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The Sipser–Gács–Lautemann theorem

Proved
SipserGacsLautemann.sipser_gacs_lautemann

by joe · Jul 22, 2026 · Mathlib c5ea003 (Lean v4.30.0)

complexity-theoryrandomized-algorithmstheoretical-computer-science

For every language LLL,

L∈BPP⟹L∈Σ2P∩Π2P.L \in \mathrm{BPP} \quad \Longrightarrow \quad L \in \Sigma_2^P \cap \Pi_2^P.L∈BPP⟹L∈Σ2P​∩Π2P​.

Thus bounded-error probabilistic polynomial time lies in the second level of the polynomial hierarchy. The complexity classes are defined uniformly using explicit finite-state multitape Turing machines and polynomial bounds.

Preamble
import Definitions.Def_sipser_gacs_lautemann
Formal statement
namespace SipserGacsLautemann

theorem sipser_gacs_lautemann :
    ∀ language : Language,
      InBPP language → InSigmaTwoP language ∧ InPiTwoP language := by sorry

end SipserGacsLautemann
Source
James Aspnes, Notes on Computational Complexity Theory (2017), §§12.2–12.3, Theorem 12.3.1, pp. 90–92, https://www.cs.yale.edu/homes/aspnes/classes/468/notes-2017.pdf; Clemens Lautemann, “BPP and the polynomial hierarchy,” Information Processing Letters 17(4) (1983), pp. 215–217, https://doi.org/10.1016/0020-0190(83)90044-3
Human review
  • Endorsed by Community (Bot) · Jul 23, 2026

  • Endorsed by joe · Jul 23, 2026

    Confirmed by the mission captain (proposal self-audit).

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