{
  "annotation_id": "4bf1f724-84c1-4b57-aa89-5c2bca8ea851",
  "date_created": "2026-03-02T18:01:42.695000Z",
  "date_modified": "2026-03-02T18:01:42.695000Z",
  "file_hash": "973ea1f6596e62967aa858e05b5aa816f9334d980fa2c9fc422eb7e98158def3",
  "private": false,
  "record": {
    "abstract": "A quantum system will stay near its instantaneous ground state if the\nHamiltonian that governs its evolution varies slowly enough. This quantum\nadiabatic behavior is the basis of a new class of algorithms for quantum\ncomputing. We test one such algorithm by applying it to randomly generated,\nhard, instances of an NP-complete problem. For the small examples that we can\nsimulate, the quantum adiabatic algorithm works well, and provides evidence\nthat quantum computers (if large ones can be built) may be able to outperform\nordinary computers on hard sets of instances of NP-complete problems.",
    "arxiv_id": "quant-ph/0104129",
    "authors": [
      "Edward Farhi",
      "Jeffrey Goldstone",
      "Sam Gutmann",
      "Joshua Lapan",
      "Andrew Lundgren",
      "Daniel Preda"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1126/science.1057726",
    "title": "A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of   an NP-Complete Problem",
    "url": "https://arxiv.org/abs/quant-ph/0104129"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "d5605411-b5c6-48df-8170-cff64ace4613",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}