Effect of static magnetic island on ITG of ADITYA-U tokamak

Magnetic islands play a crucial role in regulating plasma confinement in tokamaks by interacting with micro-instabilities, such as the ion temperature gradient (ITG) mode. This work presents a detailed investigation of the effects of static magnetic islands on ITG instability, relevant to the ADITYA-U tokamak, using the Global Gyrokinetic Code in Cylindrical Coordinates (G2C3), a particle-in-cell (PIC) framework that employs a neural-network-assisted projection scheme. A two-phase simulation strategy is adopted. In the first phase, static magnetic islands with mode numbers (m, n) = (2, 1) and (3, 1) are introduced by perturbing the equilibrium magnetic flux functions. Particle dynamics within these modified topologies result in the flattening of plasma density profiles in the island regions, confirming island formation and its impact on the equilibrium profiles. In the second phase, the flattened profiles serve as new equilibria for linear electrostatic gyrokinetic simulations with adiabatic electrons, enabling the study of the modified ITG behavior. Magnetic islands significantly restructure the ITG mode, producing a spatial redistribution of potential fluctuations within and around the island region. Moreover, as the island width increases, the growth rates of different toroidal ITG modes converge, suggesting a universal stabilization trend. A comparison between the (2,1) and (3,1) islands indicates that higher-q islands lead to a more spatially extended ITG mode structure, reflecting the longer magnetic connection lengths and weaker curvature drive at outer flux surfaces. These results demonstrate the pivotal role of island-induced equilibrium modifications in determining ITG stability and mode structure in tokamak plasmas.

💡 Research Summary

This paper presents a comprehensive investigation of how static magnetic islands affect the ion‑temperature‑gradient (ITG) instability in the ADITYA‑U tokamak, using the Global Gyrokinetic Code in Cylindrical Coordinates (G2C3). The authors adopt a two‑phase simulation workflow. In the first phase, they introduce static magnetic islands with helicities (m, n) = (2, 1) and (3, 1) by adding a helical perturbation α(ψ, θ_B, ζ) = α₀(ψ) cos(m θ_B − n ζ) to the experimentally reconstructed equilibrium flux functions. The perturbation modifies the poloidal flux ψ and generates the desired island topology at the resonant q = 2 and q = 3 surfaces, respectively. The particle‑in‑cell (PIC) implementation of G2C3, equipped with a neural‑network‑assisted field‑line‑aligned projection operator, follows the evolution of marker ions in the altered magnetic geometry. As the simulation relaxes, ion density and temperature become flattened inside the island region, reproducing the experimentally observed profile flattening and confirming that the island width and location match the measured few‑centimetre values.

In the second phase, the flattened profiles are taken as new equilibrium backgrounds for linear electrostatic gyrokinetic simulations with adiabatic electrons. The governing equation is the 5‑D gyrokinetic Vlasov equation for the ion guiding‑center distribution f_i, coupled to a gyro‑averaged Poisson equation (1 − τ∇⊥²) ϕ = Z_i δn_i. The magnetic perturbation appears in the particle equations of motion through modified field components B̃_R, B̃_Z, and B̃_ζ, which affect the parallel velocity term v_∥ δB_I·∇f₀, the E×B drift, and the curvature/gradient drift. By solving the linear weight equation L₀ w = −(1/f₀) δL f₀, the authors obtain growth rates γ and eigenmode structures for a range of toroidal mode numbers k and poloidal numbers m.

Key findings are as follows. (1) Island width strongly influences ITG stability: as the island becomes wider, the growth rates of all examined toroidal ITG modes decrease and eventually converge, indicating a universal stabilization effect caused by the reduction of temperature and density gradients within the island. (2) The (2, 1) island, located at q ≈ 2, possesses a relatively short magnetic connection length (L_c ≈ 2 R). The electrostatic potential fluctuations are largely confined to the island interior, and the mode structure shows a pronounced localization. (3) The (3, 1) island at q ≈ 3 has a longer connection length (L_c ≈ 3 R), leading to a more extended potential structure that spreads beyond the island separatrix. The weaker curvature drive at the outer surface produces a smoother, broader ITG eigenfunction. (4) The presence of the island redistributes the potential fluctuations: inside the island the amplitude is suppressed, while around the separatrix the ITG mode is reshaped, reflecting the interplay between the island‑induced flattening term v_∥ δB_I·∇f₀ and the usual drift‑wave drive. (5) The neural‑network‑assisted projection eliminates numerical singularities near the island boundary, enabling high‑resolution capture of both equilibrium flattening and mode restructuring.

The authors discuss the implications for nonlinear turbulence. Although the present work is linear, the observed restructuring suggests that in a fully nonlinear setting, the island could interact with zonal flows, potentially enhancing particle and heat transport across the separatrix. This points to the relevance of external control techniques such as electron‑cyclotron current drive (ECCD) or resonant magnetic perturbations (RMP) for tailoring island size and thereby modulating ITG activity. The study thus provides the first global gyrokinetic validation, grounded in ADITYA‑U experimental parameters, of how static magnetic islands reshape ITG growth rates and eigenfunctions, offering a physics‑based foundation for future nonlinear and control‑oriented research.