dorsal/arxiv
View SchemaNumerical simulation of information recovery in quantum computers
| Authors | Pedro J. Salas, Angel L. Sanz |
|---|---|
| Categories | |
| ArXiv ID | quant-ph/0207068 |
| URL | https://arxiv.org/abs/quant-ph/0207068 |
| DOI | 10.1103/PhysRevA.66.022302 |
Abstract
Decoherence is the main problem to be solved before quantum computers can be built. To control decoherence, it is possible to use error correction methods, but these methods are themselves noisy quantum computation processes. In this work we study the ability of Steane's and Shor's fault-tolerant recovering methods, as well a modification of Steane's ancilla network, to correct errors in qubits. We test a way to measure correctly ancilla's fidelity for these methods, and state the possibility of carrying out an effective error correction through a noisy quantum channel, even using noisy error correction methods.
{
"annotation_id": "8324cde5-b17b-42ee-a1c9-73bfddbeca14",
"date_created": "2026-03-02T18:01:52.303000Z",
"date_modified": "2026-03-02T18:01:52.303000Z",
"file_hash": "be3c24d0ae5c43ba1ce77fbfd884af2288aedb55bc296c7cda60c6346e03a84b",
"private": false,
"record": {
"abstract": "Decoherence is the main problem to be solved before quantum computers can be\nbuilt. To control decoherence, it is possible to use error correction methods,\nbut these methods are themselves noisy quantum computation processes. In this\nwork we study the ability of Steane\u0027s and Shor\u0027s fault-tolerant recovering\nmethods, as well a modification of Steane\u0027s ancilla network, to correct errors\nin qubits. We test a way to measure correctly ancilla\u0027s fidelity for these\nmethods, and state the possibility of carrying out an effective error\ncorrection through a noisy quantum channel, even using noisy error correction\nmethods.",
"arxiv_id": "quant-ph/0207068",
"authors": [
"Pedro J. Salas",
"Angel L. Sanz"
],
"categories": [
"quant-ph"
],
"doi": "10.1103/PhysRevA.66.022302",
"title": "Numerical simulation of information recovery in quantum computers",
"url": "https://arxiv.org/abs/quant-ph/0207068"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "0b913059-2bc4-42ee-a9d7-6e1a42899ebb",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}