{
  "annotation_id": "1e44cceb-62a3-44eb-b160-254dc946a4ab",
  "date_created": "2026-03-02T18:00:39.557000Z",
  "date_modified": "2026-03-02T18:00:39.557000Z",
  "file_hash": "1629d9a754445428c5fbef2c5a51b7182efbd70a3d9a64db7f152da007bd6e30",
  "private": false,
  "record": {
    "abstract": "So far proposed quantum computers use fragile and environmentally sensitive\nnatural quantum systems. Here we explore the new notion that synthetic quantum\nsystems suitable for quantum computation may be fabricated from smart\nnanostructures using topological excitations of a stochastic neural-type\nnetwork that can mimic natural quantum systems. These developments are a\ntechnological application of process physics which is an information theory of\nreality in which space and quantum phenomena are emergent, and so indicates the\ndeep origins of quantum phenomena. Analogous complex stochastic dynamical\nsystems have recently been proposed within neurobiology to deal with the\nemergent complexity of biosystems, particularly the biodynamics of higher brain\nfunction. The reasons for analogous discoveries in fundamental physics and\nneurobiology are discussed.",
    "arxiv_id": "physics/0209064",
    "authors": [
      "Reginald T. Cahill"
    ],
    "categories": [
      "physics.gen-ph"
    ],
    "doi": "10.1088/0964-1726/11/5/312",
    "journal_ref": "Smart Mater.Struct. 11 (2002) 699-707",
    "title": "Synthetic Quantum Systems",
    "url": "https://arxiv.org/abs/physics/0209064"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "56e45a66-9cba-4a8e-b0a6-e3297a7e6d6c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}