Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving PDEs, fractional equations, and eigenvalue problems, making them particularly suited for quantum mechanics, where traditional numerical methods often face computational bottlenecks. The aim of this internship is to analyse the applicability of PINNs to a broad range of quantum simulation tasks such as […]
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