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Anđela Šarković

Publications and source records attributed to Anđela Šarković.

6 recordsLinked to original sources

Random walk on the small-world network model in 3 or more dimensions

We study the mixing time of a simple random walk on the small-world network defined by adding edges to $\mathbb{Z}_n^d$ as follows: for each pair $\{x,y\}$ we add an edge with probability $Z_n/\|x-y\|^{d}$ with $Z_n$ chosen so that the average number of added edges to every vertex is $1$. When $d\geq 3$, we show that with high probability the mixing time is of order $\log n$ and that the random walk does not exhibit cutoff.

math.PR↗

Mixing time of the lazy and simple random walk on a randomly twisted hypercube

We consider a randomly twisted hypercube on $N$ vertices and study a simple or lazy random walk on this graph. We show that for both walks the mixing time is of order $\log N$, and the model does not exhibit cutoff. We also establish that both walks have cover time of order $N\log N$, and we show that the chromatic number of the graph diverges.

math.PR↗

Polynomial mixing for polygonal side matchings

We introduce a natural Markov chain on chord diagrams, which, at every step, selects two random chords and swaps them if doing so preserves the diagram's genus. This generalizes the chord swap chain on the Catalan structure of non-intersecting chord diagrams. We show that for fixed genus, the chain mixes in polynomial time.

math.PR↗

Mixing time of the random walk on the giant component of the random geometric graph

We consider a random geometric graph obtained by placing a Poisson point process of intensity 1 in the d-dimensional torus of side length n^(1/d) and connecting two points by an edge if their distance is at most r. We consider the case of d>=2 and r in [r_min, r_max], where r_min r_g and r_g is a constant above which this graph has a giant component with high probability. We show that, with high probability, the mixing time and the relaxation time of the simple random walk on the giant component in this case are both of order n^(2/d) and that therefore there is no cutoff. We also obtain bounds for the isoperimetric profile of subsets of the giant component of at least polylogarithmic size.

math.PR↗

Cutoff for random walk on random graphs with a community structure

We consider a variant of the configuration model with an embedded community structure and study the mixing properties of a simple random walk on it. Every vertex has an internal $\mathrm{deg}^{\text{int}}\geq 3$ and an outgoing $\mathrm{deg}^{\text{out}}$ number of half-edges. Given a stochastic matrix $Q$, we pick a random perfect matching of the half-edges subject to the constraint that each vertex $v$ has $\mathrm{deg}^{\text{int}}(v)$ neighbours inside its community and the proportion of outgoing half-edges from community $i$ matched to a half-edge from community $j$ is $Q(i,j)$. Assuming the number of communities is constant and they all have comparable sizes, we prove the following dichotomy: simple random walk on the resulting graph exhibits cutoff if and only if the product of the Cheeger constant of $Q$ times $\log n$ (where $n$ is the number of vertices) diverges. In [4], Ben-Hamou established a dichotomy for cutoff for a non-backtracking random walk on a similar random graph model with 2 communities. We prove the same characterisation of cutoff holds for simple random walk.

math.PR↗

Phase transition for random walks on graphs with added weighted random matching

For a finite graph $G=(V,E)$ let $G^*$ be obtained by considering a random perfect matching of $V$ and adding the corresponding edges to $G$ with weight $\varepsilon$, while assigning weight 1 to the original edges of $G$. We consider whether for a sequence $(G_n)$ of graphs with bounded degrees and corresponding weights $(\varepsilon_n)$, the (weighted) random walk on $(G_n^*)$ has cutoff. For graphs with polynomial growth we show that $\log\left(\frac{1}{\varepsilon_n}\right)\ll\log|V_n|$ is a sufficient condition for cutoff. Under the additional assumption of vertex-transitivity we establish that this condition is also necessary. For graphs where the entropy of the simple random walk grows linearly up to some time of order $\log|V_n|$ we show that $\frac{1}{\varepsilon_n}\ll\log|V_n|$ is sufficient for cutoff. In case of expander graphs we also provide a complete picture for the complementary regime $\frac{1}{\varepsilon_n}\gtrsim\log|V_n|$.

math.PR↗