arXiv AI By Jiatong Zhao, Tengyue Zhang, Yuhan Wang, Fuyuan Wu, Junchi Yan

Co4ICF: Co-evolving Physics-Informed Surrogate and RL-based Pulse Optimizer for Inertial Confinement Fusion

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arXiv:2607. 10366v1 Announce Type: new Abstract: Offline-trained surrogates for Inertial Confinement Fusion (ICF) suffer a well-known failure mode that iterative optimizers drive inputs into out-of-distribution (OOD) regions where predictions become unreliable.

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arXiv AI
Oct 27

Inverse Modeling for Laser Pulse Shape Design in Inertial Confinement Fusion

The paper introduces the ICF Laser Pulse Shape Design System (LPDS), a generative inverse modeling framework that directly maps desired fusion outcomes and pellet configurations to optimized laser pulse shapes. It incorporates a multi-objective loss function to enforce physical constraints and experimental requirements, and offers tools such as constraint-conditioning, inpainting, and gradient-based editing for fine-grained pulse control. The authors also demonstrate the framework’s applicability to a limited set of real experimental shots, positioning LPDS as a data-driven approach to advance practical inertial confinement fusion.

By Ricardo Luna Gutierrez, Vineet Gundecha, Rahman Ejaz, Varchas Gopalaswamy, Riccardo Betti, Sahand Ghorbanpour, Aarne Lees, Soumyendu Sarkar