Merge on workspaces as Hopf algebra Markov chain
- URL: http://arxiv.org/abs/2512.18861v1
- Date: Sun, 21 Dec 2025 19:26:41 GMT
- Title: Merge on workspaces as Hopf algebra Markov chain
- Authors: Matilde Marcolli, David Skigin,
- Abstract summary: We study the dynamical properties of a Hopf algebra Markov chain with state space binary rooted forests with labelled leaves.<n>This Markovian dynamical system describes the core computational process of structure formation and transformation in syntax via the Merge operation.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We study the dynamical properties of a Hopf algebra Markov chain with state space the binary rooted forests with labelled leaves. This Markovian dynamical system describes the core computational process of structure formation and transformation in syntax via the Merge operation, according to Chomsky's Minimalism model of generative linguistics. The dynamics decomposes into an ergodic dynamical system with uniform stationary distribution, given by the action of Internal Merge, while the contributions of External Merge and (a minimal form of) Sideward Merge reduce to a simpler Markov chain with state space the set of partitions and with combinatorial weights. The Sideward Merge part of the dynamics prevents convergence to fully formed connected structures (trees), unless the different forms of Merge are weighted by a cost function, as predicted by linguistic theory. Results on the asymptotic behavior of the Perron-Frobenius eigenvalue and eigenvector in this weighted case, obtained in terms of an associated Perron-Frobenius problem in the tropical semiring, show that the usual cost functions (Minimal Search and Resource Restrictions) proposed in the linguistic literature do not suffice to obtain convergence to the tree structures, while an additional optimization property based on the Shannon entropy achieves the expected result for the dynamics. We also comment on the introduction of continuous parameters related to semantic embedding and other computational models, and also on some filtering of the dynamics by coloring rules that model the linguistic filtering by theta roles and phase structure, and on parametric variation and the process of parameter setting in Externalization.
Related papers
- Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation [56.361076943802594]
CanonFlow achieves state-of-the-art performance on the challenging GEOM-DRUG dataset, and the advantage remains large in few-step generation.
arXiv Detail & Related papers (2026-02-16T18:58:55Z) - The metaplectic semigroup and its applications to time-frequency analysis and evolution operators [0.0]
We develop a systematic analysis of the metaplectic semigroup $mathrmMp_+(d,mathbbC)$ associated with positive complex symplectic matrices.<n>We exploit these structural results to characterize, from a metaplectic perspective, classes of time-frequency representations satisfying prescribed structural properties.
arXiv Detail & Related papers (2026-01-29T19:21:40Z) - Dynamics of Agentic Loops in Large Language Models: A Geometric Theory of Trajectories [0.0]
This paper introduces a geometric framework for analyzing agentic trajectories in semantic embedding space.<n>Because cosine similarity is biased by embedding anisotropy, we introduce an isotonic calibration.<n>This enables rigorous measurement of trajectories, clusters and attractors.
arXiv Detail & Related papers (2025-12-11T07:06:14Z) - Compositional Symmetry as Compression: Lie Pseudogroup Structure in Algorithmic Agents [0.0]
In the (Kolmogorov) view, agents are programs that track and compress sensory streams using generative programs.<n>We propose a framework where the relevant structural prior is simplicity (off) understood as emphSolomonal symmetry<n>We show that accurate world-tracking imposes (i) emphdynamic constraints -- and (ii) emphdynamic constraints under static inputs.
arXiv Detail & Related papers (2025-10-12T13:06:37Z) - Ultracoarse Equilibria and Ordinal-Folding Dynamics in Operator-Algebraic Models of Infinite Multi-Agent Games [0.0]
We develop an operator algebraic framework for infinite games with a continuum of agents.<n>We prove that regret based learning dynamics governed by a noncommutative continuity equation converge to a unique quantal response equilibrium.<n>We introduce the ordinal folding index, a computable ordinal valued metric that measures the self referential depth of the dynamics.
arXiv Detail & Related papers (2025-07-25T22:20:42Z) - Free-Fermion Dynamics with Measurements: Topological Classification and Adaptive Preparation of Topological States [0.0]
We develop a general framework for classifying fermionic dynamical systems with measurements using symmetry and topology.<n>We build and simulate 2+1d adaptive circuits that realize mEO-class-A topological dynamics.<n>We numerically study the topological phase transitions and dynamical domain-wall modes between different topological dynamical phases in this symmetry class.
arXiv Detail & Related papers (2025-07-17T18:00:01Z) - Why Neural Network Can Discover Symbolic Structures with Gradient-based Training: An Algebraic and Geometric Foundation for Neurosymbolic Reasoning [73.18052192964349]
We develop a theoretical framework that explains how discrete symbolic structures can emerge naturally from continuous neural network training dynamics.<n>By lifting neural parameters to a measure space and modeling training as Wasserstein gradient flow, we show that under geometric constraints, the parameter measure $mu_t$ undergoes two concurrent phenomena.
arXiv Detail & Related papers (2025-06-26T22:40:30Z) - A Free Probabilistic Framework for Analyzing the Transformer-based Language Models [19.78896931593813]
We present a formal operator-theoretic framework for analyzing Transformer-based language models using free probability theory.<n>This work offers a principled, though theoretical, perspective on structural dynamics in large language models.
arXiv Detail & Related papers (2025-06-19T19:13:02Z) - Relative Representations: Topological and Geometric Perspectives [50.85040046976025]
Relative representations are an established approach to zero-shot model stitching.<n>We introduce a normalization procedure in the relative transformation, resulting in invariance to non-isotropic rescalings and permutations.<n>Second, we propose to deploy topological densification when fine-tuning relative representations, a topological regularization loss encouraging clustering within classes.
arXiv Detail & Related papers (2024-09-17T08:09:22Z) - Distributed Bayesian Learning of Dynamic States [65.7870637855531]
The proposed algorithm is a distributed Bayesian filtering task for finite-state hidden Markov models.
It can be used for sequential state estimation, as well as for modeling opinion formation over social networks under dynamic environments.
arXiv Detail & Related papers (2022-12-05T19:40:17Z) - Initial Correlations in Open Quantum Systems: Constructing Linear
Dynamical Maps and Master Equations [62.997667081978825]
We show that, for any predetermined initial correlations, one can introduce a linear dynamical map on the space of operators of the open system.
We demonstrate that this construction leads to a linear, time-local quantum master equation with generalized Lindblad structure.
arXiv Detail & Related papers (2022-10-24T13:43:04Z) - Models of zero-range interaction for the bosonic trimer at unitarity [91.3755431537592]
We present the construction of quantum Hamiltonians for a three-body system consisting of identical bosons mutually coupled by a two-body interaction of zero range.
For a large part of the presentation, infinite scattering length will be considered.
arXiv Detail & Related papers (2020-06-03T17:54:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.