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Published as a conference paper at NeurIPS 2026

Inverse Modeling for Laser Pulse Shape Design in Inertial Confinement Fusion

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

Abstract

The achievement of practical fusion energy remains one of the most pressing unsolved scientific challenges, with immense implications for carbon-free power. A critical factor in the success of Inertial Confinement Fusion (ICF) is the design of a Laser Pulse Shape (LP) that can optimally drive implosions under stringent physical constraints. Traditional LP design relies on computationally expensive simulations and manual iterative refinement. We introduce the ICF Laser Pulse Shape Design System (LPDS), a generative inverse modeling framework that maps desired outcomes and target pellet configurations directly to optimized LPs. Crucially, we design a multi-objective loss function to ensure the generated LPs adhere to fundamental physical constraints and experimental feasibility. Furthermore, we present constraint-conditioning, inpainting, and gradient-based LP editing mechanisms for maximum fine-grained control over specific pulse characteristics during generation. Moreover, we validate our framework for LP design on a real-world experimental data. Our method establishes a data-driven inverse design framework for LP in ICF, contributing to the advancement of practical and sustainable fusion energy.

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