Truncation Dimension for Linear Problems on Multivariate Function Spaces
arXiv:1701.06778
Abstract
The paper considers linear problems on weighted spaces of multivariate functions of many variables. The main questions addressed are: When is it possible to approximate the solution for the original function of very many variables by the solution for the same function; however with all but the first variables set to zero, so that the corresponding error is small? What is the truncation dimension, i.e., the smallest number such that the corresponding error is bounded by a given error demand ? Surprisingly, could be very small even for weights with a modest speed of convergence to zero.