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SUMMARY:Jan Hladky (Czech Academy of Sciences)
DTSTART:20210111T140000Z
DTEND:20210111T150000Z
DTSTAMP:20260423T035537Z
UID:EPC/42
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/EPC/42/">Fli
 p processes on finite graphs and dynamical systems they induce on graphons
 </a>\nby Jan Hladky (Czech Academy of Sciences) as part of Extremal and pr
 obabilistic combinatorics webinar\n\n\nAbstract\nWe introduce a class of r
 andom graph processes\, which we call \\emph{flip processes}. Each such pr
 ocess is given by a \\emph{rule} which is just a function $\\mathcal{R}:\\
 mathcal{H}_k\\rightarrow \\mathcal{H}_k$ from all labelled $k$-vertex grap
 hs into itself ($k$ is fixed). Now\, the process starts with a given $n$-v
 ertex graph $G_0$. In each step\, the graph $G_i$ is obtained by sampling 
 $k$ random vertices $v_1\,\\ldots\,v_k$ of $G_{i-1}$ and replacing the ind
 uced graph $G_{i-1}[v_1\,\\ldots\,v_k]$ by $\\mathcal{R}(G_{i-1}[v_1\,\\ld
 ots\,v_k])$. This class contains several previously studied processes incl
 uding the Erdos-Renyi random graph process and the random triangle removal
 .\n\nGiven a flip processes with a rule $\\mathcal{R}$ we construct time-i
 ndexed trajectories $\\Phi:\\mathcal{W}\\times [0\,\\infty)\\rightarrow\\m
 athcal{W}$ in the space of graphons. We prove that with high probability\,
  starting with a large finite graph $G_0$ which is close to a graphon $W_0
 $ in the cut norm distance\, the flip process will stay in a thin sausage 
 around the trajectory $(\\Phi(W_0\,t))_{t=0}^\\infty$ (after rescaling the
  time by the square of the order of the graph).\n\nThese graphon trajector
 ies are then studied from the perspective of dynamical systems. We prove t
 hat two trajectories cannot form a confluence\, give an example of a proce
 ss with an oscilatory trajectory\, and address the question of existence a
 nd stability of fixed points and periodic trajectories.\n
LOCATION:https://researchseminars.org/talk/EPC/42/
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