Switch-sandwich main: completeness estimate #
prop:switch-sandwich assembled from the left and right transfer steps, and
prop:completeness-transfer-projective-P: the counterpart of
MIPRE/Background/LIDT/MIPStarRE/LDT/Preliminaries/SwitchSandwichMain/Completeness.lean in the
port of planning/c6b-plan.md (milestone M3, section "Port conventions").
switchSandwich takes a symmetric model S : SymModel š K in place of the state
Ļ : QuantumState (ι à ι). The completeness transfer is about a state on a single space
(Ļ : QuantumState ι), so completenessTransfer_core and completenessTransferProjectiveP
take a vector state V : VecState K (a symmetric model is accepted through its coercion) and
families of joint operators in K āL[ā] K, as CompTransferStmt does in
Co/Preliminaries/Defs.lean. All three drop the vendored normalization hypothesis
hĻ : Ļ.IsNormalized, a theorem of the vector state (ev_one_of_isNormalized); the
subprobability hypothesis hš stays.
The proofs are the vendored ones. Per question, the mass gap of A against the projective P
is at most the diagonal gap āā ev(Pā²) - āā ev(Aā²) (projSubMeas_diagMass_eq_mass,
subMeas_diagMass_le_mass), which the two overlap gaps (question_overlap_gap_left,
question_overlap_gap_right) bound by 2 ā(qSDD A P); the average of the square roots is at
most the square root of the average (avgOver_abs_le_sqrt_of_pointwise).
Not ported #
Every declaration of the vendored file has a counterpart here.
References #
In LionSR/MIPStarRE at commit 507e8122, not in this repository:
references/ldt-paper/preliminaries.tex,prop:switch-sandwich,prop:completeness-transfer-projective-P
prop:switch-sandwich.
The paper proof assumes a normalized state and a probability distribution (weights summing to
⤠1). Normalization is a theorem of the model; the distribution hypothesis is hš.
Core of prop:completeness-transfer-projective-P: if A ā_ε P with P projective, the
mass of A is at least that of P minus 2 āε.
prop:completeness-transfer-projective-P.
The paper proof uses a normalized state and a probability distribution. Normalization is a
theorem of the vector state; the distribution hypothesis is hš.