3 research outputs found
Compressive Sensing for Dynamic XRF Scanning
X-Ray Fluorescence (XRF) scanning is a widespread technique of high
importance and impact since it provides chemical composition maps crucial for
several scientific investigations. There are continuous requirements for
larger, faster and highly resolved acquisitions in order to study complex
structures. Among the scientific applications that benefit from it, some of
them, such as wide scale brain imaging, are prohibitively difficult due to time
constraints. However, typically the overall XRF imaging performance is
improving through technological progress on XRF detectors and X-ray sources.
This paper suggests an additional approach where XRF scanning is performed in a
sparse way by skipping specific points or by varying dynamically acquisition
time or other scan settings in a conditional manner. This paves the way for
Compressive Sensing in XRF scans where data are acquired in a reduced manner
allowing for challenging experiments, currently not feasible with the
traditional scanning strategies. A series of different compressive sensing
strategies for dynamic scans are presented here. A proof of principle
experiment was performed at the TwinMic beamline of Elettra synchrotron. The
outcome demonstrates the potential of Compressive Sensing for dynamic scans,
suggesting its use in challenging scientific experiments while proposing a
technical solution for beamline acquisition software.Comment: 16 pages, 7 figures, 1 tabl
A novel detector system for KATRIN to search for keV-scale sterile neutrinos
International audienceSterile neutrinos appear in minimal extensions of the Standard Model of particle physics. If their mass is in the keV regime, they are viable dark matter candidates. One way to search for sterile neutrinos in a laboratory-based experiment is via the analysis of β-decay spectra, where the new neutrino mass eigenstate would manifest itself as a kink-like distortion of the β-decay spectrum. The objective of the TRISTAN project is to extend the KATRIN setup with a new multi-pixel silicon drift detector system to search for a keV-scale sterile neutrino signal. In this paper we describe the requirements of such a new detector, and present first characterization measurement results obtained with a 7 pixel prototype system
Compressive Sensing for Dynamic XRF Scanning
X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and highly resolved acquisitions in order to study complex structures. Among the scientific applications that benefit from it, some of them, such as wide scale brain imaging, are prohibitively difficult due to time constraints. However, typically the overall XRF imaging performance is improving through technological progress on XRF detectors and X-ray sources. This paper suggests an additional approach where XRF scanning is performed in a sparse way by skipping specific points or by varying dynamically acquisition time or other scan settings in a conditional manner. This paves the way for Compressive Sensing in XRF scans where data are acquired in a reduced manner allowing for challenging experiments, currently not feasible with the traditional scanning strategies. A series of different compressive sensing strategies for dynamic scans are presented here. A proof of principle experiment was performed at the TwinMic beamline of Elettra synchrotron. The outcome demonstrates the potential of Compressive Sensing for dynamic scans, suggesting its use in challenging scientific experiments while proposing a technical solution for beamline acquisition software