O
Oswald H. W. Siegmund
Researcher at University of California, Berkeley
Publications - 241
Citations - 12585
Oswald H. W. Siegmund is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Microchannel plate detector & Detector. The author has an hindex of 45, co-authored 238 publications receiving 11858 citations. Previous affiliations of Oswald H. W. Siegmund include University of California, Los Angeles.
Papers
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Proceedings ArticleDOI
MCP-Medipix2 hybrid detector for AO wavefront sensors
TL;DR: In this paper, a hybrid optical detector based on proximity focused MCPs read out by a multi-pixel application specific integrated circuit (ASIC) with individual pixels that amplify, discriminate and count input events is presented.
Proceedings ArticleDOI
High-Performance Large-Area Microchannel Plate Detectors for Particle Identification Applications
Till Cremer,Melvin Aviles,Satya D. Butler,Camden Ertley,Michael R. Foley,Cole J. Hamel,Alexey Lyashenko,Michael J. Minot,Mark A. Popecki,Michael E. Stochaj,Anil U. Mane,Jeffrey W. Elam,Oswald H. W. Siegmund +12 more
TL;DR: ALD-GCA-MCPs are a technology advancement that affords microchannel plates with significant performance benefits compared to conventional lead-oxide-based MCPs.
Proceedings ArticleDOI
6-μm pore microchannel plate detectors for the ROSETTA-RTOF experiment
TL;DR: In this article, two detector units for the RTOF (reflection time of flight) mass spectrometer are based on microchannel plate detection of ions and the subsequent timing of these events.
Proceedings ArticleDOI
Photon counting arrays for AO wavefront sensors
John V. Vallerga,Anton S. Tremsin,Jason B. McPhate,Bettina Mikulec,Allan G Clark,Oswald H. W. Siegmund +5 more
TL;DR: In this paper, the authors compare the performance of noiseless array detectors and CCDs using the best available characteristics of each, and show that for sub-aperture binning of 6x6 and greater, noisless detectors have a smaller centroid error at fluences of 60 photons or less, though the specific number is dependent on seeing conditions and the centroid algorithm used.