Development of a Waveform Sampling Asic with Femtosecond Timing for a Low Occupancy Vertex Detector.

dc.contributor.authorOrel, Peter
dc.contributor.departmentElectrical Engineering
dc.date.accessioned2019-05-28T19:56:10Z
dc.date.available2019-05-28T19:56:10Z
dc.date.issued2018-05
dc.description.abstractVertex detectors provide space-time coordinates for the traversing charged particle decay products closest to the interaction point of a high-energy particle collider. Resolving these increasingly intense particle uences at higher luminosities (larger number of collisions per second) is an ever- growing challenge. Furthermore, such uences result in a non-negligible occupancy of the vertex detectors using existing low material budget techniques. Consequently, new approaches are being studied that meet the vertexing requirements while lowering the occupancy and the data rate. In this work we introduce the architecture and speci cations for a novel vertex detector design based on femtosecond precision timing. The feasibility study results indicate that the new detector ladder design could achieve an occupancy ten times lower than its predecessor in the Belle II spectrometer, while maintaining a comparable spatial resolution. Furthermore, this leads to a considerable reduction in the detector data rate, thus lowering the cost of the subsequent processing electronics. One of the crucial parts of the detector is its readout ASIC (RFpix), whose development steps are discussed in detail. The RFpix is a twelve-bit resolution waveform digitizer with a sampling speed of 20 GS/s and an analog bandwidth of 3 GHz. Post-layout simulation results of the RFpix prototype analog front-end are shown and thoroughly analyzed. The simulated performance is shown to match the RFpix requirements, thus reaching an exquisite timing resolution of 160 fs.
dc.identifier.urihttp://hdl.handle.net/10125/62399
dc.languageeng
dc.publisherUniversity of Hawaii at Manoa
dc.titleDevelopment of a Waveform Sampling Asic with Femtosecond Timing for a Low Occupancy Vertex Detector.
dc.typeThesis
dc.type.dcmiText
dcterms.descriptionPh.D. Thesis. University of Hawaiʻi at Mānoa 2018.

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