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Home > Publications database > Characterisation of the ATLAS ITK Strips Front-End Chip and Development of EUDAQ 2.0 for the EUDET-Style Pixel Telescopes |
Book/Report/Dissertation / PhD Thesis | PUBDB-2017-01392 |
; ;
2017
Verlag Deutsches Elektronen-Synchrotron
Hamburg
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Please use a persistent id in citations: doi:10.3204/PUBDB-2017-01392
Report No.: DESY-THESIS-2017-009
Abstract: As part of the ATLAS phase-II upgrade a new, all-silicon tracker will be built. The newtracker will consist of silicon pixel sensors and silicon microstrip sensors. For the readoutof the microstrip sensor a new readout chip was designed; the so called ATLAS BinaryConverter 130 (ABC130) which is based on a 130 nm CMOS technology. The chip consistsof an analog Front End built up of 256 channels, each with a preamplifier and a discriminatorfor converting the analog sensor readout into a binary response. The preamplifier of theABC130 was designed to have a gain of 90 − 95 $\frac{mV}{fC}$. First laboratory measurements with the built-in control circuits have shown a gain of < 75 $\frac{mV}{fC}$. In the course of this thesis a test beam campaign was undertaken to measure the gain in an unbiased system under realisticconditions. The obtained gain varied from ≈ 90 $\frac{mV}{fC}$ to ≈ 100 $\frac{mV}{fC}$. With this, the valuesobtained by the test beam campaign are within the specifications. In order to perform the test beam campaign with optimal efficiency, a complete overhaulof the data acquisition framework used for the EUDET type test beam telescopes wasnecessary. The new version is called EUDAQ 2.0. It is designed to accommodate deviceswith different integration times such as LHC-type devices with an integration time of only25 ns, and devices with long integration times such as the MIMOSA26 with an integrationtime of 114.5 μs. To accomplish this a new synchronization algorithm has been developed.It gives the user full flexibility on the means of synchronizing their own data stream with thesystem. Beyond this, EUDAQ 2.0 also allows user specific encoding and decoding of datapackets. This enables the user to minimize the data overhead and to shift more computationtime to the offline stage. To reduce the network overhead EUDAQ 2.0 allows the user tostore data locally. The merging is then postponed to the offline stage.
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