Inverse Modeling for Laser Pulse Shape Design in Inertial Confinement Fusion

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

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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 satisfy fundamental physical constraints and experimental requirements. Furthermore, we present constraint-conditioning, inpainting, and gradient-based LP editing mechanisms for fine-grained control over specific pulse characteristics during generation. Moreover, we study the transfer of our framework to a limited set of real experimental shots. Our method establishes a data-driven inverse design framework for LP design in ICF, contributing to the advancement of practical and sustainable fusion energy.

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Initial version submitted to NeurIPS 2026 pending publication

Subjects:

Artificial Intelligence (cs.AI) ; Machine Learning (cs.LG); Systems and Control (eess.SY); High Energy Physics - Experiment (hep-ex)

Cite as:

arXiv:2610.33096 [cs.AI]

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arXiv:2610.33096v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2610.33096

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arXiv-issued DOI via DataCite

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From: Soumyendu Sarkar [ view email ]

[v1]

Thu, 22 Oct 2026 10:06:42 UTC (1,569 KB)

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