Comparison of fractional and integral expectation thresholds
Follow the latest progress by email.
Are fractional and integral expectation thresholds universally comparable for every nonempty proper increasing family on a finite nonempty ground set? Both definitions use the same covering budget one half, and fractional support is unrestricted.
Why it matters and what counts as progress
Why it matters: A universal constant comparison relates fractional covering relaxations to integral expectation thresholds without structural restrictions on the family.
What counts as progress: Prove q_f(F)≤Cq(F) for an absolute C, improve the constant or identify when the thresholds coincide.
How the problem developed
- 2010 · Conjecture [1]
Michel Talagrand Proposed that the integral and fractional expectation thresholds of every increasing family are comparable within a universal constant.
- 13 Aug 2021 · Partial bound [1]
Keith Frankston, Jeff Kahn, Bhargav Narayanan and Jinyoung Park Proved a logarithmic-factor bound relating the random threshold to the fractional expectation threshold, extending several results in probabilistic combinatorics.
- 23 Sept 2026 · Reported constant-factor theorem [2]
OpenAI Reported a universal constant comparison between the integral and fractional expectation thresholds for every nonempty proper increasing family on a finite set.
AI contribution
Integral and fractional expectation thresholds are equivalent
For every finite nonempty ground set and nonempty proper increasing family F, OpenAI proves q_f(F)≤25·512^4 q(F), comparing fractional and integral expectation thresholds with the same covering budget of one half and unrestricted fractional support.
Sources
- Frankston, Kahn, Narayanan and Park · Thresholds versus fractional expectation-thresholds (2021)
- OpenAI, Talagrand's conjecture that fractional and integral expectation thresholds agree up to a constant
- Integral and fractional expectation thresholds are equivalent
- OpenAI mathematics release and provenance
- Lean proof of OpenAI reports a constant-factor expectation-threshold theorem
Website timeline
Publication dates and editorial changes.
OpenAI reports a constant-factor expectation-threshold theorem