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Smolyak mixed-regularity bounds control chaos coefficient error
Statement
Assume is uniform product probability on , so its integral is in Explicit work and error rate for dyadic Simpson Smolyak cubature. Let be an admissible cutoff vector for this law and let be a finite subset of its admissible degree box, with basis from Finite orthonormal polynomial tensor basis. Let be that theorem's dyadic Simpson Smolyak rule, with . Let be real and fix a representative defined at every node of . For every , suppose the coefficient integrand has the continuous mixed fourth derivatives and finite bounds required by Mixed-derivative bounds for dyadic Simpson details. Define with the constants and mixed norm of the sparse-grid theorem. Then The error-split theorem consequently bounds the L2 coefficient contribution by the right-hand side; this claim is restricted to the stated cube law and mixed regularity.
Facts & Assumptions
Given: Uniform product measure on , a finite chaos basis, and the stated mixed-derivative hypotheses for each coefficient integrand.
Explicit work and error rate for dyadic Simpson Smolyak cubature bounds each scalar Smolyak integration error by under its displayed hypotheses.
Mixed-derivative bounds for dyadic Simpson details supplies the exact mixed-derivative and endpoint convention required by [F1].
Smolyak cubature on a finite downward-closed index set defines as a finite cubature functional.
Projection and quadrature errors split in L2 identifies the Euclidean coefficient-error norm as the L2 quadrature contribution.
Proof
For each , apply [F1] to . Its assumptions are exactly the mixed-derivative bounds and cube domain in Given, with [F2] supplying the theorem's specified mixed norm. Thus . Since represents , the integral equals by the uniform product law.
Square the finitely many nonnegative inequalities from step 1.1, sum over , and take square roots; monotonicity of the square root gives the stated Euclidean bound.
Apply [F4] with these coefficient errors. Its exact orthogonal error decomposition leaves the projection residual unchanged and adds the bounded Euclidean coefficient term, which proves the final assertion.
Depends on
- Projection and quadrature errors split in L2
- Quadrature estimates of polynomial-chaos coefficients
- Finite orthonormal polynomial tensor basis
- Smolyak cubature on a finite downward-closed index set
- Explicit work and error rate for dyadic Simpson Smolyak cubature
- Mixed-derivative bounds for dyadic Simpson details
Used by
Nothing in the library uses this result yet.
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Sources
- Dongbin Xiu, Fast Numerical Methods for Stochastic Computations, §§4–5 (standard reference, not scraped)
- Bruno Sudret, Polynomial Chaos Expansions and Stochastic Finite Element Methods, §§3.4.2–3.4.3 (standard reference, not scraped)