三个硬球碰撞历史中二进制字符串的压缩和信息熵

IF 1.1 Q3 PHYSICS, MULTIDISCIPLINARY Journal of Physics Communications Pub Date : 2023-02-14 DOI:10.1088/2399-6528/acd2a3
Matej Vedak, G. Ackland
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引用次数: 0

摘要

我们研究了如何测量和定义一个简单混沌系统的熵,即一个环上的三个硬球。提出了一种新的方法,它不假设遍历假设。它包括将粒子的碰撞历史转换为二进制数字序列。然后,我们研究了三种方法,与随机数生成器创建的字符串相比,这些方法应该证明这些碰撞生成的字符串的非随机性:香农熵、顽固随机性测试和压缩百分比。我们证明了香农信息熵不能区分随机字符串和确定性字符串。Diehard测试表现更好,但对于某些质量比,碰撞产生的字符串被错误地识别为具有高置信度的随机字符串。zlib和bz2压缩算法在检测非随机性和低信息含量方面非常有效,在无限字符串的限制下,压缩效率往往达到100%。因此,对于这个混沌系统,“压缩算法熵”是非扩展的,这与通过假设遍历性从相空间积分确定的扩展熵形成了鲜明对比。
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Compression and information entropy of binary strings from the collision history of three hard balls
We investigate how to measure and define the entropy of a simple chaotic system, three hard spheres on a ring. A novel approach is presented, which does not assume the ergodic hypothesis. It consists of transforming the particles’ collision history into a sequence of binary digits. We then investigate three approaches which should demonstrate the non-randomness of these collision-generated strings compared with random number generator created strings: Shannon entropy, diehard randomness tests and compression percentage. We show that the Shannon information entropy is unable to distinguish random from deterministic strings. The Diehard test performs better, but for certain mass-ratios the collision-generated strings are misidentified as random with high confidence. The zlib and bz2 compression algorithms are efficient at detecting non-randomness and low information content, with compression efficiencies that tend to 100% in the limit of infinite strings. Thus ‘compression algorithm entropy’ is non-extensive for this chaotic system, in marked contrast to the extensive entropy determined from phase-space integrals by assuming ergodicity.
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来源期刊
Journal of Physics Communications
Journal of Physics Communications PHYSICS, MULTIDISCIPLINARY-
CiteScore
2.60
自引率
0.00%
发文量
114
审稿时长
10 weeks
期刊最新文献
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