dorsal/arxiv
View SchemaError-Resistant Distributed Quantum Computation in Trapped Ion Chain
| Authors | Sibylle Braungardt, Aditi Sen De, Ujjwal Sen, Maciej Lewenstein |
|---|---|
| Categories | |
| ArXiv ID | quant-ph/0607053 |
| URL | https://arxiv.org/abs/quant-ph/0607053 |
| DOI | 10.1103/PhysRevA.76.042307 |
| Journal | Phys. Rev. A 76, 042307 (2007) |
Abstract
We consider experimentally feasible chains of trapped ions with pseudo-spin 1/2, and find models that can potentially be used to implement error-resistant quantum computation. Similar in spirit to classical neural networks, the error-resistance of the system is achieved by encoding the qubits distributed over the whole system. We therefore call our system a ''quantum neural network'', and present a ''quantum neural network model of quantum computation''. Qubits are encoded in a few quasi-degenerated low energy levels of the whole system, separated by a large gap from the excited states, and large energy barriers between themselves. We investigate protocols for implementing a universal set of quantum logic gates in the system, by adiabatic passage of a few low-lying energy levels of the whole system. Naturally appearing and potentially dangerous distributed noise in the system leaves the fidelity of the computation virtually unchanged, if it is not too strong. The computation is also naturally resilient to local perturbations of the spins.
{
"annotation_id": "d73e7c7d-3256-4889-83b4-4a17ffc6a59f",
"date_created": "2026-03-02T18:02:27.408000Z",
"date_modified": "2026-03-02T18:02:27.408000Z",
"file_hash": "cea2e9b4fc310adfe787f8cc6d62a9411ecf5c40461ed22badfa2f3b17190cf1",
"private": false,
"record": {
"abstract": "We consider experimentally feasible chains of trapped ions with pseudo-spin\n1/2, and find models that can potentially be used to implement error-resistant\nquantum computation. Similar in spirit to classical neural networks, the\nerror-resistance of the system is achieved by encoding the qubits distributed\nover the whole system. We therefore call our system a \u0027\u0027quantum neural\nnetwork\u0027\u0027, and present a \u0027\u0027quantum neural network model of quantum\ncomputation\u0027\u0027. Qubits are encoded in a few quasi-degenerated low energy levels\nof the whole system, separated by a large gap from the excited states, and\nlarge energy barriers between themselves. We investigate protocols for\nimplementing a universal set of quantum logic gates in the system, by adiabatic\npassage of a few low-lying energy levels of the whole system. Naturally\nappearing and potentially dangerous distributed noise in the system leaves the\nfidelity of the computation virtually unchanged, if it is not too strong. The\ncomputation is also naturally resilient to local perturbations of the spins.",
"arxiv_id": "quant-ph/0607053",
"authors": [
"Sibylle Braungardt",
"Aditi Sen De",
"Ujjwal Sen",
"Maciej Lewenstein"
],
"categories": [
"quant-ph",
"cond-mat.dis-nn"
],
"doi": "10.1103/PhysRevA.76.042307",
"journal_ref": "Phys. Rev. A 76, 042307 (2007)",
"title": "Error-Resistant Distributed Quantum Computation in Trapped Ion Chain",
"url": "https://arxiv.org/abs/quant-ph/0607053"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "a816b8c2-7f5a-4677-b5ee-37cc1a050ecd",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}