{
  "$schema": "https://themachinepress.com/schemas/story-v1.schema.json",
  "schema_version": "1.0.0",
  "document_type": "machine_press_story",
  "story": {
    "story_id": "mp-2026-10-23-016",
    "source_story_id": "tmp-brief-arctn-contraction-planning",
    "edition_id": "mp-2026-10-23-morning-0105",
    "edition_url": "https://themachinepress.com/edition/2026-10-23",
    "position": 18,
    "story_type": "ticker",
    "section": "infrastructure",
    "editorial_classification": "editorial",
    "headline": "Quantum Simulation Finds a Cheaper Contraction Order",
    "slug": "quantum-simulation-finds-a-cheaper-contraction-order",
    "dek": "ArcTN's Light preset cut planned FLOPs 61.32 percent against one compared baseline while planning 1.62 times faster.",
    "summary": "ArcTN's Light preset cut planned FLOPs 61.32 percent against one compared baseline while planning 1.62 times faster.",
    "body_text": "ArcTN combines randomized-greedy construction, subtree reconfiguration and parallel tempering, then slices tensors to fit memory limits. Its relative gains vary by network and comparator, but the reported suite shows lower planning-plus-execution cost on the common completed runs.",
    "why_it_matters": "ArcTN's Light preset cut planned FLOPs 61.32 percent against one compared baseline while planning 1.62 times faster.",
    "limitations": [],
    "importance": 7,
    "canonical_url": "https://themachinepress.com/story/mp-2026-10-23-016/quantum-simulation-finds-a-cheaper-contraction-order",
    "json_url": "https://themachinepress.com/story/mp-2026-10-23-016.json",
    "first_published_at": "2026-10-23T09:00:00.000-04:00",
    "modified_at": "2026-10-23T09:00:00.000-04:00",
    "content_status": "new",
    "is_carryover": false,
    "carryover_reason": null,
    "key_claims": [
      {
        "claim_id": "claim-mp-2026-10-23-016-001",
        "text": "ArcTN's Light preset cut planned FLOPs 61.32 percent against one compared baseline while planning 1.62 times faster.",
        "source_ids": [
          "source-2026-10-23-018"
        ],
        "qualification": null
      }
    ],
    "source_ids": [
      "source-2026-10-23-018"
    ],
    "tags": [
      "quantum simulation",
      "tensor networks",
      "optimization"
    ],
    "image_url": null,
    "corrections": []
  },
  "sources": [
    {
      "source_id": "source-2026-10-23-018",
      "title": "arXiv preprint 2610.31554, original v1",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2610.31554v1",
      "canonical_url": "https://arxiv.org/abs/2610.31554v1",
      "source_type": "primary_research",
      "is_primary_source": true,
      "published_at": "2026-10-22T12:58:31.000-04:00",
      "accessed_at": "2026-10-23T08:21:38.024-04:00",
      "supports_claim_ids": [
        "claim-mp-2026-10-23-016-001"
      ]
    }
  ],
  "corrections": [],
  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
  },
  "cite_this_report": {
    "title": "Quantum Simulation Finds a Cheaper Contraction Order",
    "publisher": "The Machine Press",
    "published_at": "2026-10-23T09:00:00.000-04:00",
    "canonical_url": "https://themachinepress.com/story/mp-2026-10-23-016/quantum-simulation-finds-a-cheaper-contraction-order"
  }
}
