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B. Waclaw

Publications and source records attributed to B. Waclaw.

21 records · Page 2Linked to original sources

Balls-in-boxes condensation on networks

We discuss two different regimes of condensate formation in zero-range processes on networks: on a q-regular network, where the condensate is formed as a result of a spontaneous symmetry breaking, and on an irregular network, where the symmetry of the partition function is explicitly broken. In the latter case we consider a minimal irregularity of the q-regular network introduced by a single Q-node with degree Q>q. The statics and dynamics of the condensation depends on the parameter log(Q/q), which controls the exponential fall-off of the distribution of particles on regular nodes and the typical time scale for melting of the condensate on the Q-node which increases exponentially with the system size $N$. This behavior is different than that on a q-regular network where log(Q/q)=0 and where the condensation results from the spontaneous symmetry breaking of the partition function, which is invariant under a permutation of particle occupation numbers on the q-nodes of the network. In this case the typical time scale for condensate melting is known to increase typically as a power of the system size.

cond-mat.stat-mech↗

Eigenvalue density of empirical covariance matrix for correlated samples

We describe a method to determine the eigenvalue density of empirical covariance matrix in the presence of correlations between samples. This is a straightforward generalization of the method developed earlier by the authors for uncorrelated samples. The method allows for exact determination of the experimental spectrum for a given covariance matrix and given correlations between samples in the limit of large N and N/T=r=const with N being the number of degrees of freedom and T being the number of samples. We discuss the effect of correlations on several examples.

cond-mat.stat-mech↗

A program generating homogeneous random graphs with given weights

We present a program package which generates homogeneous random graphs with probabilities prescribed by the user. The statistical weight of a labeled graph $α$ is given in the form $W(α)=\prod_{i=1}^N p(q_i)$, where $p(q)$ is an arbitrary user function and $q_i$ are the degrees of the graph nodes. The program can be used to generate two types of graphs (simple graphs and pseudo-graphs) from three types of ensembles (micro-canonical, canonical and grand-canonical).

cond-mat.dis-nn↗