Two-sided parametrix inversion in the bounded-operator algebra #
The paper controls two remainders produced by the left and right parametrix identities. This file isolates the exact Banach-algebra argument those estimates feed:
- if
A Q = 1 + RᵣandQ A = 1 + Rₗ; - and both remainder norms are less than one;
- then
Ais a unit, with inverseQ (1 + Rᵣ)⁻¹ = (1 + Rₗ)⁻¹ Q; - the inverse differs from
Qby at most a geometric remainder.
For the Anderson realization one takes A = 1 - K. The actual
kernel-to-operator work in P-err must still construct the bounded
operator Q and prove the two displayed identities; no such analytic
input is assumed here.
Inverting 1 + R #
The Neumann inverse of 1 + R, written using the project's
canonical inverse of 1 - (-R).
Equations
Instances For
Corrected left and right inverses #
Right inverse candidate obtained from A Q = 1 + Rᵣ.
Equations
- Anderson4D.correctedParametrixRightInverse Q Rright hRright = Q * Anderson4D.oneAddNeumannInverse Rright hRright
Instances For
Left inverse candidate obtained from Q A = 1 + Rₗ.
Equations
- Anderson4D.correctedParametrixLeftInverse Q Rleft hRleft = Anderson4D.oneAddNeumannInverse Rleft hRleft * Q
Instances For
A left and a right inverse of the same operator coincide.
The two error identities and norm bounds produce an honest unit.
Quantitative error #
Anderson specialization #
Two-sided parametrix data for the factorized bounded Anderson
operator 1 - G M.
Instances For
Random good event and Chebyshev estimate #
The paper-shaped good event: both left and right remainder norms are smaller than one half.
Equations
Instances For
First-moment Markov inequality for an operator norm. This is the
form used by paper (3.32), whose hypotheses control
𝔼 (‖R‖ + ‖R'‖) rather than the squares.
Paper-shaped Chebyshev estimate from the expected sum of the two remainder norms.