dorsal/arxiv
View SchemaGrover's quantum searching algorithm is optimal
| Authors | Christof Zalka |
|---|---|
| Categories | |
| ArXiv ID | quant-ph/9711070 |
| URL | https://arxiv.org/abs/quant-ph/9711070 |
| DOI | 10.1103/PhysRevA.60.2746 |
| Journal | Phys.Rev. A60 (1999) 2746-2751 |
Abstract
I improve the tight bound on quantum searching by Boyer et al. (quant-ph/9605034) to a matching bound, thus showing that for any probability of success Grovers quantum searching algorithm is optimal. E.g. for near certain success we have to query the oracle pi/4 sqrt{N} times, where N is the size of the search space. I also show that unfortunately quantum searching cannot be parallelized better than by assigning different parts of the search space to independent quantum computers. Earlier results left open the possibility of a more efficient parallelization.
{
"annotation_id": "a620156e-b3a3-43f8-9d2c-85772bc3b301",
"date_created": "2026-03-02T18:02:41.042000Z",
"date_modified": "2026-03-02T18:02:41.042000Z",
"file_hash": "20d397173dc3bd656631091d0be3c7b338baca1aaadafc615af4dc801d56b488",
"private": false,
"record": {
"abstract": "I improve the tight bound on quantum searching by Boyer et al.\n(quant-ph/9605034) to a matching bound, thus showing that for any probability\nof success Grovers quantum searching algorithm is optimal. E.g. for near\ncertain success we have to query the oracle pi/4 sqrt{N} times, where N is the\nsize of the search space. I also show that unfortunately quantum searching\ncannot be parallelized better than by assigning different parts of the search\nspace to independent quantum computers. Earlier results left open the\npossibility of a more efficient parallelization.",
"arxiv_id": "quant-ph/9711070",
"authors": [
"Christof Zalka"
],
"categories": [
"quant-ph"
],
"doi": "10.1103/PhysRevA.60.2746",
"journal_ref": "Phys.Rev. A60 (1999) 2746-2751",
"title": "Grover\u0027s quantum searching algorithm is optimal",
"url": "https://arxiv.org/abs/quant-ph/9711070"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "ff2d8a64-9521-43f5-84e6-13f2425af7d4",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}