arXiv subjects

Jeremy Lore

Publications and source records attributed to Jeremy Lore.

4 recordsLinked to original sources

arXiv2026

WSINDy for Model Predictive Control with Applications to Fusion, Drones, and Chaos

The control of complex dynamical systems remains a fundamental challenge in science and engineering, where strong nonlinearities, the presence of noise, and computational constraints often pose significant obstacles in traditional control approaches. Recent advances in data-driven methods, particularly system identification techniques, have shown a powerful alternative by providing fast, parsimonious, interpretable models that are well-suited for model predictive control (MPC). Building on these developments, the present article embeds WSINDy with actuation inputs (WSINDYc) within a MPC framework. Compared to benchmark data-driven methods, WSINDYc enables a more robust identification of the governing dynamics, particularly in the presence of high noise levels, resulting in more accurate and efficient control. The capabilities of the proposed WSINDY-MPC framework are demonstrated on a range of problems, including a tokamak plasma boundary model that includes main ion gas puff actuation, drone tracking and collision avoidance, the chaotic Lorenz system, and a simplified flight control model for an F-8 aircraft. The proposed framework achieves superior performance in the presence of noise, enabling longer prediction horizons, lower trajectory tracking error, and a more reliable obstacle clearance, while simultaneously achieving lower MPC cost values compared to the baseline methods.

math.DS↗

arXiv2025

Autoregressive long-horizon prediction of plasma edge dynamics

Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1-100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.

physics.plasm-ph↗

arXiv2024

Conceptual Design of a Doppler Spectrometer for 10$^2$ m/s Cross-Field Flows in Tokamak Divertors

It has been theoretically predicted that the \ExB drift caused by the spontaneously generated potential in scrape-off-layers (SOLs) and divertors in tokamaks is of a similar size to the poloidal component of the parallel flow and turbulent flow, thereby it significantly impacts on the plasma transport there. Many experiments indeed have implied the role of the electric potential, however, its direct observation through its \ExB flow measurement has never been realized because the drift velocity ($10^2$--$10^3$ m/s) is significantly below the detection limit of existing diagnostics. To realize a cross-field ion flow measurement, variety of systematic uncertainties of the system must be narrowed down. Here, we develop a conceptual design of the Doppler spectrometry that enables to measure the impurity flows with $10^2$-m/s accuracy, based on an in-situ wavelength-calibration techniques developed in astrophysics field, the iodine-cell method. We discuss its properties and applicability. In particular, the scaling relation of the wavelength accuracy and various spectroscopic parameters is newly presented, which suggests the high importance of the wavelength resolution of the system. Based on transport simulations for the JT-60SA divertor, the feasibility of the system is assessed.

physics.plasm-ph↗

arXiv2021

An Efficient High-order Numerical Solver for Diffusion Equations with Strong Anisotropy

In this paper, we present an interior penalty discontinuous Galerkin finite element scheme for solving diffusion problems with strong anisotropy arising in magnetized plasmas for fusion applications. We demonstrate the accuracy produced by the high-order scheme and develop an efficient preconditioning technique to solve the corresponding linear system, which is robust to the mesh size and anisotropy of the problem. Several numerical tests are provided to validate the accuracy and efficiency of the proposed algorithm.

math.NA↗