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Discrepancy and Numerical Integration on Metric Measure Spaces
- Publication Year :
- 2019
- Publisher :
- Springer New York LLC, 2019.
-
Abstract
- We study here the error of numerical integration on metric measure spaces adapted to a decomposition of the space into disjoint subsets. We consider both the error for a single given function, and the worst case error for all functions in a given class of potentials. The main tools are the classical Marcinkiewicz–Zygmund inequality and ad hoc definitions of function spaces on metric measure spaces. The same techniques are used to prove the existence of point distributions in metric measure spaces with small $$L^p$$ discrepancy with respect to certain classes of subsets, for example, metric balls.
- Subjects :
- Function space
Metric measure space
Disjoint sets
Space (mathematics)
01 natural sciences
Measure (mathematics)
Metric measure spaces
Mathematics - Analysis of PDEs
Settore MAT/05 - Analisi Matematica
0103 physical sciences
FOS: Mathematics
Point (geometry)
Number Theory (math.NT)
Mathematics - Numerical Analysis
65D30, 11K38
0101 mathematics
Discrepancy
Mathematics
Discrete mathematics
Mathematics - Number Theory
010102 general mathematics
Numerical Analysis (math.NA)
Function (mathematics)
Numerical integration
Geometry and Topology
Discrepancy, Numerical integration, Metric measure spaces
Differential geometry
Metric (mathematics)
010307 mathematical physics
Analysis of PDEs (math.AP)
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....88084b3280b5d2c474d3208e0e957100