Distilling common randomness from bipartite quantum states
Igor Devetak, Andreas Winter
ISIT 2003
Methods of successive approximation for solving linear systems or minimization problems are accelerated by aggregation-disaggregation processes. These processes, which modify the iterates being produced, are characterized by a two directional flow of information between the original higher dimensional problem and a lower dimensional aggregated version. This technique is characterized by means of Galerkin approximations, and this in turn permits analysis of the method. A deterministic as well as probabilistic analysis is given of a number of specific aggregation-disaggregation examples. Numerical experiments have been performed, and these confirm the analysis and demonstrate the acceleration. © 1982.
Igor Devetak, Andreas Winter
ISIT 2003
R.A. Brualdi, A.J. Hoffman
Linear Algebra and Its Applications
Sankar Basu
Journal of the Franklin Institute
A.R. Conn, Nick Gould, et al.
Mathematics of Computation