Time–space inclusions and exponential time
L⊆NL⊆P⊆NP⊆PSPACE=NPSPACE⊆EXP, where EXP=⋃ₖ≥₁DTIME(2ⁿᵏ).
Key knowledge
L⊆NL⊆P⊆NP⊆PSPACE=NPSPACE⊆EXP, where EXP=⋃ₖ≥₁DTIME(2ⁿᵏ). A halting polynomial-space machine has only exponentially many configurations; a logspace configuration graph has polynomial size. P⊊EXP by deterministic time hierarchy.
Conditions and scope
- All classes concern encoded finite decision problems and the same conventional machine model.
- These containments do not declare each adjacent inclusion strict. The strict P/EXP result can use a constructible 2ⁿ-time diagonal language excluding every polynomial bound.
Sources · 3
References
Sources retain their recorded scope. A source link alone does not establish verification of every statement.
Massachusetts Institute of Technology2 sources
- Computational Complexity (2023), Slides 6: Space hierarchy and constructibilityPaul W. Goldberg / University of OxfordCourse notes · PDF
Evidence and review
Lecture 17 slides 3–4 time/space configuration counting and NP⊆PSPACE; Lecture 20 slides 3–5 L/NL⊆P; Oxford slides 6 pages 2–3 include EXP and strict P⊊EXP via time hierarchy.
2026-10-10 · Independent AI editorial review: All241 compact claims, hypotheses, displayed equations/conventions and all596 origin semantic links read; entire241-entry author exact-source inspection matrix and declared limitations reviewed. Prior105 actual inherited Mathematics/Information records read for whole-inventory breadth. Targeted independent primary sections are listed below; this does NOT claim every cited source body or every proof was independently re-read. This is AI reference-content review, not human disciplinary certification, exhaustive textbook reproduction or experimental replication. Receipt: mathematics-information-independent-content-review.1.
Entry details
Permanent link to this entry ↗- Record identity
- info-complexity-class-inclusions
- Revision
- university-core.1
- Structured reference record
- University core expansion