Modeling language evolution using a spin glass approach
Hediye Yarahmadi1, Kwang Il Ryom1, Giuseppe Longobardi2
1SISSA, -Cognitive Neuroscience, Trieste 34136, Italy.
Physical Review. E
|April 18, 2026
Summary
Natural language evolution may be driven by disorder, not just efficiency. Syntactic changes, modeled as disordered parameter interactions, explain slow, diverse language shifts and historical linguistic patterns.
Area of Science:
- Linguistics
- Computational Linguistics
- Theoretical Computer Science
- Statistical Physics
Background:
- Traditional linguistic evolution models often prioritize efficiency, yet fail to explain why languages change slowly or diversify.
- Existing research primarily focuses on lexical data, potentially overlooking the critical role of syntax in language dynamics.
- The inherent complexity of natural language evolution necessitates exploring alternative drivers beyond pure optimization.
Purpose of the Study:
- To investigate the hypothesis that disorder, rather than efficiency, is a primary driver of natural language evolution.
- To develop a computational model explaining diachronic language change based on syntactic parameter interactions.
- To analyze the 'glassy' dynamics observed in language change and their relationship to syntactic structures.
Main Methods:
- Reduction of syntax to a set of binary syntactic parameters.
- Introduction of a computational model simulating diachronic language dynamics through disordered parameter interactions.
- Analysis of 'phase space' to identify regions exhibiting glassy dynamics, akin to spin glass behavior.
- Inclusion of a Hopfield-type memory term to explore its effect on syntactic configuration stability.
Main Results:
- Disordered interactions between syntactic parameters can drive language change, even with consistent external inputs.
- Binary syntactic vectors exhibit 'glassy' metastable states below a critical asymmetry threshold, mirroring spin glass dynamics.
- A Hopfield-type memory term can stabilize configurations but reduces the diversity of stable states.
- A defined linguistic distance metric reveals a phylogenetic signal in related languages despite syntactic divergence.
Conclusions:
- Disorder in syntactic parameter interactions offers a compelling explanation for the slow and diverse evolution of natural languages.
- The model successfully replicates observed 'glassy' dynamics and metastable states in language change.
- The findings suggest that syntactic structure plays a fundamental role in language evolution, with implications for historical linguistics and computational modeling.
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