Quality Control and Functional Testing of the AMAC and HCC ASICs for the HL-LHC ATLAS ITk Strip Detector
ORAL
Abstract
The high-luminosity upgrade of the Large Hadron Collider (HL-LHC) will impose new requirements on the ATLAS detector. A new silicon-strip charged-particle tracking detector for ATLAS, the Inner Tracker Strip detector (ITk Strip) has been designed to meet the challenges of increased radiation levels, stricter timing requirements, and faster readout rates, and will provide increased detector granularity. The Hybrid Controller Chip (HCC) and the Autonomous Monitor And Control (AMAC) chip are two new radiation-tolerant ASICs developed for this detector. The HCC buffers and forwards control signals to multiple readout ASICs and serializes their readout data at 640 Mbps. The AMAC operates autonomously, monitoring detector module components for temperatures, voltages, and currents, and controlling them so that these do not reach dangerous levels. All HCCs and AMACs undergo a suite of quality control tests to verify their analog and digital functionality, and detailed grading schemes have been developed to determine which ASICs should be installed on the detector. Preliminary results of these tests, as well as results of functional tests of these ASICs, are presented.
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Publication: The following preprints (submitted to JINST and accepted for publication) predate this abstract submission, and probably don't count as "derived". Nonetheless, they will be cited in this talk and significant content from them may be presented (though new content not available in these preprints will also be presented):<br>T.C. Gosart et al., "Quality Control Testing of the AMAC ASIC for the HL-LHC ATLAS ITk Strip Detector." 15th Topical Workshop on Electronics for Particle Physics, submitted to JINST, 2022. Preprint available at https://cds.cern.ch/record/2837316<br>R.P. McGovern et al., "Quality Control Testing of the HCC ASIC for the HL-LHC ATLAS ITk Strip Detector." 15th Topical Workshop on Electronics for Particle Physics, submitted to JINST, 2022. Preprint available at https://cds.cern.ch/record/2837817
