Rational sphere maps, linear programming, and compressed sensing
John P. D'Angelo, Dusty Grundmeier, Jiri Lebl
TL;DR
This paper explores the connections between rational sphere maps, linear programming, and compressed sensing, introducing new ideas, examples, and open problems to advance understanding in these interconnected areas.
Contribution
It establishes a novel link between degree estimates for rational sphere maps and compressed sensing, offering new insights and numerous examples to deepen the theoretical connections.
Findings
New connections between rational sphere maps and compressed sensing
Introduction of several new ideas and examples in the field
A list of ten open problems for future research
Abstract
We develop a link between degree estimates for rational sphere maps and compressed sensing. We provide several new ideas and many examples, both old and new, that amplify connections with linear programming. We close with a list of ten open problems.
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