研究目的
To present the assembly and initial results of the Belle II silicon vertex detector, focusing on its chip-on-sensor concept to minimize noise and verify performance against design specifications.
研究成果
The initial results confirm that the Belle II SVD prototype meets design specifications for signal-to-noise ratio and hit time performance, demonstrating the effectiveness of the chip-on-sensor concept. This supports its role in precise vertex determination and track reconstruction in the Belle II experiment, with expectations for full installation and operation.
研究不足
The assembly of the second half of the detector was ongoing at the time of writing, and only preliminary results from a reduced-scale prototype were available, limiting the scope of performance validation. Potential optimizations could involve further testing with the full detector and under more extensive operational conditions.
1：Experimental Design and Method Selection:
The study involves the assembly and testing of the silicon vertex detector (SVD) for the Belle II experiment, utilizing a chip-on-sensor concept to reduce signal propagation distance and noise. Prototypes were tested in test beams and in a Phase 2 setup.
2：Sample Selection and Data Sources:
Prototypes of the SVD modules, including double-sided silicon strip detectors (DSSDs) and readout chips, were used. Data were collected from commissioning runs with collisions and test beams.
3：List of Experimental Equipment and Materials:
Equipment includes DSSDs, APV25 readout ASIC chips, flex PCBs, foam material, liquid CO2 cooling system, copper cables, FADC boards, and the Belle II detector structure.
4：Experimental Procedures and Operational Workflow:
Assembly involved gluing and wire-bonding chips to sensors and PCBs, cooling with liquid CO2, and data acquisition via FADC boards. Testing was conducted in laboratories, test beams, and during Phase 2 commissioning with data processing for signal-to-noise ratio and hit time analysis.
5：Data Analysis Methods:
Data analysis included measuring signal-to-noise ratios and hit times using methods such as FIR filtering and neural networks for hit-time finding, with comparisons to design expectations.
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