Searcharxiv⌕ Search

arXiv · cond-mat/0404143

Exponential and power law distribution of mass clusters in a (magnetic-like) deposition model of elongated grains in 2D piles

Abstract

A generalized so called magnetically controlled ballistic rain-like deposition (MBD) model of granular piles has been numerically investigated in 2D. The grains are taken to be elongated disks whence characterized by a two-state scalar degree of freedom, called ''nip'', their interaction being described through a Hamiltonian. Results are discussed in order to search for the effect of nip flip (or grain rotation from vertical to horizontal and conversely) probability in building a granular pile. The characteristics of creation of + (or $-$) nip's clusters and clusters of holes (missing nips) are analyzed. Two different cluster-mass regimes have been identified, through the cluster-mass distribution function which can be exponential or have a power law form depending on whether the nip flip (or grain rotation) probability is large or small. Analytical forms of the exponent are empirically found in terms of the Hamiltonian parameters.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

K. Trojan, M. Ausloos, R. Cloots. 2004-04-06. Exponential and power law distribution of mass clusters in a (magnetic-like) deposition model of elongated grains in 2D piles. https://doi.org/10.1142/s0129183104006571

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↗