Downloads provided by UsageCounts
The new generation of ground-based extremely large telescopes require highly efficient algorithms to achieve an excellent image quality in a large eld of view. These systems rely on adaptive optics, where one aims to compensate in real-time the rapidly changing optical distortions in the atmosphere. Due to the growth of telescope sizes, the computational load is increasing drastically. Thus, current algorithms become inappropriate and there is a big interest in the development of more efficient solvers. In this work, we compare a novel method called Finite Element Wavelet Hybrid Algorithm to the frequently used MVM within the framework of MAORY, an instrument of the Extremely Large Telescope. We look in detail at the performance of both algorithms in terms of floating point operations, memory usage and parallelization possibilities. On that basis, we determine a possible real-time computing hardware architecture for both algorithms.
Proceedings of the AO4ELT6, June 9-14, 2019 in Québec City, Canada
FEWHA, feasibility study, atmospheric tomography, MVM
FEWHA, feasibility study, atmospheric tomography, MVM
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 6 | |
| downloads | 5 |

Views provided by UsageCounts
Downloads provided by UsageCounts