Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.32033

Two-component Bayesian modeling in the data analysis of collective Thomson scattering

Akito Nakano·Kentaro Sakai·Hantao Ji·Lan Gao·Brandon K. Russell·Takeo Hoshi
View original source ↗Read source document ↗Export metadata ↓

Abstract

We apply Bayesian inference to the analysis of collective Thomson scattering (CTS) spectra, a diagnostic technique for determining local plasma parameters. Using the population annealing Monte Carlo (PAMC) method, we evaluate the posterior probability density functions (PDFs) for six plasma parameters. The analysis is performed separately for the ion acoustic wave (IAW) and electron plasma wave (EPW) features and jointly for both features. The results show that the combined analysis provides constraints on all six parameters, although the degree of constraint depends on the parameter, whereas the separate analyses provide strong constraints only on complementary subsets of the parameters. In particular, the combined analysis provides a clear constraint on the ion charge state, which is not determined by either separate analysis alone. These findings demonstrate the importance of Bayesian modeling that accounts for the two-component nature of plasmas, consisting of ions and electrons.

Explore related subjects

physics.plasm-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Akito Nakano, Kentaro Sakai, Hantao Ji, Lan Gao, Brandon K. Russell, Takeo Hoshi. 2026-10-23. Two-component Bayesian modeling in the data analysis of collective Thomson scattering. https://arxiv.org/abs/2610.32033

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Effects of Alfvénicity on the Compressible Energy Cascade in Magnetohydrodynamic Solar Wind Turbulence: Evidence from Parker Solar Probe, Solar Orbiter, and WIND observations

The compressible MHD energy cascade in the solar wind is shaped by Alfvénicity, plasma fluctuations, and proton temperature, yet how these factors regulate the relative weight of compressible and incompressible energy transfer across heliocentric distances remains poorly understood. We apply compressible and incompressible exact relations to a large sample of 2-hour intervals from WIND (1~au), Parker Solar Probe ($<0.25$~au), and Solar Orbiter (0.3--1~au), classifying intervals as Alfvénic ($|σ_c|>0.75$) or non-Alfvénic ($|σ_c|<0.25$) and by wind speed, and examine the Yaglom-like and purely compressible components of the compressible cascade. Velocity fluctuation amplitude is the strongest predictor of the compressible cascade rate $\langle|\varepsilon_c|\rangle$, followed by density and magnetic field fluctuations. $\langle|\varepsilon_c|\rangle$ and $\langle|\varepsilon_i|\rangle$ are tightly correlated in all regimes, with their ratio organized by Alfvénicity and wind speed: non-Alfvénic and Alfvénic fast winds cluster along $\langle|\varepsilon_c|\rangle=\langle|\varepsilon_i|\rangle$, while Alfvénic slow wind shows a systematic excess consistent with internal energy contributions. The largest $\langle|\varepsilon_c|\rangle$ systematically occur in hotter intervals, with a two-decade increase from cool to hot events in Alfvénic slow and non-Alfvénic wind, a trend carried mainly by the purely compressible term, while the dominant Yaglom-like term controls the overall cascade magnitude. Alfvénicity and wind speed thus govern the efficiency of turbulent energy transfer across heliocentric distances, and the tight coupling between compressible and incompressible rates points to the need for compressible, multi-fluid descriptions of the solar wind dissipation budget.

physics.plasm-ph↗
arXiv2026

ModeCast: One-Shot Prediction of Linear MHD Eigenmodes and Growth Rates in Tokamaks

Large-scale magnetohydrodynamic instabilities break plasma confinement, can trigger disruptions, and constrain fusion reactor design; modeling a single configuration against them takes hours with a reference solver such as JOREK, and a design study requires thousands of hours. ModeCast is the first learned surrogate to return the complete linear stability assessment for MHD modes. Trained on a comprehensive dataset of over 45,000 JOREK simulations across thousands of equilibria, it screens stability across toroidal mode numbers n=1-4 and predicts the full spatial structure and growth rate of unstable modes. With a second network of the same architecture replacing the equilibrium solve, the full pipeline from design parameters runs on one GPU up to 1,000,000x faster than JOREK's equilibrium and linear stability runs. The gain comes from building the linear-phase physics into the formulation, objective, and inputs, yielding up to six times more training data. ModeCast misses none of the unstable held-out cases, and its predicted fields reproduce the simulation's measured physics, from magnetic island topology to resistivity trends. On a fixed-geometry resistivity scan outside its training distribution, refitting only the 22k-parameter growth rate head of the 145M-parameter network on four simulation halves the held-out internal kink growth rate error, and fine-tuning the whole network adds little. Because it is differentiable and returns full fields, ModeCast could in the future assimilate experimental measurements, providing a bridge to real devices and accelerating progress toward commercial fusion. Project page: zenithon.ai/research/modecast.

physics.plasm-ph↗
arXiv2026

Plasma transport by carrier electrons: delocalization length for heat-flux

The delocalization length $λ_d=λ_{ei} Z/\sqrt{Z+4.45}$ is an improved heat-flux non-locality metric accounting for the localizing effect of electron-electron collisions on the electron population carrying heat-flux. Magnetization also localizes the carrier electrons; the delocalization Hall parameter $ψ_d=13.5 χZ/(Z+4.62)$ shows that this occurs at a faster rate than magnetization of thermal conductivity ($ψ_κ= 9.94χ(Z+0.17)/(Z+5.88)$). The traditional Knudsen number, which uses the electron-ion mean-free path, does not fairly represent non-locality across ionization and magnetization; $Kn_d = 8.28λ_{d\bot}/L_T$ should instead be used. The kinetic understanding of the three magnetized heat-flux components is unified in the linear regime with a full electron-electron collision operator and a converged harmonic expansion of the electron distribution (up to $f_6$). Righi-Leduc heat-flux is found to delocalize easier than its perpendicular counterpart, due to its carriers being higher energy electrons. This approach lays the groundwork for a consistent treatment of the kinetically-modified induction equation.

physics.plasm-ph↗