dorsal/arxiv
View SchemaNew method to simulate quantum interference using deterministic processes and application to event-based simulation of quantum computation
| Authors | H. De Raedt, K. De Raedt, K. Michielsen |
|---|---|
| Categories | |
| ArXiv ID | quant-ph/0501139 |
| URL | https://arxiv.org/abs/quant-ph/0501139 |
| DOI | 10.1143/JPSJS.74S.16 |
Abstract
We demonstrate that networks of locally connected processing units with a primitive learning capability exhibit behavior that is usually only attributed to quantum systems. We describe networks that simulate single-photon beam-splitter and Mach-Zehnder interferometer experiments on a causal, event-by-event basis and demonstrate that the simulation results are in excellent agreement with quantum theory. We also show that this approach can be generalized to simulate universal quantum computers.
{
"annotation_id": "efdcd996-0d91-4ba7-9aae-35276a8feee0",
"date_created": "2026-03-02T18:02:13.510000Z",
"date_modified": "2026-03-02T18:02:13.510000Z",
"file_hash": "9500f8efce5cf5f103893ba39f843a12efd1bc26e3e1b1c56460217af76a588f",
"private": false,
"record": {
"abstract": "We demonstrate that networks of locally connected processing units with a\nprimitive learning capability exhibit behavior that is usually only attributed\nto quantum systems. We describe networks that simulate single-photon\nbeam-splitter and Mach-Zehnder interferometer experiments on a causal,\nevent-by-event basis and demonstrate that the simulation results are in\nexcellent agreement with quantum theory. We also show that this approach can be\ngeneralized to simulate universal quantum computers.",
"arxiv_id": "quant-ph/0501139",
"authors": [
"H. De Raedt",
"K. De Raedt",
"K. Michielsen"
],
"categories": [
"quant-ph"
],
"doi": "10.1143/JPSJS.74S.16",
"title": "New method to simulate quantum interference using deterministic processes and application to event-based simulation of quantum computation",
"url": "https://arxiv.org/abs/quant-ph/0501139"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "28ffd81f-392b-4520-80a1-f34e2871201c",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}