Searcharxiv⌕ Search

arXiv · cond-mat/9910370

Cooling-rate effects in a model of (ideal?) glass

Abstract

Using Monte Carlo simulations we study cooling-rate effects in a three-dimensional Ising model with four-spin interaction. During coarsening, this model develops growing energy barriers which at low temperature lead to very slow dynamics. We show that the characteristic zero-temperature length increases very slowly with the inverse cooling rate, similarly to the behaviour of ordinary glasses. For computationally accessible cooling rates the model undergoes an ideal glassy transition, i.e., the glassy transition for very small cooling rate coincides a thermodynamic singularity. We also study cooling of this model with a certain fraction of spins fixed. Due to such heterogeneous crystalization seeds the final state strongly depends on the cooling rate.Only for sufficiently fast cooling rate does the system end up in a glassy state while slow cooling inevitably leads to a crystal phase.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A. Lipowski, D. Johnston. 1999-10-22. Cooling-rate effects in a model of (ideal?) glass. https://doi.org/10.1103/physreve.61.6375

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

KEEP EXPLORING

Related papers

Altered temporal scaling of semantic similarity fluctuations in psychosis

Scale-free temporal organization, in which fluctuations show similar statistical structures across timescales, is a feature of many complex systems considered to support optimal functioning. Alterations of such scaling have been reported in several pathologies, but whether comparable alterations characterize the temporal organization of language remains largely unexplored. We address this question in the domain of psychosis, where language anomalies are pervasively documented. Specifically, we apply detrended fluctuation analysis (DFA) to quantify temporal scaling in Qwen3-derived continuous cosine similarity time series, capturing trajectories through semantic space computed from transcripts of picture descriptions across three independent datasets. DFA scaling exponents α were extracted to characterize the strength of long-range temporal correlations. Across all datasets, patients exhibited significantly elevated α relative to controls, indicating increased temporal persistence in semantic fluctuations. This analysis opens a window into the multi-timescale organization of meaning as it unfolds in discourse and reveals a signature of altered temporal scaling. This alteration parallels known departures from critical scaling in brain dynamics in psychosis, suggesting the exploration of possible links between these two.

cond-mat.stat-mech↗

Modified Family-Vicsek Scaling and Probability Distributions for Brownian Castle Interfaces

The Brownian Castle is a new interface growth model that is a variation on the well-known ballistic deposition model that results in an entirely new universality class. We present numerical verification that the interface width for BC interfaces displays modified Family-Vicsek scaling properties up to finite size corrections. Specifically, we find a growth exponent of $β=0.470 \pm 0.012$ and a roughness exponent of $α=1.01 \pm 0.018$. The scaling is modified at short times with a size scaling exponent that described the early time dependence of interface width on length. The probability distribution of heights for the BC interface shows significant deviations from simple Gaussian behavior and the probability distribution of height changes shows a Cauchy-Lorentz form consistent with expectations for a process involving relatively large jumps.

cond-mat.stat-mech↗

Ensemble theory of thermodiffusion

Heat flow sustained by a temperature difference generates a gradient of matter as observed, for example, in atomistic simulations of hard-core gases. We use path-ensemble theory to represent the coupled thermal and diffusive transport by dynamics on a graph. Calibrated from a single equilibrium simulation, this model accurately predicts nonequilibrium mass distribution in a hard-core gas across a wide range of applied temperature gradients. It also enables estimation of transport properties, such as the Soret coefficient, using analytical expressions.

cond-mat.stat-mech↗