Planted Clique Conjectures Are Equivalent
Shuichi Hirahara, Nobutaka Shimizu
摘要
The planted clique conjecture states that no polynomial-time algorithm can find a hidden clique of size k ≪ √ n in an n-vertex Erdős-Rényi random graph with a k-clique planted. In this paper, we prove the equivalence among many (in fact, most) variants of planted clique conjectures, such as search versions with a success probability exponentially close to 1 and with a non-negligible success probability, a worst-case version (the k-clique problem on incompressible graphs), decision versions with small and large success probabilities, and decision versions with adversarially chosen k and binomially distributed k. In particular, we establish the equivalence between the planted clique problem introduced by Jerrum and Kučera and its decision version suggested by Saks in the 1990s. Moreover, the equivalence among decision versions identifies the optimality of a simple edge counting algorithm: By counting the number of edges, one can efficiently distinguish an n-vertex random graph from a random graph with a k-clique planted with probability Θ(k 2 /n) for any k ≤ √ n. We show that for any k, no polynomial-time algorithm can distinguish these two random graphs with probability ≫ k 2 /n if and only if the planted clique conjecture holds. The equivalence among search versions identifies the first one-way function that admits a polynomial-time security-preserving self-reduction from exponentially weak to strong one-way functions. These results reveal a detection-recovery gap in success probabilities for the planted clique problem. We also present another equivalence between the existence of a refutation algorithm for the planted clique problem and an average-case polynomial-time algorithm for the k-clique problem with respect to the Erdős-Rényi random graph.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper6
- Error-Correction of Matrix Multiplication AlgorithmsShuichi Hirahara, Nobutaka ShimizuSTOC 2025 · 被引用 5 次
- Low-degree evidence for computational transition of recovery rate in stochastic block modelJingqiu Ding, Yiding Hua, Lucas Slot, David SteurerNeurIPS 2025 · 被引用 2 次
- On optimal distinguishers for Planted CliqueAnsh Nagda, Prasad RaghavendraFOCS 2025 · 被引用 1 次
- Optimal Random Self-Reductions for All Linear ProblemsShuichi Hirahara, Nobutaka ShimizuSTOC 2026 · 被引用 1 次
- Hardness Amplification beyond Boolean FunctionsNobutaka Shimizu, Kenji YasunagaSTOC 2026
它引用的顶会 Paper5
- Learning in Pessiland via Inductive InferenceShuichi Hirahara, Mikito NanashimaFOCS 2023 · 被引用 11 次
- Almost-Linear Planted Cliques Elude the Metropolis ProcessZongchen Chen, Elchanan Mossel, Ilias ZadikSODA 2023 · 被引用 10 次
- Algorithms Approaching the Threshold for Semi-random Planted CliqueRares-Darius Buhai, Pravesh K. Kothari, David SteurerSTOC 2023 · 被引用 8 次
- Hardness Self-Amplification: Simplified, Optimized, and UnifiedShuichi Hirahara, Nobutaka ShimizuSTOC 2023 · 被引用 4 次
- Algorithmic Decorrelation and Planted Clique in Dependent Random Graphs: The Case of Extra TrianglesGuy Bresler, Chenghao Guo, Yury PolyanskiyFOCS 2023 · 被引用 1 次
相关 Paper
- Semirandom Planted Clique and the Restricted Isometry PropertyJaroslaw Blasiok, Rares-Darius Buhai, Pravesh K. Kothari, David SteurerFOCS 2024 · 被引用 1 次
- Statistical Inference of a Ranked Community in a Directed GraphDmitriy Kunisky, Daniel A. Spielman, Alexander S. Wein, Xifan YuSTOC 2025 · 被引用 2 次
- Using the Planted Clique Conjecture for Cryptography: Public-Key Encryption from Planted Clique and Noisy k-LIN over ExpandersRiddhi Ghosal, Isaac M. Hair, Aayush Jain, Amit SahaiSTOC 2025 · 被引用 1 次
- Sandwiching Random Geometric Graphs and Erdos-Renyi with Applications: Sharp Thresholds, Robust Testing, and EnumerationKiril Bangachev, Guy BreslerSTOC 2025 · 被引用 3 次
- Efficient Algorithms for Semirandom Planted CSPs at the Refutation ThresholdVenkatesan Guruswami, Jun-Ting Hsieh, Pravesh K. Kothari, Peter ManoharFOCS 2023 · 被引用 3 次
