Open access
Jul 2026
Fractional Physics Informed Neural Networks for Surrogate Modeling of Non-Markovian Discrete-Time Quantum Walks
FracPINN is introduced, a fractional physics-informed neural network that embeds a fully differentiable, PyTorch-based Caputo PDE solver into a classical LSTM encoder, and acts as a compact physics regularizer that constrains the inference with emergent fractional transport dynamics.
Zhaoyu Zhu, Ming-Xin Liu, Chengtian Liang et al.
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