Kahn–Kalai conjecture

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Template:Short description The Kahn–Kalai conjecture, also known as the expectation threshold conjecture or more recently the Park-Pham Theorem, was a conjecture in the field of graph theory and statistical mechanics, proposed by Jeff Kahn and Gil Kalai in 2006.[1][2] It was proven in a paper published in 2024.[3]

Background

This conjecture concerns the general problem of estimating when phase transitions occur in systems.[1] For example, in a random network with N nodes, where each edge is included with probability p, it is unlikely for the graph to contain a Hamiltonian cycle if p is less than a threshold value (logN)/N, but highly likely if p exceeds that threshold.[4]

Threshold values are often difficult to calculate, but a lower bound for the threshold, the "expectation threshold", is generally easier to calculate.[1] The Kahn–Kalai conjecture is that the two values are generally close together in a precisely defined way, namely that there is a universal constant K for which the ratio between the two is less than Klogl() where l() is the size of a largest minimal element of an increasing family of subsets of a power set.[3]

Proof

Jinyoung Park and Huy Tuan Pham announced a proof of the conjecture in 2022; it was published in 2024.[4][3]

References

Template:Reflist

See also