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Datasets:
Tribewarez
/
pot-o-quantum-88

Tasks:
Text Generation
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
100K - 1M
Tags:
Synthetic
pot-o
tensor-optimization
proof-of-tensor
tribewarez
planck
Libraries:
Datasets
pandas
Polars
License:
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metadata 
license: mit
language:
  - en
tags:
  - synthetic
  - pot-o
  - tensor-optimization
  - proof-of-tensor
  - tribewarez
  - planck
  - tensor-network
  - quantum-88
  - realms
  - mml
size_categories:
  - 100K<n<1M
task_categories:
  - text-generation

pot-o-quantum-88

888,888 synthetic PoT-O challenges for tensor + MML path optimization in a Planck–tensor–realm lineage used to probe REALMS / realms-devkit themes: Planck-scale framing (Part I), tensor-network / entropy toy scales (Part IV §3–§4), and coarse-resolution “realm” tensor shapes (including 8×8 and 88×8-style blocks).

Program scale (8.88M lineage): each row carries nominal_lineage_M: 8.88 (documentation of the Quantum-88 / 8.88M Tribewarez program scale). This dataset shard size is 888,888 rows (not 8.88×10⁶ full split).

Record schema

Field Meaning
challenge Classic PoT-O line: tensor:shape=[M,N];dtype=...;target_mml=...;ops:...
optimal_path Heuristic MML-style path + score:
difficulty From target_mml
source PoT-O/TribeWarez-Quantum88-PlanckTensor
param_signature 8.888888 (quantum-88 lineage constant)
planck_tensor_realm true — tensor pool uses Planck-realm / “88” shapes
nominal_lineage_M 8.88 — 8.88M-scale program tag
realms_reference Pointer to devkit + manuscript stack

Generation (reproducible)

Parameters: params.json

python pot-o-quantum-88/generate.py

Or via the classic generator:

python generate_synthetic_pot_o_challenges.py \
  --num-records 888888 \
  --output pot-o-quantum-88/pot-o-quantum-88.jsonl \
  --seed 888888 \
  --target-mml-center 0.0888888 \
  --param-signature 8.888888 \
  --source PoT-O/TribeWarez-Quantum88-PlanckTensor \
  --planck-tensor-realm \
  --record-extra-json '{"nominal_lineage_M":8.88,"realms_reference":"devtools/realms-devkit Part I Planck + Part IV tensor network toy scales"}'

Proving / investigating REALMS (devkit)

Manuscript / topic devkit entry
Planck units, Bekenstein bounds 01_planck_and_bounds.ipynb
Tensor network entropy (S = \gamma
Entanglement / geometry 03_entanglement_geometry.ipynb

Manuscript (33-page REALMS): TribeWarez/realms

Hub 

pip install datasets huggingface_hub
huggingface-cli login
python pot-o-quantum-88/upload_dataset.py

Related

MIT — Tribewarez guild — live beta.