README.md

metadata

license: cc-by-4.0
language:
  - en
pretty_name: SII Stellarator Configuration Dataset
tags:
  - fusion
  - stellarator
  - quasi-isodynamic
  - scientific-machine-learning
  - tabular

SII Stellarator Configuration Dataset

Wenyang Li

Shanghai Innovation Institute | PhD student

AI-Driven Controlled Fusion Simulation, Control & Design Lab

• Phone: +86-156-2003-5216
• Email: lwydsg@mail.nankai.edu.cn

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Overview

This directory hosts a stellarator configuration dataset grouped by number of field periods (nfp). Each sample keeps only three things: Fourier boundary coefficients, nfp, and 9 VMEC evaluation metrics — every field is guaranteed to be non-None / non-NaN.

Design goals:

1. Simplified content — keep only the Fourier coefficients and the 9 VMEC metrics that configuration-design optimization actually needs; all other construction parameters / diagnostics / multi-beta-branch evaluations are stripped out.
2. Ready for future growth — more QI (Quasi-Isodynamic) configurations will be folded in later, so a unified, clean, schema-stable baseline makes that painless.

Source

Derived from a local copy of proxima-fusion/constellaration, covering n_field_periods (nfp) = 1–5. The upstream library has broad coverage but not every row has complete VMEC evaluation results; this dataset keeps only rows where every field is fully valid.

File layout

One file per nfp. The filename embeds the number of retained samples n{count}:

File	Samples	Note
nfp1_n14607.parquet	14,607	nfp = 1
nfp2_n19945.parquet	19,945	nfp = 2
nfp3_n68191.parquet	68,191	nfp = 3
nfp4_n27798.parquet	27,798	nfp = 4
nfp5_n28144.parquet	28,144	nfp = 5
Total	158,685

Parquet files use snappy compression with a flat column layout — they can be loaded column-wise directly.

Fields

Each row (one sample) has three groups of fields:

1. Field-period count nfp

• Column: boundary.n_field_periods
• Type: integer
• Meaning: number of toroidal field periods
• Values present in this dataset: 1, 2, 3, 4, 5

2. Fourier boundary coefficients boundary.r_cos / boundary.z_sin

• Type: 5×9 float matrix (list<list<double>>)
• Meaning: Fourier expansion coefficients of the stellarator boundary surface along the (θ, φ) periodic directions. r_cos is the cosine component of R; z_sin is the sine component of Z (the configuration is stellarator-symmetric, so only these two terms are retained).
• Shape convention: row index corresponds to the poloidal mode m (0…4, 5 rows); column index corresponds to the toroidal mode n (−4…+4, 9 columns).

3. VMEC evaluation metrics metrics.*

Column	Meaning
metrics.aspect_ratio	Aspect ratio
metrics.edge_rotational_transform_over_n_field_periods	Edge iota / nfp (no abs applied — original sign preserved)
metrics.average_triangularity	Average triangularity
metrics.max_elongation	Maximum elongation
metrics.edge_magnetic_mirror_ratio	Edge magnetic mirror ratio
metrics.vacuum_well	Vacuum magnetic well
metrics.minimum_normalized_magnetic_gradient_scale_length	Minimum normalized magnetic gradient scale length
metrics.qi	Quasi-isodynamic residual (no log10 applied — raw value)
metrics.flux_compression_in_regions_of_bad_curvature	Flux compression in regions of bad curvature

For generality, iota is not abs-ed and qi is not log10-transformed — raw values are stored; downstream code applies whatever transform it needs.

Full schema

Flat column names for straightforward column-wise access:

Column	Type
boundary.n_field_periods	int64
boundary.r_cos	list<list<double>> (5×9)
boundary.z_sin	list<list<double>> (5×9)
metrics.aspect_ratio	double
metrics.edge_rotational_transform_over_n_field_periods	double
metrics.average_triangularity	double
metrics.max_elongation	double
metrics.edge_magnetic_mirror_ratio	double
metrics.vacuum_well	double
metrics.minimum_normalized_magnetic_gradient_scale_length	double
metrics.qi	double
metrics.flux_compression_in_regions_of_bad_curvature	double

Data-quality guarantee

Every sample satisfies:

1. nfp is neither None nor NaN;
2. The entire 5×9 matrices of boundary.r_cos and boundary.z_sin contain no None / NaN;
3. All 9 VMEC metrics above are non-None and non-NaN.

Any sample failing any of these conditions was removed before inclusion.