arXiv AI July 14, 2026 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

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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning

Jun 4

Causal Multi-fidelity Surrogate Forward and Inverse Models for ICF Implosions

arXiv:2509. 05510v3 Announce Type: replace-cross Abstract: Continued progress in inertial confinement fusion (ICF) requires solving inverse problems relating experimental observations to simulation input parameters, followed by design optimization.

By Tyler E. Maltba, Ben S. Southworth, Jeffrey R. Haack, Marc L. Klasky

rag safety

arXiv Machine Learning

Jun 5

PI-JEPA: Label-Free Surrogate Pretraining for Coupled Multiphysics Simulation via Operator-Split Latent Prediction

arXiv:2604. 01349v4 Announce Type: replace Abstract: Reservoir simulation workflows face a fundamental data asymmetry: input parameter fields (geostatistical permeability realizations, porosity distributions) are free to generate in arbitrary quantities, yet existing neural operator surrogates require large corpora of expensive labeled simulation trajectories and cannot exploit this unlabeled structure.

By Brandon Yee, Pairie Koh

rag fine-tuning

arXiv Machine Learning

Jun 8

ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics

arXiv:2604. 01313v2 Announce Type: replace Abstract: High-fidelity simulations and complex inverse problems, such as detector modeling and unfolding, are computationally intensive bottlenecks across subatomic physics, yet essential for accurate physical interpretation.

By Zeyu Xia, Tyler Kim, Trevor Reed, Judy Fox, Geoffrey Fox, Adam Szczepaniak

diffusion benchmarks

arXiv AI

Jun 12

TokaMark: A Comprehensive Benchmark for MAST Tokamak Plasma Models

arXiv:2602. 10132v3 Announce Type: replace-cross Abstract: Development and operation of commercially viable fusion energy reactors such as tokamaks require accurate predictions of plasma dynamics from sparse, noisy, and incomplete sensors readings.

By C\'ecile Rousseau, Samuel Jackson, Rodrigo H. Ordonez-Hurtado, Nicola C. Amorisco, Tobia Boschi, George K. Holt, Andrea Loreti, Eszter Sz\'ekely, Alexander Whittle, Adriano Agnello, Stanislas Pamela, Alessandra Pascale, Robert Akers, Juan Bernabe Moreno, Sue Thorne, Mykhaylo Zayats

multimodal benchmarks

arXiv AI

Jun 9

Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark

arXiv:2606. 07550v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) offers a promising route for developing plasma controllers from historical tokamak data, since online trial-and-error on real devices is costly and risky.

By Yang Fu, Haomin Bao, Rohit Sonker, Xiaoyan Hu, Aravind Venugopal, Jeff Schneider, Jiayu Chen

reinforcement-learning benchmarks

arXiv AI

Jun 8

TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics

arXiv:2602. 15084v2 Announce Type: replace-cross Abstract: We present TokaMind, to our knowledge the first open-source foundation model for tokamak plasma dynamics, based on a Multi-Modal Transformer (MMT) and pretrained on heterogeneous diagnostics from the publicly available MAST dataset.

By Tobia Boschi, Andrea Loreti, Nicola C. Amorisco, Rodrigo H. Ordonez-Hurtado, C\'ecile Rousseau, George K. Holt, Eszter Sz\'ekely, Alexander Whittle, Samuel Jackson, Adriano Agnello, Stanislas Pamela, Alessandra Pascale, Robert Akers, Juan Bernabe Moreno, Vassil Alexandrov, Mykhaylo Zayats

llms rag fine-tuning multimodal benchmarks

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Causal Multi-fidelity Surrogate Forward and Inverse Models for ICF Implosions

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TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics