Abstract
Theoretical results from the field of compressed sensing (CS), principally theorems specifying the minimum number of samples need to reconstruct a sparse spectrum, led to an explosion of activity in NMR on efficient sampling strategies and spectral reconstruction methods. While these results firmly established the notion that sparse multidimensional NMR spectra can be accurately recovered using far fewer samples and with higher resolution than is possible using conventional uniform sampling, quantitative agreement between the theorems and empirical observations remains elusive. A likely contributor to this discordance is that NMR spectra do not satisfy the strict definitions of sparseness assumed by CS. In addition, Monajemi and Donoho \cite{MoDo17}recently showed that certain specifics of NMR experiment design require modification of CS theorems. For example, when uniform sampling is conducted in a dimension orthogonal to dimensions that are sampled nonuniformly, an excess coherence is introduced that increases the minimum number of samples required to recover the spectrum. Similarly, the simple quantification of coherence of sampling schemes used in CS requires modification when phase subdimensions are sampled nonuniformly (as in random phase detection or partial component sampling \cite{21949370}(Maciejewski 2011)). Beyond the minimum bounds on the number of samples needed to recover a sparse multidimensional NMR spectrum, the notion of phase transitions in CS, the sharp transition from successful recovery to failure, holds important implications for the design of NMR experiments, including the impact of higher magnetic fields. Here we consider the broader implications of CS theorems for nonuniform sampling in multidimensional NMR and discuss avenues for further investigation.