dorsal/arxiv
View SchemaStudies of 100 um-thick silicon strip detector with analog VLSI readout
| Authors | T. Hotta, M. Fujiwara, T. Kinashi, Y. Kuno, M. Kuss, T. Matsumura, T. Nakano, S. Sekikawa, H. Tajima |
|---|---|
| Categories | |
| ArXiv ID | physics/9812034 |
| URL | https://arxiv.org/abs/physics/9812034 |
Abstract
We evaluate the performances of a 100 um-thick silicon strip detector (SSD) with a 300 MeV proton beam and a 90Sr beta-ray source. Signals from the SSD have been read out using a VLSI chip. Common-mode noise, signal separation efficiency and energy resolution are compared with those for the SSD's with a thickness of 300 um and 500 um. Energy resolution for minimum ionizing particles (MIP's) is improved by fitting the non-constant component in a common-mode noise with a linear function.
{
"annotation_id": "a5c59a48-ce36-46e3-8deb-cf45adc15e40",
"date_created": "2026-03-02T18:01:21.839000Z",
"date_modified": "2026-03-02T18:01:21.839000Z",
"file_hash": "a7419359051f243986ce600e48dfebe999a32376ad4510d6ec1d5245996cc149",
"private": false,
"record": {
"abstract": "We evaluate the performances of a 100 um-thick silicon strip detector (SSD)\nwith a 300 MeV proton beam and a 90Sr beta-ray source. Signals from the SSD\nhave been read out using a VLSI chip. Common-mode noise, signal separation\nefficiency and energy resolution are compared with those for the SSD\u0027s with a\nthickness of 300 um and 500 um. Energy resolution for minimum ionizing\nparticles (MIP\u0027s) is improved by fitting the non-constant component in a\ncommon-mode noise with a linear function.",
"arxiv_id": "physics/9812034",
"authors": [
"T. Hotta",
"M. Fujiwara",
"T. Kinashi",
"Y. Kuno",
"M. Kuss",
"T. Matsumura",
"T. Nakano",
"S. Sekikawa",
"H. Tajima"
],
"categories": [
"physics.ins-det",
"hep-ex"
],
"title": "Studies of 100 um-thick silicon strip detector with analog VLSI readout",
"url": "https://arxiv.org/abs/physics/9812034"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "1449a1f4-ec29-4c83-8d5d-259031cb3c94",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}