Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · cond-mat/0208594

High frequency acoustic modes in liquid gallium at the melting point

T. Scopigno·A. Filipponi·M. Krisch·G. Monaco·G. Ruocco·F. Sette
View original source ↗Read source document ↗Export metadata ↓

Abstract

The microscopic dynamics in liquid gallium (l-Ga) at melting (T=315 K) has been studied by inelastic x-ray scattering. We demonstrate the existence of collective acoustic-like modes up to wave-vectors above one half of the first maximum of the static structure factor, at variance with earlier results from inelastic neutron scattering data [F.J. Bermejo et al. Phys. Rev. E 49, 3133 (1994)]. Despite the structural (an extremely rich polymorphism and rather complex phase diagram) and electronic (mixed valence) peculiarity of l-Ga, its collective dynamics is strikingly similar to the one of Van der Walls and alkali metals liquids. This result speaks in favor of the universality of the short time dynamics in monatomic liquids rather than of system-specific dynamics.

Explore related subjects

cond-mat.dis-nn

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

T. Scopigno, A. Filipponi, M. Krisch, G. Monaco, G. Ruocco, F. Sette. 2002-08-30. High frequency acoustic modes in liquid gallium at the melting point. https://doi.org/10.1103/physrevlett.89.255506

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

KEEP EXPLORING

Related papers

arXiv2026

Tunable periodic cascade of delocalization transitions in non-Hermitian IAAF model

Cascade of delocalization transitions provides a route to multi-step control of delocalization, yet achieving a programmable periodic cascade remains a challenge. Here, we demonstrate a tunable periodic cascade of delocalization transitions in a non-Hermitian interpolating Aubry-André-Fibonacci (IAAF) model by introducing an imaginary phase shift into the quasiperiodic potential. Such a periodic cascade of delocalization transitions arises from the competition between kinetic-energy-facilitated delocalization and gain-loss-regulated localization. In numerical static localization characterizations, successive regular stripe patterns for localized and extended states emerge in phase diagrams. We also derive an analytical expression for the cascade period and find that it relies solely on the imaginary phase shift. This provides a direct way of continuously tuning the cascade period via a single control parameter. Complementary static and dynamical diagnostics consistently confirm this periodic cascade of delocalization transitions in the non-Hermitian IAAF system. Our findings identify a novel class of delocalization transitions with tunable cascading periods, opening a route toward experimentally programmable control of delocalization.

cond-mat.dis-nn↗
arXiv2026

Microscopic Mechanism and Control of Reentrant Localization

Increasing quasiperiodic modulation can restore extended states after localization, raising the question of how the same modulation drives both localization and recovery. We identify a microscopic mechanism in quasiperiodic dimer chains by resolving scattering between Fourier channels. Specifically, scattering into neighboring channels and back shifts the spectral edge relative to a localization boundary determined by a neutral auxiliary resonance. Their successive crossings drive the same spectral packet with fixed integrated-density-of-states (IDS) labels into localization and back into an extended regime. This recovery persists across finite parameter ranges in both gap-opening families, including relative-phase detuning. Furthermore, an exact sublattice mapping enables compensated control of the recovery window and predicts recovery thresholds for individual IDS labels.

cond-mat.dis-nn↗
arXiv2026

Dynamical mean-field theory for associative memory with block-correlated patterns

In associative memories storing correlated patterns, retrieval of individual memories can compete with symmetric mixed states. A dynamical description is needed to determine how the initial state selects between these outcomes. We extend the generating-functional dynamical mean-field theory (DMFT) for independent patterns to independent blocks of correlated binary patterns of fixed finite size. The resulting effective single-neuron process has a self-consistent cross-talk noise covariance and self-feedback coefficients that depend on the block-covariance eigenvalues. For hierarchically correlated patterns with nonmonotonic transfer, increasing the loading can permit retrieval from an imperfect initial state before further loading prevents it. DMFT reproduces the retrieval trajectories and basin geometry found in direct simulations. Near the lower boundary of this re-entrant region, direct networks reveal stationary saddles separating coexisting mixed and target-retrieval states. Parameter sensitivities of DMFT trajectories predict nearby shifts of this boundary. At the tested upper boundary, retrieval remains accessible from initial states with larger target overlap, indicating a change in basin access. Under fixed-point convergence assumptions, the theory recovers the equations of generalized self-consistent signal-to-noise analysis.

cond-mat.dis-nn↗