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Sipser–Lautemann theorem

Bounded-error probabilistic polynomial time is contained in the polynomial time hierarchy

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Record originEnglish Wikipedia
Text licenseCC BY-SA 4.0
Source revisionJan 18, 2026
Entity authorityQ7525845
Source-derived summary

In computational complexity theory, the Sipser–Lautemann theorem or Sipser–Gács–Lautemann theorem states that bounded-error probabilistic polynomial (BPP) time is contained in the polynomial time hierarchy, and more specifically Σ2 ∩ Π2.

In 1983, Michael Sipser showed that BPP is contained in the polynomial time hierarchy. Péter Gács showed that BPP is actually contained in Σ2 ∩ Π2. Clemens Lautemann contributed by giving a simple proof of BPP’s membership in Σ2 ∩ Π2, also in 1983. It is conjectured that in fact BPP=P, which is a much stronger statement than the Sipser–Lautemann theorem.

Proof

Here we present the proof by Lautemann. Without loss of generality, a machine M ∈ BPP with error ≤ 2−|x| can be chosen. (All BPP problems can be amplified to reduce the error probability exponentially.) The basic idea of the proof is to define a Σ2 sentence that is equivalent to stating that x is in the language, L, defined by M by using a set of transforms of the random variable inputs.

Since the output of M depends on random input, as well as the input x, it is useful to define which random strings produce the correct output as A(x) = {r | M(x,r) accepts}. The key to the proof is to note that when x ∈ L, A(x) is very large and when x ∉ L, A(x) is very small.

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This entry incorporates text from Sipser–Lautemann theorem” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.