The Minimum Formula Size Problem is (ETH) Hard
Rahul Ilango
2021年份
5被引次数
3顶会引用
摘要
A longstanding open question is whether the Minimum Circuit Size Problem (MCSP) is NP-complete. In fact, even determining whether MCSP has a search-to-decision reduction has been open for over twenty years. We show that, under the Exponential Time Hypothesis, the Minimum (DeMorgan) Formula Size Problem, MFSP, is not in P. Building on this, we show that MFSP has a polynomial-time (exact) search-to-decision reduction, a result that does not relativize. Our main technique relates the formula complexity of a partial function with the formula complexity of an associated total function and is proved using the “leaf weighting” technique of Buchfuhrer and Umans.
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引用它的顶会 Paper3
- NP-Hardness of Learning Programs and Partial MCSPShuichi HiraharaFOCS 2022 · 被引用 24 次
- SAT Reduces to the Minimum Circuit Size Problem with a Random OracleRahul IlangoFOCS 2023 · 被引用 7 次
- NP-hardness of the Minimum Circuit Size Problem from Well-Studied AssumptionsShuichi Hirahara, Rahul IlangoFOCS 2025 · 被引用 1 次
它引用的顶会 Paper3
- On One-way Functions and Kolmogorov ComplexityYanyi Liu, Rafael PassFOCS 2020 · 被引用 39 次
- Cryptography from sublinear-time average-case hardness of time-bounded Kolmogorov complexityYanyi Liu, Rafael PassSTOC 2021 · 被引用 14 次
- Constant Depth Formula and Partial Function Versions of MCSP are HardRahul IlangoFOCS 2020 · 被引用 10 次
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