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The binary coding of CNF formulas is injective

Proved
PvsNP.encodeCNF_injective

by korbonits · Sep 8, 2026 · Mathlib 0df444a (Lean v4.33.1)

complexity-theorymillennium-prizenp-completenessp-vs-nppolynomial-timesatisfiabilityturing-machines

The map encodeCNF from CNF formulas (lists of lists of literals (s,i)∈{0,1}×N(s,i) \in \{0,1\} \times \mathbb{N}(s,i)∈{0,1}×N) to binary strings is injective: two formulas with the same code are equal.

This certifies that the coding used to define SAT\mathrm{SAT}SAT and 3-SAT3\text{-}\mathrm{SAT}3-SAT is a coding in Cook's sense ("the set of strings coding YES instances to the decision problem using standard coding methods", p. 5): a binary string is the code of at most one formula, so whether a code lies in SAT\mathrm{SAT}SAT depends only on the formula it codes. The code writes every symbol as a two-bit block, 0b0b0b for a data bit bbb (the sign of a literal, then the binary digits of its variable index, least significant first, without leading zeros), 101010 for the end of a literal and 111111 for the end of a clause, so it can be parsed from left to right; injectivity of the binary representation of natural numbers does the rest.

Formalization Note The statement is Function.Injective encodeCNF. The empty string codes exactly the empty formula and the string 111111 exactly the formula with one empty clause; the block structure means that the parity of positions matters, e.g. the string 0 1 1 00\,1\,1\,00110 is the code of the one-literal clause x0x_0x0​ followed by nothing and is not the concatenation of the blocks 010101 and 101010 read from position one.

Preamble
import Definitions.Def_PvsNP
import Mathlib
Formal statement
namespace PvsNP
theorem encodeCNF_injective : Function.Injective encodeCNF := by sorry
end PvsNP
Source
S. Cook, The P versus NP problem, Clay Mathematics Institute Millennium Prize Problem description (2000), https://www.claymath.org/wp-content/uploads/2022/06/pvsnp.pdf, p. 5, 'the corresponding language is understood to mean the set of strings coding YES instances to the decision problem using standard coding methods' (the coding is the mission's `PvsNP.encodeCNF`)
Read-back

What the Lean code literally says, in plain math · claude-fable-5-1

Read-back: PvsNP.encodeCNF_injective

The statement. The declaration asserts that the map encodeCNF\mathrm{encodeCNF}encodeCNF (defined below) from "CNF formulas" to finite bit-strings is injective; explicitly, for all F1,F2F_1, F_2F1​,F2​ of the type called CNF,

encodeCNF(F1)=encodeCNF(F2)  ⟹  F1=F2.\mathrm{encodeCNF}(F_1) = \mathrm{encodeCNF}(F_2) \;\Longrightarrow\; F_1 = F_2 .encodeCNF(F1​)=encodeCNF(F2​)⟹F1​=F2​.

There are no other hypotheses, no typeclass assumptions and no further quantified variables. The equalities on both sides are equalities of finite lists: two lists are equal exactly when they have the same length and agree entry-by-entry in order. The theorem is stated with the proof omitted (a placeholder), so what is recorded is the claim itself.

What the objects are. Every notion below is a bare list type with no side conditions.

  • A bit-string (Str\mathrm{Str}Str) is a finite list of Booleans b∈{false,true}b \in \{\mathsf{false}, \mathsf{true}\}b∈{false,true}; below I write 000 for false\mathsf{false}false and 111 for true\mathsf{true}true.
  • A literal is an ordered pair (s,v)(s, v)(s,v) with s∈{0,1}s \in \{0,1\}s∈{0,1} a Boolean (a "sign" flag) and v∈N={0,1,2,… }v \in \mathbb{N} = \{0,1,2,\dots\}v∈N={0,1,2,…} a natural number (a "variable index"). Every such pair is a literal; in particular v=0v = 0v=0 is allowed, and both signs are allowed for every vvv.
  • A clause is a finite list of literals [ℓ1,…,ℓm][\ell_1, \dots, \ell_m][ℓ1​,…,ℓm​], m≥0m \ge 0m≥0. The empty clause is allowed; literals may repeat; order matters (the lists [ℓ1,ℓ2][\ell_1,\ell_2][ℓ1​,ℓ2​] and [ℓ2,ℓ1][\ell_2,\ell_1][ℓ2​,ℓ1​] are different clauses).
  • A CNF formula is a finite list of clauses [c1,…,ck][c_1, \dots, c_k][c1​,…,ck​], k≥0k \ge 0k≥0. The empty formula is allowed; clauses may repeat; order matters. Nothing ties the variable indices to any bound, and nothing requires clauses to be non-empty or literals to be distinct.

Consequently the conclusion F1=F2F_1 = F_2F1​=F2​ means: F1F_1F1​ and F2F_2F2​ have the same number of clauses, the iii-th clauses have the same number of literals for every iii, and the jjj-th literal of the iii-th clause has the same sign flag and the same variable index in both.

The binary digits of a natural number. For v∈Nv \in \mathbb{N}v∈N, bits(v)\mathrm{bits}(v)bits(v) denotes the (Mathlib) list of binary digits of vvv, least significant digit first, with no trailing zeros (i.e. no leading zeros in ordinary positional notation). It is determined by

bits(0)=[ ] (the empty list),bits(2n+1)=1::bits(n),bits(2n)=0::bits(n)  (n≠0),\mathrm{bits}(0) = [\,] \ (\text{the empty list}), \qquad \mathrm{bits}(2n+1) = 1 :: \mathrm{bits}(n), \qquad \mathrm{bits}(2n) = 0 :: \mathrm{bits}(n)\ \ (n \ne 0),bits(0)=[] (the empty list),bits(2n+1)=1::bits(n),bits(2n)=0::bits(n)  (n=0),

where b::Lb :: Lb::L means the list LLL with bbb prepended. Thus bits(1)=[1]\mathrm{bits}(1) = [1]bits(1)=[1], bits(2)=[0,1]\mathrm{bits}(2) = [0,1]bits(2)=[0,1], bits(5)=[1,0,1]\mathrm{bits}(5) = [1,0,1]bits(5)=[1,0,1], bits(6)=[0,1,1]\mathrm{bits}(6) = [0,1,1]bits(6)=[0,1,1]; the list has length ⌊log⁡2v⌋+1\lfloor \log_2 v \rfloor + 1⌊log2​v⌋+1 for v≥1v \ge 1v≥1, and length 000 for v=0v = 0v=0. In particular v=0v = 0v=0 is the only number whose digit list is empty, and the last entry of bits(v)\mathrm{bits}(v)bits(v) is 111 whenever v≥1v \ge 1v≥1.

The encoding of a literal. For a literal (s,v)(s, v)(s,v), form the Boolean list s::bits(v)=[s,d0,d1,…,dr−1]s :: \mathrm{bits}(v) = [s, d_0, d_1, \dots, d_{r-1}]s::bits(v)=[s,d0​,d1​,…,dr−1​] (the sign flag followed by the digits of vvv, r=∣bits(v)∣r = |\mathrm{bits}(v)|r=∣bits(v)∣). Replace each entry bbb of this list by the two-bit block [0,b][0, b][0,b] and concatenate, then append the two-bit block [1,0][1, 0][1,0]:

encodeLiteral(s,v)  =  [0,s,  0,d0,  0,d1,  …,  0,dr−1,  1,0].\mathrm{encodeLiteral}(s, v) \;=\; [0, s,\; 0, d_0,\; 0, d_1,\; \dots,\; 0, d_{r-1},\; 1, 0] .encodeLiteral(s,v)=[0,s,0,d0​,0,d1​,…,0,dr−1​,1,0].

This string has length 2(r+1)+2=2r+42(r+1) + 2 = 2r + 42(r+1)+2=2r+4. Examples: encodeLiteral(1,0)=[0,1,1,0]\mathrm{encodeLiteral}(1, 0) = [0,1,1,0]encodeLiteral(1,0)=[0,1,1,0]; encodeLiteral(0,0)=[0,0,1,0]\mathrm{encodeLiteral}(0, 0) = [0,0,1,0]encodeLiteral(0,0)=[0,0,1,0]; encodeLiteral(1,2)=[0,1, 0,0, 0,1, 1,0]\mathrm{encodeLiteral}(1, 2) = [0,1,\,0,0,\,0,1,\,1,0]encodeLiteral(1,2)=[0,1,0,0,0,1,1,0].

The encoding of a clause. For a clause c=[ℓ1,…,ℓm]c = [\ell_1, \dots, \ell_m]c=[ℓ1​,…,ℓm​], concatenate the encodings of its literals in order and append the two-bit block [1,1][1, 1][1,1]:

encodeClause(c)  =  encodeLiteral(ℓ1) ∥ ⋯ ∥ encodeLiteral(ℓm) ∥ [1,1],\mathrm{encodeClause}(c) \;=\; \mathrm{encodeLiteral}(\ell_1) \,\Vert\, \cdots \,\Vert\, \mathrm{encodeLiteral}(\ell_m) \,\Vert\, [1, 1],encodeClause(c)=encodeLiteral(ℓ1​)∥⋯∥encodeLiteral(ℓm​)∥[1,1],

where ∥\Vert∥ is list concatenation. The empty clause encodes to [1,1][1,1][1,1].

The encoding of a formula. For a formula F=[c1,…,ck]F = [c_1, \dots, c_k]F=[c1​,…,ck​], concatenate the encodings of its clauses in order, with no terminator or header:

encodeCNF(F)  =  encodeClause(c1) ∥ ⋯ ∥ encodeClause(ck).\mathrm{encodeCNF}(F) \;=\; \mathrm{encodeClause}(c_1) \,\Vert\, \cdots \,\Vert\, \mathrm{encodeClause}(c_k) .encodeCNF(F)=encodeClause(c1​)∥⋯∥encodeClause(ck​).

The empty formula encodes to the empty bit-string. Every encoded string has even length, and, read in consecutive two-bit blocks, each block is [0,b][0, b][0,b] (a payload bit bbb, either the sign flag or a digit of a variable index), [1,0][1, 0][1,0] (end of a literal) or [1,1][1, 1][1,1] (end of a clause).

Summary of the claim in these terms. For any two finite lists of finite lists of pairs (Boolean, natural number) F1F_1F1​ and F2F_2F2​, if the bit-strings obtained by the above three-level concatenation coincide as lists, then F1F_1F1​ and F2F_2F2​ coincide as lists of lists of pairs. Equivalently, distinct formulas (distinct in number of clauses, order of clauses, multiplicity or order of literals within a clause, or sign flag or index of any literal) always have distinct encodings.

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