Near-axis quasi-isodynamic database

TL;DR

This work creates a comprehensive database of over 800,000 stable quasi-isodynamic stellarator configurations using near-axis magnetic field expansion, enabling detailed analysis and optimization insights.

Contribution

It introduces a large, systematically generated database of quasi-isodynamic stellarators with diverse parameters, facilitating advanced analysis and design optimization.

Findings

Database includes 800,000+ configurations with stability and quasi-isodynamic properties.

Statistical and machine learning analyses reveal key descriptors influencing configuration behavior.

Provides baseline configurations for future studies and optimization efforts.

Abstract

In this work, we investigate the landscape of quasi-isodynamic stellarators using the near-axis expansion of the magnetic field. Building on recent theoretical developments, we construct a database of more than 800,000 stable, approximately quasi-isodynamic vacuum magnetic configurations. These configurations span a range of field period numbers and other geometric control parameters, including the magnetic axis shape and plasma elongation. To evaluate each configuration, we use a broad set of measures, including effective ripple, sensitivity of the Shafranov shift to changes in plasma beta, the prevalence of maximum-J trapped particles, and the Rosenbluth-Hinton residual, among others. This enables an exhaustive, thorough and quantitative characterization of the database. Statistical analysis and modern machine learning techniques are then employed to find correlations, and identify key descriptors and heuristics to help understand tendencies that govern the behaviour of numerical optimization. The database provides baseline configurations for further studies, and to serve as tailored initial conditions for optimization. With this work we initiate a long term program to complete a systematic exploration of quasi-isodynamic stellarator design space.