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Smolyak cubature on a finite downward-closed index set
Definition
Fix a dimension . A finite set is downward closed if, whenever and , the index also belongs to ; here is the th coordinate unit vector. In this pair an admissible Smolyak set is a nonempty finite downward- closed that contains .
For a level hierarchy from Nested one-dimensional quadrature levels and differences, define the scalar detail value and the Smolyak cubature functional Each summand is a finite signed weighted sum. Expanding all differences and adding coefficients at equal points gives one finite signed weight for each distinct node in The node-union work count for this direct evaluation convention is , so shared nodes are counted once. A combined weight may be negative or zero; no positivity claim follows from the definition.
Depends on
Used by
- Deterministic node merging for Smolyak cubature Algorithm
- Finite-budget dimension-adaptive Smolyak surplus selection Algorithm
- Smolyak mixed-regularity bounds control chaos coefficient error Corollary
- Absolute summability of a multi-index detail family Definition
- A four-dimensional product exactly integrated on a sparse node union Example
- A signed Simpson-Smolyak weight makes a nonnegative chaos coefficient estimate negative Example
- Rectangular telescoping of tensor details Lemma
- Termination of finite-cap surplus selection Lemma
- Absolute detail reconstruction and omitted-tail error bound Theorem
- Explicit work and error rate for dyadic Simpson Smolyak cubature Theorem
- Smolyak polynomial exactness from actual one-dimensional levels Theorem
Dependency tree · two levels
20 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- T. Gerstner and M. Griebel, Sparse Grids, Encyclopedia of Quantitative Finance, §Numerical integration (standard reference, not scraped)
- N. Zabaras, Sparse Grid Collocation Methods, lecture notes, slides 17–21 (standard reference, not scraped)
- T. Gerstner and M. Griebel, Dimension-Adaptive Tensor-Product Quadrature, §§2–3.1 (standard reference, not scraped)