dorsal/arxiv
View SchemaUnavoidable Canonical Nonlinearity Induced by Gaussian Measures Discretization
| Authors | Koretaka Yuge |
|---|---|
| Categories | |
| ArXiv ID | 2601.08381vv4 |
| URL | https://arxiv.org/abs/2601.08381 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
Abstract
When we consider canonical averages for classical discrete systems, typically referred to as substitutional alloys, the map phi from many-body interatomic interactions to thermodynamic equilibrium configurations generally exhibits complicated nonlinearity. This canonical nonlinearity is fundamentally rooted in deviations of the discrete configurational density of states (CDOS) from continuous Gaussian families, and has conventionally been characterized by the Kullback-Leibler (KL) divergence on discrete statistical manifold. Thus, the previous works inevitablly missed intrinsic nonlinearities induced by discretization of Gaussian families, which remains invisible within conventional information-geometric descriptions. In the present work, we identify and quantify such unavoidable canonical nonlinearity by employing the 2-Wasserstein distance with a cost function aligned with the Fisher metric for Gaussian families. We derive an explicit expression for the Wasserstein distance in the limit of vanishing discretization scale d to 0: W2 = d*sqrt(Tr(Gamma)^(-1)/12), where Gamma denotes covariance matrix of the CDOS. We further show that this limiting Wasserstein distance admits a clear geometric interpretation on the statistical manifold, equivalent to a KL divergence associated with the expected parallel translations of continuous Gaussian. Our framework thus provides a transport-information-geometric characterization of discretization-induced nonlinearity in classical discrete systems. In addition, we confirm that this W2-KL equivalence admits a natural generalization beyond Gaussian families, provided that the transport cost is aligned with the Fisher metric of an underlying statistical submanifold and the discretization scale induces infinitesimal parameter variations.
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"abstract": "When we consider canonical averages for classical discrete systems, typically referred to as substitutional alloys, the map phi from many-body interatomic interactions to thermodynamic equilibrium configurations generally exhibits complicated nonlinearity. This canonical nonlinearity is fundamentally rooted in deviations of the discrete configurational density of states (CDOS) from continuous Gaussian families, and has conventionally been characterized by the Kullback-Leibler (KL) divergence on discrete statistical manifold. Thus, the previous works inevitablly missed intrinsic nonlinearities induced by discretization of Gaussian families, which remains invisible within conventional information-geometric descriptions. In the present work, we identify and quantify such unavoidable canonical nonlinearity by employing the 2-Wasserstein distance with a cost function aligned with the Fisher metric for Gaussian families. We derive an explicit expression for the Wasserstein distance in the limit of vanishing discretization scale d to 0: W2 = d*sqrt(Tr(Gamma)^(-1)/12), where Gamma denotes covariance matrix of the CDOS. We further show that this limiting Wasserstein distance admits a clear geometric interpretation on the statistical manifold, equivalent to a KL divergence associated with the expected parallel translations of continuous Gaussian. Our framework thus provides a transport-information-geometric characterization of discretization-induced nonlinearity in classical discrete systems. In addition, we confirm that this W2-KL equivalence admits a natural generalization beyond Gaussian families, provided that the transport cost is aligned with the Fisher metric of an underlying statistical submanifold and the discretization scale induces infinitesimal parameter variations.",
"arxiv_id": "2601.08381",
"authors": [
"Koretaka Yuge"
],
"categories": [
"cond-mat.stat-mech"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "Unavoidable Canonical Nonlinearity Induced by Gaussian Measures Discretization",
"url": "https://arxiv.org/abs/2601.08381",
"version": "v4"
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