Hausdorff dimension of collision times in one-dimensional log-gases

We consider systems of multiple Brownian particles in one dimension that repel mutually via a logarithmic potential on the real line, more specifically the Dyson model. These systems are characterized by a parameter that controls the strength of the interaction, k > 0. Despite being a one-dimensional system, this system is interesting due to the properties that arise from the long-range interaction between particles. It is a well-known fact that when k is small enough, particle collisions occur almost surely, while when k is large, collisions never occur. However, aside from this fact, there was no characterization of the collision times until now. In this paper, we derive the fractal (Hausdorff) dimension of the set of collision times by generalizing techniques introduced by L. Liu and Y. Xiao [Probab. Math. Stat. 18(2), 369–383 (1998)] to study the return times to the origin of self-similar Markov processes. In our case, we consider the return times to configurations where at least one collision occurs, which is a condition that defines unbounded sets as opposed to a single point, namely, the origin. We find that the fractal dimension characterizes the collision behavior of these systems and establishes a clear delimitation between the colliding and non-colliding regions in a way similar to that of a thermodynamic function.

Authors

Institutions

Publication Details

Journal
AIP Advances
Published
2024-09-01
DOI
https://doi.org/10.1063/5.0148019
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hausdorff dimension of collision times in one-dimensional log-gases

Sergio Andraus, Nicole Hufnagel
AIP Advances
Random Matrices and Applications
article

Hausdorff dimension of collision times in one-dimensional log-gases

Sergio Andraus, Nicole Hufnagel
article en

Abstract

We consider systems of multiple Brownian particles in one dimension that repel mutually via a logarithmic potential on the real line, more specifically the Dyson model. These systems are characterized by a parameter that controls the strength of the interaction, k > 0. Despite being a one-dimensional system, this system is interesting due to the properties that arise from the long-range interaction between particles. It is a well-known fact that when k is small enough, particle collisions occur almost surely, while when k is large, collisions never occur. However, aside from this fact, there was no characterization of the collision times until now. In this paper, we derive the fractal (Hausdorff) dimension of the set of collision times by generalizing techniques introduced by L. Liu and Y. Xiao [Probab. Math. Stat. 18(2), 369–383 (1998)] to study the return times to the origin of self-similar Markov processes. In our case, we consider the return times to configurations where at least one collision occurs, which is a condition that defines unbounded sets as opposed to a single point, namely, the origin. We find that the fractal dimension characterizes the collision behavior of these systems and establishes a clear delimitation between the colliding and non-colliding regions in a way similar to that of a thermodynamic function.

AIP AdvancesVol. 14(9)
Heinrich Heine University Düsseldorf (DE), Tsukuba International University (JP)
Deutsche Forschungsgemeinschaft, Japan Society for the Promotion of Science
Openalex Percentile: Top 100%
Random Matrices and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Hausdorff dimension of collision times in one-dimensional log-gases — Sergio Andraus, Nicole Hufnagel · AIP Advances (2024) | TGRS Research Map | TGRS