How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Immerman-Szelepcsényi theorem: NL equals coNL
Statement
Moreover, in the same read-only-input model, if is work-space constructible and , then .
Facts & Assumptions
Given: a fixed nondeterministic decider for , where has the stated constructibility and logarithmic floor.
The inductive-counting algorithm certifies nonreachability in an -vertex digraph using work space and a polynomial-length read-once certificate (Nonreachability has an inductive counting certificate).
Proof
Fix an integer bounding 's visited work cells by for all sufficiently large ; handle the finitely many exceptional input lengths separately. Run the work-space constructor for on a virtual unary input of length ; an address on the actual endmarked input provides this virtual input in space. A configuration records the fixed finite control, work symbols, work-head positions, and the endmarked input-head position. Since is fixed, choose a fixed constant so that every configuration within the cap has a padded binary description of length .
Use all binary strings as candidate vertex names and add a fresh target . Invalid configuration names are isolated. Between valid names put an edge exactly for a legal transition of on the actual input within the work cap, and add an edge from each accepting configuration to . The source is the actual initial configuration. Enumerating names, validating them, checking a transition, and recognizing an accepting state all take space by direct scans of the fixed-length records and of . Thus a path to exists exactly when accepts . This constructs a well-defined finite graph for every input string , without querying validity of any externally supplied STCON encoding.
Run the algorithm of [L2] on this implicit graph, with . Its implementation only enumerates vertices and requests adjacency tests while checking bounded paths and successive reachable counts. Supply each such test by step 2.1. The previous layer's verified count, the current layer count, the finitely many vertex/loop indices, and one bounded path at a time have bits. The certificate checks are sequential nested loops of fixed depth, not a recursion stack through all layers. All loop and path lengths are bounded by polynomials in , and each guessed certificate field has bounded length, so every branch halts. Nondeterministic choices generate the read-once certificate as needed; it is never stored. Soundness and completeness of [L2] now give an -space decider for .
This proves closure of under complement. By the definition of the co-class, closure implies equality with its co-class, since complementing twice recovers the original language. Finally is work-space constructible: count the unary input in binary and compute the bit length, treating a power of two separately for the ceiling. This uses work cells. Its class is exactly NL under The classes L and NL, so the same equality specializes to .
Depends on
Used by
Dependency tree · two levels
8 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Arora and Barak, Computational Complexity, Theorem 3.18 (standard reference, not scraped)
- Harvard CS 221, Lecture 5, §3 (standard reference, not scraped)