IV. Ecosmomics: Independent Complex Network Systems, Computational Programs, Genetic Ecode Scripts

3. Iteracy: A Rosetta Ecosmos Textuality

Ga, Jianquao, et al. Cross-Language Differences in the Brain Network Subserving Intelligible Speech. Proceedings of the National Academy of Sciences. 112/2972, 2015. Through sophisticated experimentation not possible earlier, neuroscientists across China, with a University College London colleague, find a definitive difference between Western nontonal and Eastern tonal languages. While alphabet-based speech is referred mostly to the left hemisphere, an idiographic mode employs left side processing along with a right hemisphere prosodic, rhythmic input for a fuller comprehension.

How is language processed in the brain by native speakers of different languages? Is there one brain system for all languages or are different languages subserved by different brain systems? The first view emphasizes commonality, whereas the second emphasizes specificity. We investigated the cortical dynamics involved in processing two very diverse languages: a tonal language (Chinese) and a nontonal language (English). We used functional MRI and dynamic causal modeling analysis to compute and compare brain network models exhaustively with all possible connections among nodes of language regions in temporal and frontal cortex and found that the information flow from the posterior to anterior portions of the temporal cortex was commonly shared by Chinese and English speakers during speech comprehension, whereas the inferior frontal gyrus received neural signals from the left posterior portion of the temporal cortex in English speakers and from the bilateral anterior portion of the temporal cortex in Chinese speakers.

Our results revealed that, although speech processing is largely carried out in the common left hemisphere classical language areas (Broca’s and Wernicke’s) and anterior temporal cortex, speech comprehension across different language groups depends on how these brain regions interact with each other. Moreover, the right anterior temporal cortex, which is crucial for tone processing, is equally important as its left homolog, the left anterior temporal cortex, in modulating the cortical dynamics in tone language comprehension. The current study pinpoints the importance of the bilateral anterior temporal cortex in language comprehension that is downplayed or even ignored by popular contemporary models of speech comprehension. (Abstract)

Gallego, Angel and Roman Orus. The Physical Structure of Grammatical Correlations. arXiv:1708.01525. In this late 2010s scientific rehab of a truly whole cosmos, which must be one, a University of Barcelona linguist and a Johannes Gutenberg University, Mainz physicist find another way join human literature within natural phenomena. As a result, via technical flourishes, language systems gain a “legitimacy, universality and optimality,” which by turns implies an innate textual, cosmic narrative.

In this paper we consider some well-known facts in syntax from a physics perspective, which allows us to establish some remarkable equivalences. Specifically, we observe that the operation MERGE put forward by N. Chomsky in 1995 can be interpreted as a physical information coarse-graining. Thus, MERGE in linguistics entails information renormalization in physics, according to different time scales. We make this point mathematically formal in terms of language models, i.e., probability distributions over word sequences, widely used in natural language processing as well as other ambits. The probability vectors of meaningful sentences are naturally given by tensor networks (TN) that are mostly loop-free. Moreover, using tools from quantum information and entanglement theory, we use these quantum states to prove classical lower bounds on the perplexity of the probability distribution for a set of words in a sentence. Implications of these results are discussed in the ambits of theoretical and computational linguistics, artificial intelligence, programming languages, RNA and protein sequencing, quantum many-body systems, and beyond. (Abstract)

Gnanadesikan, Amalia. The Writing Revolution: Cuniform to the Internet. West Sussex, UK: Wiley Blackwell, 2009. A Holy Family University (Philadelphia) linguist surveys the many, variegated ways by which this genesis cosmos has tried to achieve its own textual description, which now might take on a salutary global dimension unto a momentary self-realization.

Gong, Tao, et al. Evolutionary Linguistics: Theory of Language in an Interdisciplinary Space. Language Sciences. 41/243, 2014. Gong, Hong Kong University, with Lan Shuai, Johns Hopkins University, and Bernard Comrie, MPI for Evolutionary Anthropology, affirm from this deep perspective a continuous tandem ascent of compositionality (component, word, sign) and their common regularity. These “universalities” are seen to reveal a “recapitulation” in kind between primate to human literacy and how a child learns to speak and read. To reflect, might it seem that life’s long course could be seen as a genesis universe’s way of trying articulate and discover itself, i.e. to decipher its own script?

This paper revisits the key questions in current thinking in evolutionary linguistics, reviews the alleged stages during language evolution, and evaluates the mainstream hypotheses on language emergence, namely innatism and emergentism. We summarize both the supporting and opposing arguments for these hypotheses and evaluate two scenarios respectively following these hypotheses. As we will show, many of these arguments require an interdisciplinary collaboration between linguistics and other disciplines such as cognitive sciences, psychology, neuroscience, genetics, animal behaviors, and computer simulation, which illustrates the interdisciplinary nature of evolutionary linguistics and highlights the opportunities for future engagement of our discipline. (Abstract)

Gong, Wen. A New Exploration into Chinese Characters: From Simplification to Deeper Understanding. arXiv:2502.19428. A City University of Macau scholar posts a unique synthesis across millennia of oriental wisdom, mathematics and geometry and our 2025 intelligent cybersphere frontiers. The achievement is a luminous preview of a Earthuman (East/west, South/north) spatial and temporal textual universality.

This paper presents a novel approach to Chinese characters through the lens of physics, networks, and natural systems. Computational analysis of over 6,000 characters served to identify 422 elemental logographs which exhibit properties of emergent complexity, self-organization, and adaptive resilience. By viewing Chinese characters as a living system, this research can reveal how human cognition organizes and transmits knowledge. This perspective, combined with AI approaches, promises to transform language education from knowledge gain to meaning discovery.

This paper represents a collaborative effort between the author, and a team of AI assistants including Claude 3.3 from Anthropic, Gemini 2 from Google and Qwen2.5-Max from Alibaba. The fusion of human knowledge and software development, physics, and Chinese language with AI capabilities enables the novel perspectives and methodologies presented in this work.

Natural Growth Patterns in Character Evolution Just as natural systems evolve from simple to complex through predictable patterns, Chinese characters follow a similar organic development. The Fibonacci sequence provides an elegant metaphor for how complexity emerges from simplicity in systematic ways. The accompanying images of Fibonacci patterns in nature - from sunflowers to nautilus shells and fern fronds to spiral galaxies - reveal this universal principle of growth and organization. (22)

Dedication This work is dedicated to the late Professor T.D. Lee whose efforts opened doors for many Chinese students to pursue studies in the United States as a bridge between Eastern and Western traditions. His vision and support have enabled countless scholars like myself to contribute to global discourse.

Grabska-Gradzinska, Iwona, et al. Complex Network Analysis of Literary and Scientific Texts. International Journal of Modern Physics C. Online May, 2012. In this journal of “Computational Physics and Physical Computation,” with coauthors Andrzej Kulig, Jaroslaw Kwapien (search), and Stanislaw Drozdz, Polish Academy of Sciences, Krakow, researchers continue to articulate the intrinsic dynamical nature of humankind’s textual script. Whatever the local dialect an underlying commonality seems to characterize, which one may note is just the same as used to describe a generative genome. The paper is available in full on arXiv.

We present results from our quantitative study of statistical and network properties of literary and scientific texts written in two languages: English and Polish. We show that Polish texts are described by the Zipf law with the scaling exponent smaller than the one for the English language. We also show that the scientific texts are typically characterized by the rank-frequency plots with relatively short range of power-law behavior as compared to the literary texts. We then transform the texts into their word-adjacency network representations and find another difference between the languages. For the majority of the literary texts in both languages, the corresponding networks revealed the scale-free structure, while this was not always the case for the scientific texts. However, all the network representations of texts were hierarchical. We do not observe any qualitative and quantitative difference between the languages. However, if we look at other network statistics like the clustering coefficient and the average shortest path length, the English texts occur to possess more clustered structure than do the Polish ones. This result was attributed to differences in grammar of both languages, which was also indicated in the Zipf plots. (Abstract)

Natural language is an evolving system whose present structure can doubtlessly be considered a product of long history of self-organization. Like for many other self organized systems known in Nature, the observables associated with language, being, for example, written texts or spoken messages, reveal quite sophisticated dynamics. Any language sample by no means is an amorphous mixture of symbols (letters, phonemes, morphemes, words, etc.) but rather a highly organized sequence in which particular symbols are ordered according to specific rules most of which are defined by the language grammar. Since the existence of grammar is an emergent phenomenon, language can be counted among the complex systems. The grammatical rules together with the information content impose on the language elements relations which can be most easily expressed in a form of network where, for instance, words are expressed by nodes and their relations by edges. (Introduction)

Gromov, Vasilii and Anastasia Migrina. A Language as a Self-Organized Critical System. Complexity. November, 2017. Oles Honchar National University, Ukraine mathematicians lay out a theoretical basis by which even this human cultural communicative quality appears to express nature’s universal middle way propensity.

A natural language (herewith texts generated by native speakers) is considered as a complex system. Namely, the authors hypothesize that such dynamic languages are self-organized critical systems and that their texts are “avalanches” flowing through word cooccurrence graphs. The respective statistical distributions of the number of words in English and Russian languages are calculated from a corpora of literary texts and sets of social media messages. The analysis found that the number of words in the texts obeys power-law distribution. (Abstract excerpt)

HaiTao, Liu. Statistical Properties of Chinese Semantic Networks. Chinese Science Bulletin. 54/16, 2009. As a companion to the next paper, the Communication University of China linguist finds evidence of nature’s generic complexity principles, just as everywhere else from galaxies to genomes, in our written and spoken languages.

Almost all language networks in word and syntactic levels are small-world and scale-free. This raises the questions of whether a language network in deeper semantic or cognitive level also has the similar properties. To answer the question, we built up a Chinese semantic network based on a treebank with semantic role (argument structure) annotation and investigated its global statistical properties. The results show that although semantic network is also small-world and scale-free, it is different from syntactic network in hierarchical structure and K-Nearest-Neighbor correlation. (Abstract)

HaiTao, Liu and WenWen Li. Language Clusters Based on Linguistic Complex Networks. Chinese Science Bulletin. 55/30, 2010. As if a 21st century synthesis of the ancient polyglot Tower of Babel, Zhejiang University and Communication University of China system researchers proceed to elucidate mathematical lineaments and affinities across Greek, Latin, Japanese, Chinese, Arabic to English, Hungarian, Portuguese, and Romanian languages.

To investigate the feasibility of using complex networks in the study of linguistic typology, this paper builds and explores 15 linguistic complex networks based on the dependency syntactic treebanks of 15 languages. The results show that it is possible to classify human languages by means of the following main parameters of complex networks: (a) average degree of the node, (b) cluster coefficients, (c) average path length, (d) network centralization, (e) diameter, (f) power exponent of degree distribution, and (g) the determination coefficient of power law distributions. (Abstract)

A language system is a network with a complex structure. Scholars have conducted many studies on language and complex networks. There are several kinds of human languages and various principles for constructing language networks. Research shows that most of the language networks within different languages and diverse construction principles have characteristics that are small-world and scale-free. This research had been valuable for understanding the universality of language networks and the commonness of language systems, human society, and other natural systems. (3455)

Hartnett, Kevin. A Rosetta Stone for Mathematics. Quanta. May 6, 2024. A science writer recounts the work of the French mathematician Andre Weil (1906-1998) with regard to a letter he wrote in 1940 to his sister Simone Weil, a philosopher in London. As the quotes say, he drew upon the exemplary Rosetta stone as a basis for how various mathematical methods could have a deeper affinity with each other. The article goes on to add further instances such as the 1970 Langlands Program (See What Is the Langlands Program? by Alex Kontorovich in Quanta for June 1, 2022) and other esoteric modes all the way to 2020. As a presentation slide of mine (home page) entitled A Rosetta Cosmos sought to convey, a vital insight might be that every aspect of a human uniVerse can mirror and be translated into each other.

Following the example of the famous engraving by that same name — a trilingual text that made ancient Egyptian writing legible to Western readers through translation into Ancient Greek — Weil’s Rosetta stone linked three fields of mathematics: number theory, geometry, and, in the middle, the study of finite fields. Other mathematicians had proposed ideas in this direction, but Weil was the first to spell out an exact vision. His letter presaged the Langlands program, a major initiative in contemporary mathematical research.

Hernandez-Fernandez, Antoni and Ramon Ferrer-i-Cancho. The Infochemical Core. Journal of Quantitative Linguistics. 23/2, 2016. The paper is also posted at arXiv:1610.05654. Universitat Politècnica de Catalunya, Barcelona, researchers achieve a novel perception of how natural systems far from language can be seen to display a linguistic, informational essence. For example, analogous correlations are noted between chemical communications or signals such as pheronomes and kairomones, and human writings. A deep, pervasive “language of life” can thus be alluded to.

Vocalizations and less often gestures have been the object of linguistic research over decades. However, the development of a general theory of communication with human language as a particular case requires a clear understanding of the organization of communication through other means. Infochemicals are chemical compounds that carry information and are employed by small organisms that cannot emit acoustic signals of optimal frequency to achieve successful communication. Here the distribution of infochemicals across species is investigated when they are ranked by their degree or the number of species with which it is associated. The quality of the fit of different functions to the dependency between degree and rank is evaluated with a penalty for the number of parameters of the function. Surprisingly, a double Zipf distribution with two regimes with a different exponent each is the model yielding the best fit although it is the function with the largest number of parameters. This suggests that the world wide repertoire of infochemicals contains a chemical nucleus shared by many species and reminiscent of the core vocabularies found for human language in dictionaries or large corpora. (Abstract)

Heunen, Chris, et al, eds. Quantum Physics and Linguistics: A Compositional, Diagrammatic Discourse. Oxford: Oxford University Press, 2013. An initial collection, broadly based at Oxford University, conveys an inherent affinity by way of mathematic and geometric finesses between these universe and human realms. It opens with An Alternative Gospel of Structure: Order, Composition, Processes by Bob Coecke (search). The grand implication would be a phenomenal nature as a truly textual composition, made and meant for we literate peoples to read, comprehend, avail, and continue. For a 2018 update see Uniqueness of Composition in Quantum Theory and Linguistics by Coecke, et al at arXiv:1803.00708.

New scientific paradigms typically consist of an expansion of the conceptual language with which we describe the world. Over the past decade, theoretical physics and quantum information theory have turned to category theory to model and reason about quantum protocols. This new use of categorical and algebraic tools allows a more conceptual and insightful expression of elementary events. Recent work in natural language semantics has begun to use these categorical methods to relate grammatical analysis and semantic representations in a unified framework for analysing language meaning, and learning meaning from a corpus. A growing body of literature on the use of categorical methods in quantum information theory and computational linguistics shows both the need and opportunity for new research on the relation between these categorical methods and the abstract notion of information flow.

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