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Bounded-error nearest-neighbour matchgate languages lie in deterministic P

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QAlgorithms.Papers.Independent.Intakethird100.P77.nearestBoundedError_inP

by Gohan · Nov 1, 2026 · Mathlib 0df444a (Lean v4.33.1)

prove2quantum

For each input length, fix one effectively uniform nearest-neighbour matchgate circuit, with enough wires for the computational-basis input and zero workspace, and one existing output wire. Every local parity block is unitary and the even and odd determinants agree. Suppose the output bit is correct with probability at least 2/32/32/3 on every input. Then the decided language belongs to deterministic polynomial time:

Vn.n.bounded⊆P.\mathcal V^{\mathrm{bounded}}_{\mathrm{n.n.}}\subseteq\mathrm P.Vn.n.bounded​⊆P.

Here the left class is exactly the class of languages admitted by those circuit families, and P\mathrm PP is defined by a characteristic function computed by an actual polynomial-time finite Turing machine. This is the bounded-error specialization of strong simulation, using only constant precision.

Preamble
import Definitions.Def_QAlgorithms_Papers_Independent_Intakethird100_P77
Formal statement
noncomputable section

namespace QAlgorithms.Papers.Independent.Intakethird100.P77

open QAlgorithms

open QAlgorithms.Complexity (Str)

open QAlgorithms.Papers.Independent.Advance50.P19 (Major CARSystem)

open QAlgorithms.Papers.Independent.Information100.P32 (Op)

open scoped BigOperators Matrix ComplexConjugate

attribute [local instance] Classical.propDecidable Classical.decEq

/-- PDF p.3: bounded-error nearest-neighbour matchgate decision languages are
in deterministic P. The class definitions fix one circuit per input length,
computational-basis inputs, uniform finite descriptions and the 2/3 gap. -/
theorem nearestBoundedError_inP :
    {L : Set Str | InBoundedMatchgate 1 L} ⊆ {L : Set Str | InP L} := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P77

end
Source
Matchgates and classical simulation of quantum circuits, arXiv:0804.4050v2, PDF p. 3, Section 1 consequence: bounded-error nearest-neighbour matchgate decision problems lie in P
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What the Lean code literally says, in plain math · gpt-6.1-sol

For every language LLL of finite Boolean strings, suppose there exists a family assigning widths w(s)w(s)w(s) and finite gate lists to all strings sss, with output wires o(n)<w(true n)o(n)<w(\mathrm{true}^{\,n})o(n)<w(truen) and n≤w(true n)n\le w(\mathrm{true}^{\,n})n≤w(truen) for every n∈Nn\in\mathbb Nn∈N. Each gate consists of unitary Boolean-indexed complex 2×22\times22×2 matrices Ag,BgA_g,B_gAg​,Bg​ and an injective ordered pair of wires vgv_gvg​; at unary strings, require det⁡Ag=det⁡Bg\det A_g=\det B_gdetAg​=detBg​ and ∣vg(0)−vg(1)∣≤1|v_g(0)-v_g(1)|\le1∣vg​(0)−vg​(1)∣≤1. Its local matrix uses AgA_gAg​ on the even-parity block and BgB_gBg​ on the odd-parity block, each indexed by the first bit, is zero between blocks, and leaves other wires unchanged. Require the following effectiveness conditions: putting u(j)=true ju(j)=\mathrm{true}^{\,j}u(j)=truej and T([a1,…,ak])=∥j(u(∣aj∣) false aj)T([a_1,\ldots,a_k])=\big\Vert_j(u(|a_j|)\,\mathrm{false}\,a_j)T([a1​,…,ak​])=​j​(u(∣aj​∣)falseaj​), the functions s↦T([u(w(s)),u(gate count)]+ ⁣ ⁣+[T([u(vg(0)),u(vg(1))]):g in order])s\mapsto T([u(w(s)),u(\text{gate count})]\mathbin{+\!\!+}[T([u(v_g(0)),u(v_g(1))]):g\text{ in order}])s↦T([u(w(s)),u(gate count)]++[T([u(vg​(0)),u(vg​(1))]):g in order]) and x↦u(o(∣x∣))x\mapsto u(o(|x|))x↦u(o(∣x∣)) are polynomial-time computable, and there is a polynomial-time function returning approximations within 2−m2^{-m}2−m to each real or imaginary gate-matrix entry at input T([s,u(j),u(m),[b]])T([s,u(j),u(m),[b]])T([s,u(j),u(m),[b]]). Here jjj indexes the list of entries of AgA_gAg​ followed by BgB_gBg​, in gate order and entry order (0,0),(0,1),(1,0),(1,1)(0,0),(0,1),(1,0),(1,1)(0,0),(0,1),(1,0),(1,1); b=falseb=\mathrm{false}b=false selects the real part and true the imaginary part; and the output is read as its binary tail divided by 2m2^m2m, negated when its first bit is true, with missing bits zero. Let UnU_nUn​ be the reverse-order product of embedded gates at true n\mathrm{true}^{\,n}truen, with the empty product the identity, and axa_xax​ the input xxx padded with false to that width. Suppose, for every xxx, the sum ∑z: zo(∣x∣)=true∣(U∣x∣)z,ax∣2\sum_{z:\,z_{o(|x|)}=\mathrm{true}}|(U_{|x|})_{z,a_x}|^2∑z:zo(∣x∣)​=true​∣(U∣x∣​)z,ax​​∣2 is at least 2/32/32/3 when x∈Lx\in Lx∈L and at most 1/31/31/3 when x∉Lx\notin Lx∈/L. Then there exists a polynomial-time function on Boolean strings returning exactly [true] for members of LLL and exactly [false] for nonmembers. Every polynomial-time requirement here means computability by a TM2 Turing machine with identity input and output encodings; all conditions include the empty input.

Human review
  • Endorsed by Shuze Chen · Nov 1, 2026

    Confirmed by the moderator at approval.

  • Endorsed by Gohan · Nov 1, 2026

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

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