SearcharxivSearch

arXiv · 2509.15415

Spectral Characterization of Wave Scattering at a Granular-Elastic Solid Interface: From Hyperbolic Wave Propagation to Near-Parabolic Diffusion

Abstract

We present a method based on acoustic wavenumber imaging algorithms to quantify the spectral content of strongly nonlinear energy scattering of a propagating wavefront across the discrete-continuum interface of a 2D hybrid system composed of an ordered granular layer in contact with a thin elastic plate. We consider snapshots of the transmitted wavefront at given time instants, which are filtered across the wavenumber domain by applying the spatial Fourier Transform (FT), and then the filtered wavefields are transformed back to the spatial domain by inverse spatial FT. This yields a spectral decomposition of the given snapshots at varying center wavenumbers. Based on this postprocessing method, the scattering of the kinetic energy in the receiving medium (plate) can be studied in the wavenumber-time domain, proving a quantitative measure of the nonlinear scattering of the transmitted wavefront by the strongly nonlinear 2D granular layer. This postprocessing method enables the detailed quantitative study of the scattering and spectral energy redistribution of propagating wavepackets in elastic media with embedded linear or nonlinear layers or inclusions. In addition, we show that the spectral evolution of receiving plate with a granular interface exhibits diffusion-like behavior in the wavenumber domain, drawing an analogy between parabolic heat diffusion and classical hyperbolic elsatodynamic energy transport.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Joshua R. Tempelman, Chongan Wang, Alexander F. Vakakis. 2025-09-18. Spectral Characterization of Wave Scattering at a Granular-Elastic Solid Interface: From Hyperbolic Wave Propagation to Near-Parabolic Diffusion. https://arxiv.org/abs/2509.15415

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Universal sampling of spin systems across quenched disorder

Statistical physics extracts macroscopic laws by averaging over the many microscopic degrees of freedom of a system. Disordered systems demand a second and far harder average, one over the quenched randomness itself. The classic analytical routes, the replica and cavity methods, become uncontrolled outside mean-field or tree-like limits, and conventional numerical algorithms like parallel tempering require expensive, independent equilibration for every disorder realization. In this work, we introduce a universal neural variational framework that amortizes inference across the disorder ensemble, eliminating both the need for per-instance Markov chain equilibration and the cost of retraining instance-specific variational ansatzes. Built on an encoder-decoder Transformer architecture, after training once, it produces an explicit approximation to the Boltzmann distribution given previously unseen disorder realizations without further optimization. We validate this framework on 2D Edwards-Anderson models, and apply it to the random-bond Ising model, successfully capturing the Binder cumulant crossings near the Nishimori multicritical point. These results shift the object of variational inference from the single instance to the disorder ensemble, opening a route to frustrated many-body systems where instance-by-instance computation is prohibitive.

cond-mat.stat-mech

Information-Theoretic Characterization of Macroscopic Chaos Emerging from the Chemical Master Equation

Open chemical reaction networks exhibit stochastic concentration dynamics at finite system sizes, whereas their macroscopic limit is governed by deterministic rate equations that can display chaos. In this Letter, we show theoretically that a rate of information loss constructed from two-time mutual information recovers the Kolmogorov-Sinai entropy in the deterministic limit. We verify this result through numerical simulations of a Markov jump process for a three-species system involving seven reactions.

cond-mat.stat-mech

Orientational order on non-orientable domains

We study the statistical properties of passive and active many-body systems with orientational degrees of freedom on non-orientable domains. By rephrasing topological constraints as non-local symmetry relations on an orientable double-cover, we show that non-orientability eliminates global rotational soft modes without acting like an external field. In a passive XY model, this results in topological caging, where orientational fluctuations that exhibit conventional diffusive behavior on a torus saturate on a Klein bottle to a finite value that we compute exactly in the thermodynamic limit. In models of active self-propelled particles with orientational degrees of freedom, topological caging persists despite continuously changing interaction neighborhoods. In an active Ising spin model, non-orientability enforces the coexistence of ordered anti-parallel domains with vanishing global polar order, a state that is absent on orientable domains.

cond-mat.stat-mech