92.6689B }}</ref>它的概念已经被应用于各个领域,比如地球物理学,<ref name=SmalleyTurcotteSolla85>{{cite journal|author1=Smalley, R. F., Jr. |author2=Turcotte, D. L. |author3=Solla, S. A. | year = 1985| title = A renormalization group approach to the stick-slip behavior of faults | ||
+ | | journal = Journal of Geophysical Research| bibcode = 1985JGR....90.1894S| doi = 10.1029/JB090iB02p01894| volume = 90 | issue = B2| pages = 1894|url=https://semanticscholar.org/paper/6776d17957204c198e278bda98c935ab1cf8f22b }}</ref> 物理宇宙学,进化生物学和生态学,生物启发计算和优化(数学) ,经济学,量子引力,社会学,太阳物理学,等离子物理学,神经生物学等。<ref name=LinkenkaerHansen2001> | ||
+ | {{cite journal |author1=K. Linkenkaer-Hansen |author2=V. V. Nikouline |author3=J. M. Palva |author4=R. J. Ilmoniemi. |name-list-style=amp | year = 2001 | title = Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations | journal = J. Neurosci. | volume = 21 | pages = 1370–1377 | pmid = 11160408 | issue = 4|doi=10.1523/JNEUROSCI.21-04-01370.2001 |pmc=6762238 }}</ref><ref name=Beggs2003>{{cite journal |author1=J. M. Beggs |author2=D. Plenz |name-list-style=amp | year = 2006 | title = Neuronal Avalanches in Neocortical Circuits | journal = J. Neurosci. | volume = 23|issue=35 |pages=11167–77 |doi=10.1523/JNEUROSCI.23-35-11167.2003 |pmid=14657176 |pmc=6741045 | ||
+ | }}</ref><ref name=Chialvo2004>{{cite journal | author =Chialvo, D. R. | year = 2004 | title = Critical brain networks | journal = Physica A | volume = 340 | issue =4 | pages = 756–765 | doi = 10.1016/j.physa.2004.05.064 | ||
+ | |arxiv = cond-mat/0402538 |bibcode = 2004PhyA..340..756R | author-link = Dante R. Chialvo }}</ref>'''SOC'''通常在多自由度、强非线性动力学的缓慢驱动非平衡系统中被观察到。自从 BTW 的原始论文以来,已经确定了许多单独的例子,但是到目前为止还没有一组已知的一般特征来保证一个系统将显示 '''<font color="#ff8000"> SOC</font>'''。 | ||
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+ | == 概览== | ||
− | + | '''自组织临界性'''是20世纪下半叶统计物理学及相关领域的众多重要发现之一,这些发现尤其与研究自然界的复杂性有关。例如,[[元胞自动机]]的研究---- 从 Stanislaw Ulam 和[[约翰·冯·诺伊曼]]的早期发现到 [[John Conway]] 的[[生命游戏]]和 [[Stephen Wolfram]] 的大量工作---- 清楚地表明,复杂性可以作为具有简单局部相互作用的扩展系统的一个[[涌现]]特征而产生。在相似的时间段内,[[Mandelbrot]]关于[[分形]]的大量工作表明,自然界的许多复杂性可以用某些无处不在的数学定律来描述,而在20世纪60年代和70年代对相变的广泛研究表明,诸如分形和[[幂律]]等尺度不变现象是如何出现不同相的[[临界点]]上的。 | |
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− | + | 自组织临界性最早由 Bak,Tang 和 Wiesenfeld 在1987年的论文中提出,这篇论文将这些因素清楚地联系在一起: 一个简单的细胞自动机被证明可以产生在自然复杂性中观察到的几个特征(分形几何、粉红噪声和幂律) ,这种方式可以与临界点现象联系起来。然而,关键的是,这篇论文强调,观察到的复杂性是以一种强有力的方式出现的,并不依赖于系统精细调整的细节:模型中的可变参数可以被广泛改变,而不会影响临界行为的涌现:因此,具有自组织临界性。因此,BTW 论文的关键结果是发现了一种机制,通过这种机制,从简单的局部相互作用中产生的复杂性可能是自发的---- 因此是合理的自然复杂性的来源---- 而不是只有在控制参数调整到精确的临界值的人工情况下才可能出现的东西。这项研究的发表引起了理论家和实验家的极大兴趣,产生了一些在科学文献中被引用最多的论文。 | |
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− | + | 由于 BTW 将他们的模型比喻为一个“沙堆” ,在沙堆上缓慢地喷洒新的沙粒以引起“雪崩” ,所以最初的实验工作主要集中在研究颗粒物质中的真实雪崩,其中最著名和最广泛的研究可能是奥斯陆地震实验。其他实验还包括在磁畴图案、超导体中的巴克豪森效应 Barkhausen effect和涡旋 vortices上进行的实验。 | |
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+ | 早期的理论工作包括开发各种不同于 BTW 模型的 soc 生成动力学,试图解析证明模型的性质(包括计算临界指数<ref name=Tang1988a>{{cite journal | author = Chao Tang and Per Bak | year = 1988 | title = Critical exponents and scaling relations for self-organized critical phenomena | journal = Physical Review Letters | volume = 60 | issue = 23 | ||
+ | | pages = 2347–2350 | doi = 10.1103/PhysRevLett.60.2347| bibcode= 1988PhRvL..60.2347T | pmid=10038328}} | ||
+ | </ref><ref name=Tang1988b>{{cite journal | author = Chao Tang and Per Bak | year = 1988 | title = Mean field theory of self-organized critical phenomena | journal = Journal of Statistical Physics | volume = 51 | issue = 5–6 | pages = 797–802 | doi = 10.1007/BF01014884| bibcode= 1988JSP....51..797T| url = https://zenodo.org/record/1232502 | type = Submitted manuscript }} | ||
+ | </ref>) ,以及检验发生SOC的必要条件。后一项研究的一个重要问题是,在局部动态交换模型时是否需要能量守恒: 一般的答案是否定的,但有一些保留意见,因为一些交换动力学(如 BTW 的动态)确实需要局部至少平均的能量守恒。从长远来看,有待解决的关键理论问题包括SOC行为可能的普适性类的计算,以及是否有可能推导出一个一般规则来确定一个随机算法是否显示SOC。 | ||
− | + | 除了这些大部分基于实验室的方法,许多其他的研究都集中在大规模的自然或社会系统上,这些系统已经知道(或怀疑)表现出尺度不变的行为。虽然这些方法并不总是受到研究对象专家的欢迎(至少最初是这样) ,但 '''<font color="#ff8000"> SOC</font>''' 已经成为解释一些自然现象的强有力的候选者,包括: 地震(早在SOC被发现之前,地震就被认为是尺度不变行为的来源,例如描述地震大小统计分布的古腾堡-里克特定律,以及描述余震频率的描述余震的 Omori 定律<ref name=TurcotteSmalleySolla85> | |
+ | {{cite journal|author1=Turcotte, D. L. |author2=Smalley, R. F., Jr. |author3=Solla, S. A. | year = 1985| title = Collapse of loaded fractal trees| journal = Nature | doi= 10.1038/313671a0| volume = 313| issue = 6004| pages = 671–672|bibcode = 1985Natur.313..671T }}</ref><ref name=SmalleyTurcotteSolla85 />);太阳耀斑; 经济系统的波动,比如金融市场(经济物理学中经常提到 SOC) ; 景观形成; 森林火灾; 滑坡; 流行病; 大脑皮层的神经雪崩;<ref name="Beggs2003" /><ref name=Poil2012>{{cite journal | pmid = 22815496 |date=Jul 2012 |author1=Poil, SS |author2=Hardstone, R |author3=Mansvelder, HD |author4=Linkenkaer-Hansen, K | title = Critical-state dynamics of avalanches and oscillations jointly emerge from balanced excitation/inhibition in neuronal networks | volume = 32 | issue = 29 | pages = 9817–23 | ||
+ | | doi = 10.1523/JNEUROSCI.5990-11.2012 | journal = Journal of Neuroscience | pmc=3553543}}</ref>电生理信号振幅的1 / f 噪声,<ref name=LinkenkaerHansen2001 />以及生物进化(其中 SOC 已被调用,例如,作为背后的动力机制的理论“间断平衡”由 Niles Eldredge 和史蒂芬·古尔德提出)。对SOC的这些”应用”研究既包括建模(开发新模型或使现有模型适应特定自然系统的具体情况) ,也包括广泛的数据分析,以确定是否存在和 / 或具有自然幂率的特点。 | ||
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− | + | 此外,SOC 已经应用于计算算法。最近,人们发现来自 SOC 过程的雪崩,如 BTW 模型,在图的最优解的随机搜索中形成有效的模式。 <ref name=Hoffmann2018>{{cite journal| author = H. Hoffmann and D. W. Payton| year = 2018| title = Optimization by Self-Organized Criticality| journal = Scientific Reports| volume = 8| issue = 1| pages = 2358| doi=10.1038/s41598-018-20275-7 | |
− | + | | pmid = 29402956| pmc = 5799203| bibcode = 2018NatSR...8.2358H}}</ref> 图着色就是这种最佳化问题的一个例子。'''<font color="#ff8000"> SOC</font>''' 过程显然有助于避免优化陷入局部最优,而无需使用任何以前的极值优化工作所建议的退火方案。 | |
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− | {{cite journal | ||
− | | author = | ||
− | | year = 2018 | ||
− | | title = Optimization by Self-Organized Criticality | ||
− | | journal = | ||
− | | volume = 8 | ||
− | | issue = 1 | ||
− | | pages = 2358 | ||
− | | doi=10.1038/s41598-018-20275-7 | ||
− | | pmid = 29402956 | ||
− | | pmc = 5799203 | ||
− | | bibcode = 2018NatSR...8.2358H | ||
− | }}</ref> | ||
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− | 图着色就是这种最佳化问题的一个例子。'''<font color="#ff8000"> SOC</font>''' 过程显然有助于避免优化陷入局部最优,而无需使用任何以前的极值优化工作所建议的退火方案。 | ||
The recent excitement generated by [[scale-free networks]] has raised some interesting new questions for SOC-related research: a number of different SOC models have been shown to generate such networks as an emergent phenomenon, as opposed to the simpler models proposed by network researchers where the network tends to be assumed to exist independently of any physical space or dynamics. While many single phenomena have been shown to exhibit scale-free properties over narrow ranges, a phenomenon offering by far a larger amount of data is solvent-accessible surface areas in globular proteins.<ref name=Moret2007> | The recent excitement generated by [[scale-free networks]] has raised some interesting new questions for SOC-related research: a number of different SOC models have been shown to generate such networks as an emergent phenomenon, as opposed to the simpler models proposed by network researchers where the network tends to be assumed to exist independently of any physical space or dynamics. While many single phenomena have been shown to exhibit scale-free properties over narrow ranges, a phenomenon offering by far a larger amount of data is solvent-accessible surface areas in globular proteins.<ref name=Moret2007> | ||
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− | == | + | == 延伸阅读 == |
* {{cite journal | * {{cite journal | ||
| author = Adami, C. | | author = Adami, C. | ||
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}} | }} | ||
*[http://xstructure.inr.ac.ru/x-bin/theme2.py?arxiv=cond-mat&level=1&index1=20771 Self-organized criticality on arxiv.org] | *[http://xstructure.inr.ac.ru/x-bin/theme2.py?arxiv=cond-mat&level=1&index1=20771 Self-organized criticality on arxiv.org] | ||
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[[Category:Critical phenomena]] | [[Category:Critical phenomena]] |
2021年9月13日 (一) 14:29的版本
此词条暂由水流心不竞初译,Inch审校,带来阅读不便,请见谅。
在物理学中,自组织临界性 Self-organized criticality (SOC)是动力系统的一种特性,动力系统有一个临界点作为吸引子 Attractor。它们在相变临界点的宏观行为因此显示了空间或时间尺度不变特性,但不需要把控制参数调整到一个精确的值,因为系统有效地自我调整趋向于临界状态。
这个概念是由 Per Bak,Chao Tang 和 Kurt Wiesenfeld (简称“BTW”)在1987年的《物理评论快报 Physical Review Letters》上的论文中提出的,[1] 其被认为是复杂性在自然界出现的机制之一。[2]它的概念已经被应用于各个领域,比如地球物理学,[3] 物理宇宙学,进化生物学和生态学,生物启发计算和优化(数学) ,经济学,量子引力,社会学,太阳物理学,等离子物理学,神经生物学等。[4][5][6]SOC通常在多自由度、强非线性动力学的缓慢驱动非平衡系统中被观察到。自从 BTW 的原始论文以来,已经确定了许多单独的例子,但是到目前为止还没有一组已知的一般特征来保证一个系统将显示 SOC。
概览
自组织临界性是20世纪下半叶统计物理学及相关领域的众多重要发现之一,这些发现尤其与研究自然界的复杂性有关。例如,元胞自动机的研究---- 从 Stanislaw Ulam 和约翰·冯·诺伊曼的早期发现到 John Conway 的生命游戏和 Stephen Wolfram 的大量工作---- 清楚地表明,复杂性可以作为具有简单局部相互作用的扩展系统的一个涌现特征而产生。在相似的时间段内,Mandelbrot关于分形的大量工作表明,自然界的许多复杂性可以用某些无处不在的数学定律来描述,而在20世纪60年代和70年代对相变的广泛研究表明,诸如分形和幂律等尺度不变现象是如何出现不同相的临界点上的。
自组织临界性最早由 Bak,Tang 和 Wiesenfeld 在1987年的论文中提出,这篇论文将这些因素清楚地联系在一起: 一个简单的细胞自动机被证明可以产生在自然复杂性中观察到的几个特征(分形几何、粉红噪声和幂律) ,这种方式可以与临界点现象联系起来。然而,关键的是,这篇论文强调,观察到的复杂性是以一种强有力的方式出现的,并不依赖于系统精细调整的细节:模型中的可变参数可以被广泛改变,而不会影响临界行为的涌现:因此,具有自组织临界性。因此,BTW 论文的关键结果是发现了一种机制,通过这种机制,从简单的局部相互作用中产生的复杂性可能是自发的---- 因此是合理的自然复杂性的来源---- 而不是只有在控制参数调整到精确的临界值的人工情况下才可能出现的东西。这项研究的发表引起了理论家和实验家的极大兴趣,产生了一些在科学文献中被引用最多的论文。
由于 BTW 将他们的模型比喻为一个“沙堆” ,在沙堆上缓慢地喷洒新的沙粒以引起“雪崩” ,所以最初的实验工作主要集中在研究颗粒物质中的真实雪崩,其中最著名和最广泛的研究可能是奥斯陆地震实验。其他实验还包括在磁畴图案、超导体中的巴克豪森效应 Barkhausen effect和涡旋 vortices上进行的实验。
早期的理论工作包括开发各种不同于 BTW 模型的 soc 生成动力学,试图解析证明模型的性质(包括计算临界指数[7][8]) ,以及检验发生SOC的必要条件。后一项研究的一个重要问题是,在局部动态交换模型时是否需要能量守恒: 一般的答案是否定的,但有一些保留意见,因为一些交换动力学(如 BTW 的动态)确实需要局部至少平均的能量守恒。从长远来看,有待解决的关键理论问题包括SOC行为可能的普适性类的计算,以及是否有可能推导出一个一般规则来确定一个随机算法是否显示SOC。
除了这些大部分基于实验室的方法,许多其他的研究都集中在大规模的自然或社会系统上,这些系统已经知道(或怀疑)表现出尺度不变的行为。虽然这些方法并不总是受到研究对象专家的欢迎(至少最初是这样) ,但 SOC 已经成为解释一些自然现象的强有力的候选者,包括: 地震(早在SOC被发现之前,地震就被认为是尺度不变行为的来源,例如描述地震大小统计分布的古腾堡-里克特定律,以及描述余震频率的描述余震的 Omori 定律[9][3]);太阳耀斑; 经济系统的波动,比如金融市场(经济物理学中经常提到 SOC) ; 景观形成; 森林火灾; 滑坡; 流行病; 大脑皮层的神经雪崩;[5][10]电生理信号振幅的1 / f 噪声,[4]以及生物进化(其中 SOC 已被调用,例如,作为背后的动力机制的理论“间断平衡”由 Niles Eldredge 和史蒂芬·古尔德提出)。对SOC的这些”应用”研究既包括建模(开发新模型或使现有模型适应特定自然系统的具体情况) ,也包括广泛的数据分析,以确定是否存在和 / 或具有自然幂率的特点。
此外,SOC 已经应用于计算算法。最近,人们发现来自 SOC 过程的雪崩,如 BTW 模型,在图的最优解的随机搜索中形成有效的模式。 [11] 图着色就是这种最佳化问题的一个例子。 SOC 过程显然有助于避免优化陷入局部最优,而无需使用任何以前的极值优化工作所建议的退火方案。
The recent excitement generated by scale-free networks has raised some interesting new questions for SOC-related research: a number of different SOC models have been shown to generate such networks as an emergent phenomenon, as opposed to the simpler models proposed by network researchers where the network tends to be assumed to exist independently of any physical space or dynamics. While many single phenomena have been shown to exhibit scale-free properties over narrow ranges, a phenomenon offering by far a larger amount of data is solvent-accessible surface areas in globular proteins.[12] These studies quantify the differential geometry of proteins, and resolve many evolutionary puzzles regarding the biological emergence of complexity.[13]
无标度网络Scale-free networks最近的热潮为 SOC相关研究提出了一些有趣的新问题: 许多不同的 SOC模型已经被证明是作为一种涌现现象产生这样的网络,而不是网络研究人员提出的更简单的模型,其中网络往往被假定独立于任何物理空间或动力学存在。虽然许多单一现象已被证明在狭窄的范围内表现出无标度特性,但是到目前为止提供了大量数据的现象是球状蛋白质中溶剂可及的表面区域。这些研究量化了蛋白质的微分几何,并解决了许多关于生物复杂性出现的进化之谜
Despite the considerable interest and research output generated from the SOC hypothesis, there remains no general agreement with regards to its mechanisms in abstract mathematical form. Bak Tang and Wiesenfeld based their hypothesis on the behavior of their sandpile model.[1] However, it has been argued that this model would actually generate 1/f2 noise rather than 1/f noise.[15] This claim was based on untested scaling assumptions, and a more rigorous analysis showed that sandpile models generally produce 1/fa spectra, with a<2.[16] Other simulation models were proposed later that could produce true 1/f noise,[17] and experimental sandpile models were observed to yield 1/f noise.[18] In addition to the nonconservative theoretical model mentioned above, other theoretical models for SOC have been based upon information theory,[19] mean field theory,[20] the convergence of random variables,[21] and cluster formation.[22] A continuous model of self-organised criticality is proposed by using tropical geometry.[23]
Despite the considerable interest and research output generated from the SOC hypothesis, there remains no general agreement with regards to its mechanisms in abstract mathematical form. Bak Tang and Wiesenfeld based their hypothesis on the behavior of their sandpile model.[1] However, it has been argued that this model would actually generate 1/f2 noise rather than 1/f noise.[14] This claim was based on untested scaling assumptions, and a more rigorous analysis showed that sandpile models generally produce 1/fa spectra, with a<2.[15] Other simulation models were proposed later that could produce true 1/f noise,[16] and experimental sandpile models were observed to yield 1/f noise.[17] In addition to the nonconservative theoretical model mentioned above, other theoretical models for SOC have been based upon information theory,[18] mean field theory,[19] the convergence of random variables,[20] and cluster formation.[21] A continuous model of self-organised criticality is proposed by using tropical geometry.[22]
尽管 SOC 假说引起了相当大的兴趣和研究成果,但是关于其抽象数学形式的机制仍然没有普遍的一致性。Bak Tang 和 Wiesenfeld 基于他们的沙堆模型的行为建立了他们的假设。然而,有人认为,这种模型实际上会产生1 / f sup 2 / sup 噪声而不是1 / f 噪声。这种说法是基于未经测试的比例假设,更严格的分析表明在a>2沙堆模型一般产生1 / f sup a / sup 光谱。 其他的仿真模型能产生真正的1/f的噪声也被提出,并且实验上的实验模型能被观测到产生1/f噪音。除了上面提到的非保守理论模型之外,其他关于 SOC 的理论模型都是基于信息论, 平均场论,随机变量的收敛和剧集信息一个 自组织临界Self-organised criticality的连续模型是通过使用热带几何来提出的。
Examples of self-organized critical dynamics自组织临界动力学的例子
In chronological order of development:
In chronological order of development:
按发展时间顺序排列:
See also 参见
- 复杂系统s
- Detrended fluctuation analysis, a method to detect power-law scaling in time series.
- Detrended涨落分析,一种检测中幂律标度的方法
- Dual-phase evolution, another process that contributes to self-organization in complex systems.
- 双相演化,另一个有助于自我组织的过程
- 分形s;
- Ilya Prigogine, a systems scientist who helped formalize dissipative system behavior in general terms.
- 伊利亚·普里高津,一位帮助将耗散系统形式化的系统科学家
- 幂律s
References参考资料
- ↑ 1.0 1.1 Per Bak, Chao Tang and Kurt Wiesenfeld (1987). "Self-organized criticality: an explanation of 1/f noise". Physical Review Letters. 59 (4): 381–384. Bibcode:1987PhRvL..59..381B. doi:10.1103/PhysRevLett.59.381. PMID 10035754. Papercore summary: http://papercore.org/Bak1987.
- ↑ Per Bak, and Maya Paczuski (1995). "Complexity, contingency, and criticality". Proc Natl Acad Sci U S A. 92 (15): 6689–6696. Bibcode:1995PNAS...92.6689B. doi:10.1073/pnas.92.15.6689. PMC 41396. PMID 11607561.
- ↑ 3.0 3.1 3.2 3.3 Smalley, R. F., Jr.; Turcotte, D. L.; Solla, S. A. (1985). "A renormalization group approach to the stick-slip behavior of faults". Journal of Geophysical Research. 90 (B2): 1894. Bibcode:1985JGR....90.1894S. doi:10.1029/JB090iB02p01894.
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: CS1 maint: multiple names: authors list (link) - ↑ 4.0 4.1 K. Linkenkaer-Hansen; V. V. Nikouline; J. M. Palva & R. J. Ilmoniemi. (2001). "Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations". J. Neurosci. 21 (4): 1370–1377. doi:10.1523/JNEUROSCI.21-04-01370.2001. PMC 6762238. PMID 11160408.
- ↑ 5.0 5.1 J. M. Beggs & D. Plenz (2006). "Neuronal Avalanches in Neocortical Circuits". J. Neurosci. 23 (35): 11167–77. doi:10.1523/JNEUROSCI.23-35-11167.2003. PMC 6741045. PMID 14657176.
- ↑ Chialvo, D. R. (2004). "Critical brain networks". Physica A. 340 (4): 756–765. arXiv:cond-mat/0402538. Bibcode:2004PhyA..340..756R. doi:10.1016/j.physa.2004.05.064.
- ↑ Chao Tang and Per Bak (1988). "Critical exponents and scaling relations for self-organized critical phenomena". Physical Review Letters. 60 (23): 2347–2350. Bibcode:1988PhRvL..60.2347T. doi:10.1103/PhysRevLett.60.2347. PMID 10038328.
- ↑ Chao Tang and Per Bak (1988). "Mean field theory of self-organized critical phenomena". Journal of Statistical Physics (Submitted manuscript). 51 (5–6): 797–802. Bibcode:1988JSP....51..797T. doi:10.1007/BF01014884.
- ↑ 9.0 9.1 9.2
Turcotte, D. L.; Smalley, R. F., Jr.; Solla, S. A. (1985). "Collapse of loaded fractal trees". Nature. 313 (6004): 671–672. Bibcode:1985Natur.313..671T. doi:10.1038/313671a0.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) - ↑ Poil, SS; Hardstone, R; Mansvelder, HD; Linkenkaer-Hansen, K (Jul 2012). "Critical-state dynamics of avalanches and oscillations jointly emerge from balanced excitation/inhibition in neuronal networks". Journal of Neuroscience. 32 (29): 9817–23. doi:10.1523/JNEUROSCI.5990-11.2012. PMC 3553543. PMID 22815496.
- ↑ H. Hoffmann and D. W. Payton (2018). "Optimization by Self-Organized Criticality". Scientific Reports. 8 (1): 2358. Bibcode:2018NatSR...8.2358H. doi:10.1038/s41598-018-20275-7. PMC 5799203. PMID 29402956.
- ↑
Moret, M. A. and Zebende, G. (2007). "Amino acid hydrophobicity and accessible surface area". Phys. Rev. E. 75 (1): 011920. Bibcode:2007PhRvE..75a1920M. doi:10.1103/PhysRevE.75.011920. PMID 17358197.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) - ↑ Phillips, J. C. (2014). "Fractals and self-organized criticality in proteins". Physica A. 415: 440–448. Bibcode:2014PhyA..415..440P. doi:10.1016/j.physa.2014.08.034.
- ↑
Jensen, H. J., Christensen, K. and Fogedby, H. C. (1989). "1/f noise, distribution of lifetimes, and a pile of sand". Phys. Rev. B. 40 (10): 7425–7427. Bibcode:1989PhRvB..40.7425J. doi:10.1103/physrevb.40.7425. PMID 9991162.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) - ↑ Laurson, Lasse; Alava, Mikko J.; Zapperi, Stefano (15 September 2005). "Letter: Power spectra of self-organized critical sand piles". Journal of Statistical Mechanics: Theory and Experiment. 0511. L001.
- ↑
Maslov, S., Tang, C. and Zhang, Y. - C. (1999). "1/f noise in Bak-Tang-Wiesenfeld models on narrow stripes". Phys. Rev. Lett. 83 (12): 2449–2452. arXiv:cond-mat/9902074. Bibcode:1999PhRvL..83.2449M. doi:10.1103/physrevlett.83.2449.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) - ↑
Frette, V., Christinasen, K., Malthe-Sørenssen, A., Feder, J, Jøssang, T and Meaken, P (1996). "Avalanche dynamics in a pile of rice". Nature. 379 (6560): 49–52. Bibcode:1996Natur.379...49F. doi:10.1038/379049a0.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) - ↑ Dewar, R. (2003). "Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states". J. Phys. A: Math. Gen. 36 (3): 631–641. arXiv:cond-mat/0005382. Bibcode:2003JPhA...36..631D. doi:10.1088/0305-4470/36/3/303.
- ↑
Vespignani, A., and Zapperi, S. (1998). "How self-organized criticality works: a unified mean-field picture". Phys. Rev. E. 57 (6): 6345–6362. arXiv:cond-mat/9709192. Bibcode:1998PhRvE..57.6345V. doi:10.1103/physreve.57.6345. hdl:2047/d20002173.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) - ↑ Kendal, WS (2015). "Self-organized criticality attributed to a central limit-like convergence effect". Physica A. 421: 141–150. Bibcode:2015PhyA..421..141K. doi:10.1016/j.physa.2014.11.035.
- ↑ Hoffmann, H. (2018). "Impact of Network Topology on Self-Organized Criticality". Phys. Rev. E. 97 (2): 022313. Bibcode:2018PhRvE..97b2313H. doi:10.1103/PhysRevE.97.022313. PMID 29548239.
- ↑ Kalinin, N.; Guzmán-Sáenz, A.; Prieto, Y.; Shkolnikov, M.; Kalinina, V.; Lupercio, E. (2018-08-15). "Self-organized criticality and pattern emergence through the lens of tropical geometry". Proceedings of the National Academy of Sciences (in English). 115 (35): E8135–E8142. arXiv:1806.09153. doi:10.1073/pnas.1805847115. ISSN 0027-8424. PMC 6126730. PMID 30111541.
延伸阅读
- Adami, C. (1995). "Self-organized criticality in living systems". Physics Letters A. 203 (1): 29–32. arXiv:adap-org/9401001. Bibcode:1995PhLA..203...29A. CiteSeerX 10.1.1.456.9543. doi:10.1016/0375-9601(95)00372-A.
- Bak, P. (1996). How Nature Works: The Science of Self-Organized Criticality. New York: Copernicus. ISBN 978-0-387-94791-4.
- Bak, P. and Paczuski, M. (1995). "Complexity, contingency, and criticality". Proceedings of the National Academy of Sciences of the USA. 92 (15): 6689–6696. Bibcode:1995PNAS...92.6689B. doi:10.1073/pnas.92.15.6689. PMC 41396. PMID 11607561.
{{cite journal}}
: CS1 maint: multiple names: authors list (link)
- Bak, P. and Sneppen, K. (1993). "Punctuated equilibrium and criticality in a simple model of evolution". Physical Review Letters. 71 (24): 4083–4086. Bibcode:1993PhRvL..71.4083B. doi:10.1103/PhysRevLett.71.4083. PMID 10055149.
{{cite journal}}
: CS1 maint: multiple names: authors list (link)
- Bak, P., Tang, C. and Wiesenfeld, K. (1987). "Self-organized criticality: an explanation of [math]\displaystyle{ 1/f }[/math] noise". Physical Review Letters. 59 (4): 381–384. Bibcode:1987PhRvL..59..381B. doi:10.1103/PhysRevLett.59.381. PMID 10035754.
{{cite journal}}
: CS1 maint: multiple names: authors list (link)
- Bak, P., Tang, C. and Wiesenfeld, K. (1988). "Self-organized criticality". Physical Review A. 38 (1): 364–374. Bibcode:1988PhRvA..38..364B. doi:10.1103/PhysRevA.38.364. PMID 9900174.
{{cite journal}}
: CS1 maint: multiple names: authors list (link) Papercore summary.
- Buchanan, M. (2000). Ubiquity. London: Weidenfeld & Nicolson. ISBN 978-0-7538-1297-6.
- Jensen, H. J. (1998). Self-Organized Criticality. Cambridge: Cambridge University Press. ISBN 978-0-521-48371-1.
- Katz, J. I. (1986). "A model of propagating brittle failure in heterogeneous media". Journal of Geophysical Research. 91 (B10): 10412. Bibcode:1986JGR....9110412K. doi:10.1029/JB091iB10p10412.
- Kron, T./Grund, T. (2009). "Society as a Selforganized Critical System". Cybernetics and Human Knowing. 16: 65–82.
{{cite journal}}
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- Paczuski, M. (2005). Networks as renormalized models for emergent behavior in physical systems. The Science and Culture Series – Physics. pp. 363–374. arXiv:physics/0502028. Bibcode 2005cmn..conf..363P. doi:10.1142/9789812701558_0042. ISBN 978-981-256-525-9.
- Turcotte, D. L. (1997). Fractals and Chaos in Geology and Geophysics. Cambridge: Cambridge University Press. ISBN 978-0-521-56733-6.
- Turcotte, D. L. (1999). "Self-organized criticality". Reports on Progress in Physics. 62 (10): 1377–1429. Bibcode:1999RPPh...62.1377T. doi:10.1088/0034-4885/62/10/201.
- Md. Nurujjaman/A. N. Sekar Iyengar (2007). "Realization of {SOC} behavior in a dc glow discharge plasma". Physics Letters A. 360 (6): 717–721. arXiv:physics/0611069. Bibcode:2007PhLA..360..717N. doi:10.1016/j.physleta.2006.09.005.
- Self-organized criticality on arxiv.org