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Fixed-degree Clifford-intertwined Gaussian circuits and their boundary interpretation

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QAlgorithms.Papers.Independent.Intakethird100.P77.cliffordIntertwining_strongSimulation

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

prove2quantum

For each circuit instance sss, choose a fixed Clifford unitary TsT_sTs​ normalizing the full phase-inclusive Pauli group and define ci′=Ts†ciTsc'_i=T_s^\dagger c_iT_sci′​=Ts†​ci​Ts​ from the Jordan–Wigner generators. Select one existing measured wire ksk_sks​ and supply a canonical polynomial for ZksZ_{k_s}Zks​​ in the ci′c'_ici′​ of degree at most one fixed ddd. Supply effective product factors of all ci′c'_ici′​, real skew Gaussian coefficients, normalized product inputs and the selected observable coefficients. All structural and numerical description costs are charged. Other wires need no bounded-degree polynomial representation. The resulting circuit has one deterministic polynomial-time simulator for its selected bit probabilities to error 2−m2^{-m}2−m.

Writing Unew=Ts†UoldTsU_{\rm new}=T_s^\dagger U_{\rm old}T_sUnew​=Ts†​Uold​Ts​ and ψs\psi_sψs​ for the product input, the exact boundary interpretation is

⟨Unewψs,ZksUnewψs⟩=⟨UoldTsψs,(TsZksTs†)UoldTsψs⟩.\langle U_{\rm new}\psi_s,Z_{k_s}U_{\rm new}\psi_s\rangle=\langle U_{\rm old}T_s\psi_s,(T_sZ_{k_s}T_s^\dagger)U_{\rm old}T_s\psi_s\rangle.⟨Unew​ψs​,Zks​​Unew​ψs​⟩=⟨Uold​Ts​ψs​,(Ts​Zks​​Ts†​)Uold​Ts​ψs​⟩.

The Clifford is fixed across all gates in an instance; it need not be Gaussian or local. The transformed input can be entangled, and the transformed observable can involve many wires.

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 pp.12--13: constant-degree Clifford intertwining gives strong simulation
for the selected output and the exact boundary interpretation. The old input
is T psi and the old observable T Z_k T† at that output. Other output wires need
not satisfy the degree condition; T is not required to be Gaussian or local. -/
theorem cliffordIntertwining_strongSimulation (d : ℕ) (F : IntertwinedFamily)
    (I : ProductInputs F.base.width) (hF : F.Effective)
    (hI : EffectiveNumbers I.data)
    (hdegree : ∀ s, (F.observable s).DegreeLE d) :
    SelectedStrongSimulation (fun s b =>
      singleWireProbability
        (gaussianCircuit (conjugatedGenerators (F.T s) (jordanWigner (F.base.width s)))
          (F.base.gates s)) (prodState (I.factor s)) (F.measured s) b) ∧
    (∀ s,
      outputExpectation
          (gaussianCircuit (conjugatedGenerators (F.T s) (jordanWigner (F.base.width s)))
            (F.base.gates s)) (prodState (I.factor s)) (zOperator (F.measured s)) =
        outputExpectation (gaussianCircuit (jordanWigner (F.base.width s)) (F.base.gates s))
          (act (F.T s : Op (Qubits (F.base.width s))) (prodState (I.factor s)))
          ((F.T s : Op (Qubits (F.base.width s))) * zOperator (F.measured s) *
            star (F.T s : Op (Qubits (F.base.width s))))) := by sorry

end QAlgorithms.Papers.Independent.Intakethird100.P77

end
Source
Matchgates and classical simulation of quantum circuits, arXiv:0804.4050v2, PDF p. 13, Section 6: Clifford-conjugated Gaussian simulation and boundary interpretation
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What the Lean code literally says, in plain math · gpt-6.1-sol

For every natural number ddd, every intertwined family FFF, and every collection of normalized single-qubit vectors ϕs,k∈C2\phi_{s,k}\in\mathbb C^2ϕs,k​∈C2, indexed by finite Boolean strings sss and wires k<n(s)k<n(s)k<n(s) of its base width, assume that FFF’s structural code is polynomial-time computable, its numerical data is effectively approximable, the input-factor data is effectively approximable, and every stored observable word has length at most ddd. The structural code is the tuple of the base code tuple⁡[1n(s),1L(s)]\operatorname{tuple}[1^{n(s)},1^{L(s)}]tuple[1n(s),1L(s)], the unary measured-wire index, and the nested tuple of unary generator indices in each stored observable word. The numerical data lists base gate-matrix entries, then the four entries of each conjugated-generator factor, then observable coefficients; the input data lists each ϕs,k(false)\phi_{s,k}(\mathrm{false})ϕs,k​(false) followed by ϕs,k(true)\phi_{s,k}(\mathrm{true})ϕs,k​(true). Effective approximability of either numerical list D(s)D(s)D(s) means that there exists a polynomial-time string function aaa such that, for every position j<∣D(s)∣j<|D(s)|j<∣D(s)∣, precision m∈Nm\in\mathbb Nm∈N, and Boolean bbb,

∣dyad⁡m ⁣(a(tuple⁡[s,1j,1m,[b]]))−{Im⁡D(s)j,b=true,Re⁡D(s)j,b=false∣≤2−m.\left|\operatorname{dyad}_m\!\left(a(\operatorname{tuple}[s,1^j,1^m,[b]])\right) -\begin{cases}\operatorname{Im}D(s)_j,&b=\mathrm{true},\\ \operatorname{Re}D(s)_j,&b=\mathrm{false} \end{cases}\right|\le2^{-m}.​dyadm​(a(tuple[s,1j,1m,[b]]))−{ImD(s)j​,ReD(s)j​,​b=true,b=false​​≤2−m.

Tuple encoding prefixes each constituent string with its unary length and a false bit; dyad⁡m\operatorname{dyad}_mdyadm​ interprets the first output bit as a negative-sign flag and the remaining bits as a binary magnitude divided by 2m2^m2m, with an empty output representing zero. For each sss, put n=n(s)n=n(s)n=n(s), let q<nq<nq<n be its measured wire, and define cic_ici​, i<2ni<2ni<2n, as tensor products of Z=diag⁡(1,−1)Z=\operatorname{diag}(1,-1)Z=diag(1,−1) on wires preceding ⌊i/2⌋\lfloor i/2\rfloor⌊i/2⌋, X=(0110)X=\begin{pmatrix}0&1\\1&0\end{pmatrix}X=(01​10​) or Y=(0−ii0)Y=\begin{pmatrix}0&-\mathrm i\\\mathrm i&0\end{pmatrix}Y=(0i​−i0​) on that wire according as iii is even or odd, and identity afterward. The family supplies a unitary TsT_sTs​ normalizing the subgroup generated by all ia⨂k<nPk\mathrm i^a\bigotimes_{k<n}P_kia⨂k<n​Pk​, with a∈{0,1,2,3}a\in\{0,1,2,3\}a∈{0,1,2,3} and Pk∈{I,X,Y,Z}P_k\in\{I,X,Y,Z\}Pk​∈{I,X,Y,Z}. Its conjugated generators ci′=Ts†ciTsc'_i=T_s^\dagger c_iT_sci′​=Ts†​ci​Ts​ have the supplied tensor factorizations, and its distinct increasing observable words satisfy ∑(w,α)αcw1′⋯cw∣w∣′=Zq\sum_{(w,\alpha)}\alpha c'_{w_1}\cdots c'_{w_{|w|}}=Z_q∑(w,α)​αcw1​′​⋯cw∣w∣​′​=Zq​, where ZqZ_qZq​ applies ZZZ on wire qqq and identity elsewhere. For any generator collection a=(ai)a=(a_i)a=(ai​), define

Hh(a)=i∑i,j<2ni≠jhijaiaj,U(a)=eiHhL(a)⋯eiHh1(a),Ψs(x)=∏k<nϕs,k(xk),H_h(a)=\mathrm i\sum_{\substack{i,j<2n\\i\ne j}}h_{ij}a_ia_j,\qquad U(a)=e^{\mathrm iH_{h_L}(a)}\cdots e^{\mathrm iH_{h_1}(a)},\qquad \Psi_s(x)=\prod_{k<n}\phi_{s,k}(x_k),Hh​(a)=ii,j<2ni=j​∑​hij​ai​aj​,U(a)=eiHhL​​(a)⋯eiHh1​​(a),Ψs​(x)=k<n∏​ϕs,k​(xk​),

using the stored real skew-symmetric gate matrices h1,…,hLh_1,\ldots,h_Lh1​,…,hL​. Then there exists a polynomial-time string function fff such that, for every sss, every m∈Nm\in\mathbb Nm∈N, and both Booleans bbb,

∣dyad⁡m ⁣(f(tuple⁡[s,1m,[b]]))−∑x∈{0,1}n(s)xq=b∣(U(c′)Ψs)(x)∣2∣≤2−m.\left|\operatorname{dyad}_m\!\left(f(\operatorname{tuple}[s,1^m,[b]])\right) -\sum_{\substack{x\in\{0,1\}^{n(s)}\\x_q=b}}|(U(c')\Psi_s)(x)|^2\right|\le2^{-m}.​dyadm​(f(tuple[s,1m,[b]]))−x∈{0,1}n(s)xq​=b​∑​∣(U(c′)Ψs​)(x)∣2​≤2−m.

Moreover, for every sss, the following equality of complex inner products holds:

⟨U(c′)Ψs, Zq U(c′)Ψs⟩=⟨U(c)(TsΨs), (TsZqTs†) U(c)(TsΨs)⟩.\big\langle U(c')\Psi_s,\ Z_q\,U(c')\Psi_s\big\rangle = \big\langle U(c)(T_s\Psi_s),\ (T_sZ_qT_s^\dagger)\,U(c)(T_s\Psi_s)\big\rangle.⟨U(c′)Ψs​, Zq​U(c′)Ψs​⟩=⟨U(c)(Ts​Ψs​), (Ts​Zq​Ts†​)U(c)(Ts​Ψs​)⟩.

Here the inner product is conjugate-linear in its first argument. The statement includes d=0d=0d=0, empty observable words, empty gate lists, and m=0m=0m=0; empty products are identities, and the measured wire requires n(s)>0n(s)>0n(s)>0.

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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