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.
Classical NP-Completeness Reductions: Examples and Counterexamples
1 · Prerequisites
- Classical NP-Completeness Reductions
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Countability and Uncountability
- Finite Counting, Factorials and Binomial Coefficients
- Formal Languages, Encodings, and Decision Problems
- Foundations of the Real Numbers for Analysis
- Graphs, Walks and Connectivity
- Linear Recurrences and Rational Generating Functions
- P, NP, coNP, and Polynomial Reductions
- Relations, Functions, and Quotients
- Resource Bounds and Machine Invariance
- Sequences and Limits
- The ZFC Axioms and the Basic Set Constructions
- Turing Machines, Configurations, and Computation
2 · Summary
These examples work through three of the page's recurring patterns on small instances. The first writes down an explicit clause-cluster graph and clique, the second traces the NAE-to-colouring construction on a toy formula, and the counterexample shows why a yes-preserving map can still fail to be a valid many-one reduction.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
A worked clause-cluster instance witnessing that CLIQUE is NP-complete
Example
Consider the formula
Form a graph with one vertex for each of the nine displayed literal occurrences. Join two vertices exactly when they come from different clauses and their literal labels are not complementary.
Facts & Assumptions
Given: The above -CNF formula .
A CLIQUE instance asks for pairwise adjacent vertices, by Clique, independent set, and vertex cover decision problems.
The reduction theorem states that the clause-occurrence construction gives a CLIQUE yes-instance exactly when the input formula is satisfiable, by 3SAT polynomial-time many-one reduces to CLIQUE.
CLIQUE is NP-complete, by CLIQUE is NP-complete.
Verification
In the graph defined in the example, choose the vertices labeled by the literal in the first, second, and third clauses. These occurrences come from different clauses and no two are complementary, so every pair is adjacent. Thus they form a clique of size .
The assignment satisfies all three clauses of , so the explicitly constructed clique agrees with the iff asserted by [L1]. This concrete yes-instance therefore illustrates the reduction theorem and, through [L2], the NP-completeness conclusion for CLIQUE.
A small 3SAT instance and its three-colourability gadget graph
Example
Take the one-clause formula The reduction introduces the global variable and one fresh splitter variable , producing the NAE clauses
Facts & Assumptions
Given: The satisfying assignment , , , together with and .
A proper three-colouring uses the colours and forbids equal colours on adjacent vertices, by The three-colourability decision problem.
The reduction to -COLORABILITY first converts a -CNF clause to NAE clauses and then builds one variable triangle per variable and one clause triangle per NAE clause, by 3SAT polynomial-time many-one reduces to 3-COLORABILITY.
Verification
Under the given assignment, both NAE clauses are satisfied: is not all equal, and is not all equal.
Define the graph directly: take a distinguished vertex ; for each variable add the triangle ; for each of the two ordered NAE clauses add a triangle of three position vertices and join its th vertex to the literal vertex in position . Colour by . In the variable triangles, colour each literal vertex by its Boolean value, so receive , receive , receive , receive , and receive .
For the clause triangle for , the literals and have different truth values, so colour their two position vertices by the opposite colours and , and colour the remaining position vertex by . Do the same for . Every clause triangle then uses , and each clause vertex differs from the colour of its adjacent literal vertex. Thus the explicitly defined graph is properly three-coloured.
This worked instance shows concretely how the theorem's NAE assignment is converted into a proper three-colouring.
A forward-only mapping that is not a correct many-one reduction
Statement refuted
A gadget reduction is correct as soon as every yes-instance maps to a yes-instance.
Facts & Assumptions
Given: The constant map sending every -CNF formula to the CLIQUE instance .
The graph has one vertex, so is a yes-instance of CLIQUE, by Clique, independent set, and vertex cover decision problems.
A polynomial-time many-one reduction requires an iff between source and target membership, by Polynomial-time many-one reductions.
The false slogan being refuted is recorded in A gadget reduction is correct as soon as every yes-instance maps to a yes-instance.
Counterexample
The constant map in the given data is total and polynomial-time, and every satisfiable -CNF formula is sent to the yes-instance . So it preserves yes-instances in exactly the way promised by [L2].
Consider the unsatisfiable formula . It is still mapped to , which is a yes-instance by [F1]. Thus the reverse implication in [L1] fails, so the map is not a correct many-one reduction.
This explicit map therefore refutes the slogan [L2].