Identification of magnetic field errors in synchrotrons based on deep Lie map networks

Article Physics, Nuclear

Differentiable self-consistent space-charge simulation for accelerator design

Ji Qiang

Summary: Nonlinear space-charge effects can significantly affect the beam properties in high intensity or high brightness accelerators. This paper proposes a differentiable self-consistent space-charge simulation model that allows the study of sensitivity in accelerator design parameters through only one simulation. This model connects the beam properties directly with the design parameters, enabling computation of local derivatives during simulation and facilitating accelerator design optimizations.

PHYSICAL REVIEW ACCELERATORS AND BEAMS (2023)

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Article Thermodynamics

Physics-Informed Neural Networks for Heat Transfer Problems

Shengze Cai et al.

Summary: Physics-informed neural networks (PINNs) have gained popularity in engineering fields for their effectiveness in solving realistic problems with noisy data and partially missing physics. Through automatic differentiation to evaluate differential operators and defining a multitask learning problem, PINNs have been applied to various heat transfer problems, bridging the gap between computational and experimental heat transfer.

JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME (2021)

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Article Physics, Nuclear