[#P3130] Polynomial-time recovery of planted cliques below the square-root scale
Problem. Fix \(\delta>0\). Given a graph sampled by first drawing \(G(n,1/2)\) and then planting a uniformly random clique of size \(k=\lceil n^{1/2-\delta}\rceil\), is there a randomized polynomial-time algorithm that recovers the planted vertex set with probability tending to one?
1Context
Known frontier: Polynomial-time recovery works at k on the order of √n, while low-degree, sum-of-squares, and several algorithm families have lower bounds below it. Open boundary: No unrestricted polynomial-time algorithm or unconditional average-case lower bound is known for k=n^{1/2−δ}.
2Problem setup
Definition 1 (planted clique model). G(n,1/2) with every missing edge inside a random k-set added.
Definition 2 (recovery). Output the exact planted vertex set with probability 1−o(1).
Remark 1. Information-theoretic recovery is possible near logarithmic size, while known general polynomial-time methods require roughly the square-root scale. The packet fixes one constant δ to avoid mixing regimes.
3What counts as a solution
- For some fixed δ>0, give and prove a polynomial-time exact-recovery algorithm.
- Or prove polynomial-time recovery impossible under an explicit unconditional average-case model, which may require a new lower-bound framework.
1Status
Current status (Current status and exact unresolved remainder). OPEN as checked on 2026-08-01. Strongest checked neighboring result: Polynomial-time recovery works at k on the order of √n, while low-degree, SoS, and several algorithm families have lower bounds below it. Exact unresolved remainder: No unrestricted polynomial-time algorithm or unconditional average-case lower bound is known for k=n^{1/2−δ}.[1][2]
1Records
Notes and companion material
Original intake status. OPEN as checked on 2026-08-01. Strongest checked neighboring result: Polynomial-time recovery works at k on the order of √n, while low-degree, SoS, and several algorithm families have lower bounds below it. Exact unresolved remainder: No unrestricted polynomial-time algorithm or unconditional average-case lower bound is known for k=n^{1/2−δ}.
- Equivalent-formulation queries: planted clique polynomial time below sqrt n current 2026; planted clique n one half minus delta recovery open
- Strongest checked neighboring result: Polynomial-time recovery works at k on the order of √n, while low-degree, SoS, and several algorithm families have lower bounds below it.
- Exact unresolved remainder: No unrestricted polynomial-time algorithm or unconditional average-case lower bound is known for k=n^{1/2−δ}.
How the 4 records connect
ProblemPolynomial-time recovery of planted cliques below the square-root scale
2See also
- Is VP equal to VNP?theoretical computer science
- Is there a truly subcubic algorithm for weighted APSP?theoretical computer science
- Strong Exponential Time Hypothesistheoretical computer science
How to cite
TheoremDB contributors, “Polynomial-time recovery of planted cliques below the square-root scale,” TheoremDB research memory, snapshot of August 1, 2026. https://theoremdb.org/statements/planted-clique-below-square-rootThis page as plain text: planted-clique-below-square-root.md
This problem includes 4 records joined by 3 typed links, sourced from arxiv.org[1], current as of August 1, 2026.
1References
- Packet source. R. Meka, A. Potechin, and A. Wigderson, Sum-of-squares lower bounds for planted clique, STOC 2015. main SoS lower bounds. ↗preprint · primary source · arXiv:1503.06447, checked 2026-08-01 · checked 2026-08-01Source use: original summary.Shows strong lower bounds for a major algorithmic hierarchy below the square-root regime.Also cited at R. Meka, A. Potechin, and A. Wigderson, Sum-of-squares lower bounds for planted clique, STOC 2015. main SoS lower bounds.Source used to assess the problem's recorded status.For Polynomial-time recovery of planted cliques below the square-root scale: This is the dated publication status for the canonical target Polynomial-time recovery of planted cliques below the square-root scale.Source named by the research packet.
- Reza Gheissari, Aukosh Jagannath, and Yiming Xu, “Finding Planted Cliques Using Gradient Descent”. SIAM Journal on Mathematics of Data Science 7(2) (2025), 643-669. DOI 10.1137/24M1680489. abstract and main results. ↗journal article · primary source · checked 2026-08-01Source use: original summary.States the continuing square-root algorithmic threshold and analyzes another broad method.Source used to assess the problem's recorded status.For Polynomial-time recovery of planted cliques below the square-root scale: States the continuing square-root algorithmic threshold and analyzes another broad method.
Original TheoremDB editorial statement and source synthesis; external works are used for citation only.