dorsal/arxiv
View SchemaA fast programmable trigger for isolated cluster counting in the BELLE experiment
| Authors | H. J. Kim, S. K. Kim, S. H. Lee, T. W. Hur, C. H. Kim, F. Wang, I. C. Park, Hee Jong Kim, B. G. Cheon, E. Won |
|---|---|
| Categories | |
| ArXiv ID | physics/9911050 |
| URL | https://arxiv.org/abs/physics/9911050 |
Abstract
We have developed a fast programmable trigger processor board based on a field programmable gate array and a complex programmable logic device for use in the BELLE experiment. The trigger board accommodates 144 ECL input signals, 2 NIM input signals, 24 ECL output signals, and the VME bus specification. An asynchronous trigger logic for counting isolated clusters is used. We have obtained trigger latency of 50 ns with a full access to input and output signals via a VME interface. The trigger logic can be modified at any time depending on the experimental conditions.
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"date_created": "2026-03-02T18:01:25.440000Z",
"date_modified": "2026-03-02T18:01:25.440000Z",
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"abstract": "We have developed a fast programmable trigger processor board based on a\nfield programmable gate array and a complex programmable logic device for use\nin the BELLE experiment. The trigger board accommodates 144 ECL input signals,\n2 NIM input signals, 24 ECL output signals, and the VME bus specification. An\nasynchronous trigger logic for counting isolated clusters is used. We have\nobtained trigger latency of 50 ns with a full access to input and output\nsignals via a VME interface. The trigger logic can be modified at any time\ndepending on the experimental conditions.",
"arxiv_id": "physics/9911050",
"authors": [
"H. J. Kim",
"S. K. Kim",
"S. H. Lee",
"T. W. Hur",
"C. H. Kim",
"F. Wang",
"I. C. Park",
"Hee Jong Kim",
"B. G. Cheon",
"E. Won"
],
"categories": [
"physics.ins-det"
],
"title": "A fast programmable trigger for isolated cluster counting in the BELLE experiment",
"url": "https://arxiv.org/abs/physics/9911050"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "29c2e87b-649f-4133-a5c3-c0a20765d42d",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
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