The Greedy Optimal Sampling for Solar Inverse Problems (GOSSIP) project tackles the challenge of inverting highly sparse Fourier data by developing greedy algorithms to optimally select sampling points. This is crucial for compact solar X-ray telescopes, as the ESA’s STIX telescope, which can only capture a limited number of indirect measurements (visibilities) due to hardware constraints. A key mathematical aspect of the project is the analysis of how uncertainties in the sampling locations propagate through the regularized Fourier inversion process. We are also interested in studying and testing new numerical methods for other physical solar problems, such as the detection and tracking of coronal mass ejections (CMEs).
Tozza, S. (In stampa/Attività in corso). Greedy Optimal Sampling for Solar Inverse Problems (GOSSIP).
Greedy Optimal Sampling for Solar Inverse Problems (GOSSIP)
Silvia Tozza
In corso di stampa
Abstract
The Greedy Optimal Sampling for Solar Inverse Problems (GOSSIP) project tackles the challenge of inverting highly sparse Fourier data by developing greedy algorithms to optimally select sampling points. This is crucial for compact solar X-ray telescopes, as the ESA’s STIX telescope, which can only capture a limited number of indirect measurements (visibilities) due to hardware constraints. A key mathematical aspect of the project is the analysis of how uncertainties in the sampling locations propagate through the regularized Fourier inversion process. We are also interested in studying and testing new numerical methods for other physical solar problems, such as the detection and tracking of coronal mass ejections (CMEs).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
