A network perspective on J.S Bach’s 6 violin sonatas and partitas, BWV 1001 - 1006

IF 2.8 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica A: Statistical Mechanics and its Applications Pub Date : 2024-10-10 DOI:10.1016/j.physa.2024.130124
Dima Mrad , Sara Najem , Pablo Padilla , Francis Knights
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Abstract

Complex networks and statistical physics have been proposed as powerful frameworks and tools in the analysis of the properties of complex systems and in particular musical pieces. They can reveal variations in musical features such as harmony, melody, rhythm as well as the composer’s style. The empirical study of a wide range of digitized scores of Western classical music and their corresponding networks brought to light quantitative evidence for changes in harmonic complexity. We complement the common topological analysis of these networks with musicological or music-theoretical considerations. We illustrate this by studying J. S. Bach’s sonatas and partitas for solo violin by constructing duration-weighted transition matrices between notes, or melody networks, as well as harmony networks, which are transition matrices between the chords, or equivalently synchronously played notes. We further propose statistical physics measures that were first introduced in the study of socio-economic networks: the partition function and communicability and provide evidence for their significance. Our findings and observations include: the detection of three main communities centered around the tonic, the dominant, and submediant in most of the pieces; the association of the nodes with the highest betweenness centrality, the lowest clustering coefficient and highest in and out degrees respectively with the tonic and the dominant; the high similarity between pieces which share the same key or when the key of one is the dominant of the other; finally, the association of the highest partition function, the shortest average path length, and the highest communicability with the Fugues.

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从网络角度看巴赫的 6 首小提琴奏鸣曲和 Partitas,BWV 1001 - 1006
复杂网络和统计物理学被认为是分析复杂系统,特别是音乐作品属性的强大框架和工具。它们可以揭示和声、旋律、节奏以及作曲家风格等音乐特征的变化。通过对大量西方古典音乐数字化乐谱及其相应网络的实证研究,我们发现了和声复杂性变化的量化证据。我们从音乐学或音乐理论的角度对这些网络的常见拓扑分析进行了补充。我们通过研究巴赫(J. S. Bach)的小提琴独奏奏鸣曲和部分奏鸣曲,构建了音符之间的时长加权转换矩阵,即旋律网络,以及和声网络,即和弦之间的转换矩阵,或等同于同步演奏的音符之间的转换矩阵,来说明这一点。我们进一步提出了首次在社会经济网络研究中引入的统计物理测量方法:分区函数和可传播性,并为其重要性提供了证据。我们的发现和观察结果包括:在大多数乐曲中发现了以调性、主音和副主音为中心的三个主要群落;具有最高间度中心性、最低聚类系数和最高进出度的节点分别与调性和主音相关;具有相同调性的乐曲或其中一个调性是另一个调性的乐曲之间具有高度相似性;最后,具有最高分区函数、最短平均路径长度和最高可传播性的乐曲与赋格相关。
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来源期刊
CiteScore
7.20
自引率
9.10%
发文量
852
审稿时长
6.6 months
期刊介绍: Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.
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