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Marrying Graph Convergence and Cascade Models

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Shows that for bounded‑degree or large‑set expander graph sequences the critical probability converges and any giant component is unique and has a relative size that converges; proves a constant‑query local estimator (a few BFS‑style simulations from uniform random nodes) gives a 1–ε approximation of that limit; uses sprinkling + Menger paths to merge many constant‑size clusters and Efron‑Stein/variance control (instead of bounded‑differences) for the directed percolation bow‑tie result and equality of directed/undirected thresholds.

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  1. 0:00Start
  2. 0:10Personal Story
  3. 5:06The Epidemic Process
  4. 6:17Directed Percolation
  5. 8:23The Critical Probability
  6. 11:01Converging Sequence
  7. 22:47The Household Model
  8. 24:37The Directed Percolation
  9. 38:49Concentration Bonds
  10. 40:51Menger's Theorem
  11. 53:01Coupling the Director to the Undirected
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