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Internal diffusion-limited aggregation (IDLA) is a stochastic growth model on a graph $G$ which describes the formation of a random set of vertices growing from the origin (some fixed vertex) of $G$. Particles start at the origin and…

Probability · Mathematics 2020-08-26 Joe P. Chen , Wilfried Huss , Ecaterina Sava-Huss , Alexander Teplyaev

Internal DLA (IDLA) is an internal aggregation model in which particles perform random walks from the origin, in turn, and stop upon reaching an unoccupied site. Levine and Peres showed that, when particles start instead from fixed…

Probability · Mathematics 2022-01-24 David Darrow

We compute the probability of positive large deviations of the free energy per spin in mean-field Spin-Glass models. The probability vanishes in the thermodynamic limit as $P(\Delta f) \propto \exp[-N^2 L_2(\Delta f)]$. For the…

Disordered Systems and Neural Networks · Physics 2012-10-31 Giorgio Parisi , Tommaso Rizzo

We investigate diffusion-limited aggregation (DLA) in a wedge geometry. Arneodo and collaborators have suggested that the ensemble average of DLA cluster density should be close to the noise-free selected Saffman-Taylor finger. We show that…

Statistical Mechanics · Physics 2009-11-11 Leonard M. Sander , Ellak Somfai

An appropriate model for the random energy landscape in organic glasses is a spatially correlated Gaussian field. We calculated the distribution of the average value of a Gaussian random field in a finite domain. The results of the…

Disordered Systems and Neural Networks · Physics 2013-03-21 S. V. Novikov

We study internal diffusion limited aggregation (DLA) on the two dimensional comb lattice. The comb lattice is a spanning tree of the euclidean lattice, and internal DLA is a random growth model, where simple random walks, starting one at a…

Probability · Mathematics 2014-01-28 Amine Asselah , Houda Rahmani

We consider geometrical clusters (i.e. domains of parallel spins) in the square lattice random field Ising model by varying the strength of the Gaussian random field, $\Delta$. In agreement with the conclusion of previous investigation…

Statistical Mechanics · Physics 2010-08-09 László Környei , Ferenc Iglói

We test the multiscaling issue of DLA clusters using a modified algorithm. This algorithm eliminates killing the particles at the death circle. Instead, we return them to the birth circle at a random relative angle taken from the evaluated…

Statistical Mechanics · Physics 2009-11-11 Anton Yu. Menshutin , Lev N. Shchur

We study the scaling limits of three different aggregation models on the integer lattice Z^d: internal DLA, in which particles perform random walks until reaching an unoccupied site; the rotor-router model, in which particles perform…

Probability · Mathematics 2007-12-31 Lionel Levine

In a previous work, we showed that the 2D, extended-source internal DLA (IDLA) of Levine and Peres is $\delta^{3/5}$-close to its scaling limit, if $\delta$ is the lattice size. In this paper, we investigate the scaling limits of the…

Probability · Mathematics 2022-01-24 David Darrow

Calculation of the distribution of the average value of a Gaussian random field in a finite domain is carried out for different cases. The results of the calculation demonstrate a strong dependence of the width of the distribution on the…

Disordered Systems and Neural Networks · Physics 2015-05-13 S. V. Novikov , M. Van der Auweraer

The Gauss circle problem asks for an approximation to the number of lattice points of $\mathbb{Z}^2$ contained in $B_r$, the disk of radius $r$ centered at the origin. Upper, lower, and average bounds have been established for this…

Mathematical Physics · Physics 2024-12-10 Roni A. Edwin , Allen Lin

For a class of aggregation models on the integer lattice $\mathbb{Z}^d$, $d\geq 2$, in which clusters are formed by particles arriving one after the other and sticking irreversibly where they first hit the cluster, including the classical…

Probability · Mathematics 2023-08-28 Tillmann Bosch , Steffen Winter

We develop a technique for probing harmonic measure of the diffusion limited aggregation (DLA) cluster surface with the variable size particle and generate one thousand clusters with 50 million particles using original off-lattice…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Yu. Menshutin , L. N. Shchur , V. M. Vinokur

We study the minimum mean-squared error for 2-means clustering when the outcomes of the vector-valued random variable to be clustered are on two touching spheres of unit radius in $n$-dimensional Euclidean space and the underlying…

Probability · Mathematics 2018-10-17 Bernhard G. Bodmann , Craig J. George

We use coupling ideas introduced in \cite{levine2018long} to show that an IDLA process on a cylinder graph $G\times \mathbb{Z}$ forgets a typical initial profile in $\mathcal{O}( N\sqrt{\tau_N} (\log \! N)^2 )$ steps for large $N$, where…

Probability · Mathematics 2020-07-02 Vittoria Silvestri

Diffusion-limited cluster aggregation (DLCA) is a well established model for the formation of highly porous low-density non-equilibrium structures. One of the main conclusions of the previous studies considering this model is that the…

Soft Condensed Matter · Physics 2019-01-15 Swetlana Jungblut , Jan-Ole Joswig , Alexander Eychmüller

We discuss random geometric structures obtained by percolation of Brownian loops, in relation to the Gaussian Free Field, and how their existence and properties depend on the dimension of the ambient space. We formulate a number of…

Probability · Mathematics 2020-02-27 Wendelin Werner

We study the volume of the critical clusters for the percolation of the level sets of the Gaussian free field on metric graphs. On $\mathbb{Z}^d$ below the upper-critical dimension $d=6$, we show that the largest such cluster in a box of…

Probability · Mathematics 2024-12-10 Alexander Drewitz , Alexis Prévost , Pierre-François Rodriguez

Latent Dirichlet allocation (LDA) obtains essential information from data by using Bayesian inference. It is applied to knowledge discovery via dimension reducing and clustering in many fields. However, its generalization error had not been…

Machine Learning · Statistics 2021-01-26 Naoki Hayashi