{
  "annotation_id": "404d303d-70a7-4a6e-b4ed-ec63173b1f4f",
  "date_created": "2026-03-02T18:01:18.135000Z",
  "date_modified": "2026-03-02T18:01:18.135000Z",
  "file_hash": "bfda04c46b5dfb2bc137aeb71deadee5f579265bf4c17a5256d3b1c7cdaeaad4",
  "private": false,
  "record": {
    "abstract": "We present a quantum-like (QL) model in that contexts (complexes of e.g.\nmental, social, biological, economic or even political conditions) are\nrepresented by complex probability amplitudes. This approach gives the\npossibility to apply the mathematical quantum formalism to probabilities\ninduced in any domain of science. In our model quantum randomness appears not\nas irreducible randomness (as it is commonly accepted in conventional quantum\nmechanics, e.g., by von Neumann and Dirac), but as a consequence of obtaining\nincomplete information about a system. We pay main attention to the QL\ndescription of processing of incomplete information. Our QL model can be useful\nin cognitive, social and political sciences as well as economics and artificial\nintelligence. In this paper we consider in a more detail one special\napplication -- QL modeling of brain\u0027s functioning. The brain is modeled as a\nQL-computer.",
    "arxiv_id": "physics/0702250",
    "authors": [
      "Andrei Khrennikov"
    ],
    "categories": [
      "physics.gen-ph",
      "physics.pop-ph"
    ],
    "doi": "10.1142/9789812779953_0006",
    "title": "Quantum-like Probabilistic Models outside Physics",
    "url": "https://arxiv.org/abs/physics/0702250"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "860a797f-ace4-4fc7-aef5-43e69248b94c",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}