{
  "model": "J1J2",
  "lattice": "square",
  "n_sites": 100,
  "boundary": "P",
  "params": {
    "J2": 0.2
  },
  "instance_id": "J1J2/square_100_P_0.2",
  "rows": [
    {
      "energy": -237.1928,
      "sigma": null,
      "energy_variance": 0.352,
      "dof": 100,
      "einf": 0,
      "v_score": 0.0006256618287724582,
      "method": "ViT",
      "method_detail": "",
      "method_as_published": "ViT",
      "family": "transformer / ViT",
      "bound_type": "variational",
      "bound_type_reason": "variational ansatz at a stated size; energy is an upper bound (assigned during source reading)",
      "reference": "Extremely slow scaling of minimal Hamming distance in quantum sampling data, arXiv:2606.04558",
      "peer_reviewed": false,
      "source": "sweep-allresults-2026-09-28",
      "provenance": "primary",
      "verified": {
        "checked_on": "2026-09-28",
        "method": "source text of arXiv:2606.04558 read locally (arXiv HTML or pypdf layout text); value copied from the harvested cell and the text, no LLM transcription of numbers; single reading",
        "reported_as": "-0.592982",
        "note": "Table I, row J2=0.20, column '10×10, ViT (this work)' | Table I prints energy per site in S.S units: its J2 = 0 QMC column equals Sandvik's exact values on Heisenberg/square_64_P and square_100_P.",
        "secondary_of": null
      },
      "compute": {
        "parameters": null,
        "gpu_hours": null,
        "device": null,
        "n_devices": null,
        "samples": 4096,
        "wall_clock": null,
        "reported_as": "\"The corresponding number of samples is\" ... \"4096.\"",
        "source": "arXiv:2606.04558, located by string match in the committed source text"
      },
      "error_metrics": {
        "fields": [
          "energy_variance"
        ],
        "measured_by": "authors",
        "checked_on": "2026-09-28",
        "source": "extended data for the 10x10 ViT energies of arXiv:2606.04558, sent by V. V. Mazurenko on 2026-09-28 for the QMBL entry (private correspondence); column \"the best epochs, 4096 samples\", transcribed in sources/2606.04558-authors-extended-data-vit.txt",
        "source_file": "sources/2606.04558-authors-extended-data-vit.txt",
        "reported_as": "0.20 -0.592982 2.3 0.22",
        "conversion": "var_over_n_SS",
        "note": "Best of ten checkpoints (one every 150 epochs of 1500), each measured on 4096 samples: the state and sample set behind the energy Table I prints. Var(H)/N in S.S units, stored as a Pauli total (x 16 N). The source also gives an error epsilon = 2.3e-5 per site; it equals sqrt(sigma^2/(N x 4096)), the standard error without autocorrelation, so it is used only for the agreement check and not attached as sigma (RULES.md 6; Tristan, 2026-09-28)."
      }
    },
    {
      "energy": -237.1,
      "sigma": 0.004,
      "energy_variance": null,
      "dof": 100,
      "einf": 0,
      "v_score": null,
      "method": "CNN",
      "method_detail": "",
      "method_as_published": "CNN",
      "family": "CNN / ResNet",
      "bound_type": "variational",
      "bound_type_reason": "variational ansatz at a stated size; energy is an upper bound (assigned during source reading)",
      "reference": "Choo, Neupert & Carleo, Two-dimensional frustrated J1-J2 model studied with neural network quantum states, Phys. Rev. B 100, 125124 (2019)",
      "peer_reviewed": true,
      "source": "sweep-allresults-2026-09-28",
      "provenance": "secondary",
      "verified": {
        "checked_on": "2026-09-28",
        "method": "source text of arXiv:2206.14307 read locally (arXiv HTML or pypdf layout text); value copied from the harvested cell and the text, no LLM transcription of numbers; single reading",
        "reported_as": "-0.59275(1)",
        "note": "Table 5, row 'Energy(CNN)', 10x10 J2 = 0.2 | Energy per site E/N in S.S units (table captions); the 6x6 exact column equals the exact rows QMBL carries.",
        "secondary_of": "arXiv:2206.14307"
      }
    },
    {
      "energy": -237.1388,
      "sigma": 0.0036,
      "energy_variance": null,
      "dof": 100,
      "einf": 0,
      "v_score": null,
      "method": "RBM",
      "method_detail": "",
      "method_as_published": "RBM wave function",
      "family": "RBM",
      "bound_type": "variational",
      "bound_type_reason": "variational ansatz at a stated size; energy is an upper bound (assigned during source reading)",
      "reference": "Chen, Hendry, Weinberg & Feiguin, Systematic improvement of neural network quantum states using a Lanczos recursion, arXiv:2206.14307 (2022)",
      "peer_reviewed": false,
      "source": "sweep-allresults-2026-09-28",
      "provenance": "primary",
      "verified": {
        "checked_on": "2026-09-28",
        "method": "source text of arXiv:2206.14307 read locally (arXiv HTML or pypdf layout text); value copied from the harvested cell and the text, no LLM transcription of numbers; single reading",
        "reported_as": "-0.592847(9)",
        "note": "Table 5, row 'Energy(RBM)', 10x10 J2 = 0.2 | Energy per site E/N in S.S units (table captions); the 6x6 exact column equals the exact rows QMBL carries.",
        "secondary_of": null
      }
    }
  ],
  "url": "https://qmbl.org/i/J1J2/square_100_P_0.2/",
  "per_site_divisor": 400,
  "per_site_label": "E/N (S.S)",
  "record": {
    "energy": -237.1388,
    "sigma": 0.0036,
    "method": "RBM",
    "method_detail": "",
    "reference": "Chen, Hendry, Weinberg & Feiguin, Systematic improvement of neural network quantum states using a Lanczos recursion, arXiv:2206.14307 (2022)",
    "bound_type": "variational",
    "energy_per_site": -0.592847
  },
  "no_record_reason": null
}