Datasets:
text stringlengths 0 23 |
|---|
Total runs: 18 |
Unique enforced: False |
Clues=36: solved 6/6 |
median steps: 537 |
median seconds: 0.270 |
Clues=30: solved 6/6 |
median steps: 2784 |
median seconds: 1.315 |
Clues=26: solved 6/6 |
median steps: 7040 |
median seconds: 3.990 |
2 . . | . 7 9 | . 6 . |
. . . | . . . | . . . |
. . 6 | 8 . . | . . . |
--------------------- |
. 1 . | 2 8 . | . 3 . |
4 9 . | 1 . 7 | . . . |
6 . 8 | . . 4 | . . . |
--------------------- |
. 6 . | 4 . 8 | 3 1 7 |
8 4 . | . . 3 | . . 6 |
. . 1 | . 2 . | . . 4 |
2 5 4 | 3 7 9 | 1 6 8 |
1 8 7 | 5 6 2 | 9 4 3 |
9 3 6 | 8 4 1 | 7 2 5 |
--------------------- |
7 1 5 | 2 8 6 | 4 3 9 |
4 9 3 | 1 5 7 | 6 8 2 |
6 2 8 | 9 3 4 | 5 7 1 |
--------------------- |
5 6 2 | 4 9 8 | 3 1 7 |
8 4 9 | 7 1 3 | 2 5 6 |
3 7 1 | 6 2 5 | 8 9 4 |
Total runs: 18 |
Unique enforced: False |
Clues=36: solved 6/6 |
median steps: 4533 |
median seconds: 2.091 |
Clues=30: solved 6/6 |
median steps: 8751 |
median seconds: 3.951 |
Clues=26: solved 6/6 |
median steps: 9911 |
median seconds: 4.786 |
2 . . | . 7 9 | . 6 . |
. . . | . . . | . . . |
. . 6 | 8 . . | . . . |
--------------------- |
. 1 . | 2 8 . | . 3 . |
4 9 . | 1 . 7 | . . . |
6 . 8 | . . 4 | . . . |
--------------------- |
. 6 . | 4 . 8 | 3 1 7 |
8 4 . | . . 3 | . . 6 |
. . 1 | . 2 . | . . 4 |
2 8 4 | 3 7 9 | 5 6 1 |
1 3 7 | 5 6 2 | 9 4 8 |
9 5 6 | 8 4 1 | 7 2 3 |
--------------------- |
7 1 5 | 2 8 6 | 4 3 9 |
4 9 3 | 1 5 7 | 6 8 2 |
6 2 8 | 9 3 4 | 1 7 5 |
--------------------- |
5 6 2 | 4 9 8 | 3 1 7 |
8 4 9 | 7 1 3 | 2 5 6 |
3 7 1 | 6 2 5 | 8 9 4 |
Sudoku p-adic residual experiment data
This dataset contains the small reproducibility bundle for the manuscript "Signed p-adic Residual Encodings of Finite-Domain All-Different Systems with a Sudoku Case Study".
Canonical dataset page: https://huggingface.co/datasets/gregb/sudoku-padic-regression-experiments
The bundle includes:
data/paper_stepwise/experiment_results.csvdata/paper_zubarev/experiment_results.csv- summary files for both experiment runs
- trace puzzle and solution files for the plotted examples
- loss-curve source files
- the Python scripts used to generate the outputs
The experiment table is regenerated from the source repository with:
python3 code/run_experiments.py --outdir outputs/paper_stepwise \
--seed 123 --n 6 --clues 36,30,26 --max-steps 60000 \
--restarts 15 --method stepwise
python3 code/run_experiments.py --outdir outputs/paper_zubarev \
--seed 123 --n 6 --clues 36,30,26 --max-steps 60000 \
--restarts 15 --method zubarev --beta0 0.5 --beta1 6.0 \
--beta-schedule linear
The puzzles are randomly carved from solved grids and are not uniqueness-checked. The computational claims are illustrative rather than competitive Sudoku-solving claims.
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