Ellipsoid fitting conjecture
Let be independent standard Gaussian vectors, and let as . The ellipsoid fitting conjecture predicts a sharp threshold at : if , then with probability tending to there exists a symmetric positive definite matrix such that for every ; if , then with probability tending to there is no symmetric positive semidefinite matrix satisfying for every .
References
Primary source
Additional references
Progress summary
Two August 2026 papers claim to settle the conjecture for Gaussian data, but the broader version remains open.
The conjecture was posed by Saunderson, Parrilo, and Willsky in work from 2011–2013 and predicts a sharp feasibility transition for fitting an ellipsoid through random Gaussian points.
Known results
- Potechin (2023): constructed fitting ellipsoids up to , far below the conjectured threshold.
- Bandeira and Maillard (2023): established an approximate transition at under a bounded-spectrum condition.
- Earlier work established only weaker satisfiability bounds and the dimension-count obstruction above .
August 2026 Gaussian resolution claims
On August 12, 2026, one preprint claimed the exact Gaussian threshold: feasibility with high probability when and infeasibility when , removing the prior approximate-fitting and spectral-bound restrictions. A second preprint claimed the same threshold up to a vanishing factor. These claims are not independently verified. A separate August 2026 report describes a fourth-moment-universal extension, but the supplied evidence does not establish its full scope.
Current status (as of August 2026): The Gaussian proportional-regime case at threshold is claimed solved but remains unverified; the conjecture beyond that setting remains open.
Solutions 0
No solutions have been posted yet.