Unselected add-in-u Step 1/2 Cauchy--Schwarz bounds #
Unselected-family contraction inputs and raw √(2δ) estimates for the first
two add-in-u moves in the self-improvement chain.
Raw Cauchy--Schwarz bound for the add-in-u Step 1 difference #
This section proves the raw |Q₀ - Q₁| ≤ √(2δ) bound from
references/ldt-paper/self_improvement.tex, lines 255--277 (eq:move-one).
The proof combines:
addInU_cs_chain_step1_diff_eq(algebraic alignment to commutator-times-PSD),addInU_pointMeasurement_snd_selfConsistency(A^vself-consistency lifted to the(u, v)average),addInU_filtered_sandwiched_tensor_sum_le_one(filtered sandwich-tensor mass is a contraction),Preliminaries.closenessOfInnerProduct_right(the weighted Cauchy--Schwarz inner-product bound fromprop:closeness-of-ip,eq:closeness4).
The analogous Step 2 bound (|Q₁ - Q₂| ≤ √(2δ)) is proved by the same
strategy with closenessOfInnerProduct_left and the leftTensor-sandwiched
analogue of the Step 1 contraction lemma.
Raw |Q₀ - Q₁| ≤ √(2δ) bound for the add-in-u Step 1 Cauchy--Schwarz move.
Proves the paper's eq:move-one bound from
references/ldt-paper/self_improvement.tex, lines 255--277, as a completed
construction. The proof combines the algebraic alignment
addInU_cs_chain_step1_diff_eq with the weighted Cauchy--Schwarz inner-product
bound Preliminaries.closenessOfInnerProduct_right, the A^v self-consistency
input via addInU_pointMeasurement_snd_selfConsistency, and the
filtered-tensor contraction addInU_filtered_sandwiched_tensor_sum_le_one.
The hypothesis is the bipartite SSC for the unlifted point measurement on the
single-point distribution; the lifted 2δ bound is constructed inside the
proof via addInU_pointMeasurement_snd_selfConsistency.
Raw |Q₁ - Q₂| ≤ √(2δ) bound for the add-in-u Step 2 Cauchy--Schwarz move.
Proves the paper's eq:move-another bound from
references/ldt-paper/self_improvement.tex, lines 279--297, as a completed
construction. The proof combines the algebraic alignment
addInU_cs_chain_step2_diff_eq with the weighted Cauchy--Schwarz inner-product
bound Preliminaries.closenessOfInnerProduct_left, the A^v self-consistency
input via addInU_pointMeasurement_snd_selfConsistency, and the
filtered-tensor contraction addInU_filtered_sandwiched_tensor_sum_le_one.