A Dough-Like Model for Understanding Double-Slit Phenomena

The probabilistic interference fringes observed in the double slit experiment vividly demonstrate the quantum superposition principle, yet they also highlight a fundamental conceptual challenge: the relationship between a system before and after the measurement. According to Copenhagen interpretation, an unobserved quantum system evolves continuously based on the Schrodinger equation, whereas observation induces an instantaneous collapse of the wave function to an eigenstate. This contrast between continuous evolution and sudden collapse renders the single particle behavior particularly enigmatic, especially given that quantum mechanics itself is constructed upon the statistical behavior of ensembles rather than individual entities. In this study, we introduce a Double Slit Diffraction Surrogate Model DSM based on deep learning, designed to capture the mapping between wave functions and probability distributions. The DSM explores multiple potential propagation paths and adaptively selects optimal transmission channels using gradient descent, forming a backbone for the information through the network. By comparing the interpretability of paths and interference, we propose an intuitive physical analogy: the particle behaves like a stretchable dough, extending across both slits, reconnecting after transmission, allowing detachment before the barrier. Monte Carlo simulations confirm that this framework can naturally reproduce the characteristic interference and diffraction probability patterns. Our approach offers a novel, physically interpretable perspective on quantum superposition and measurement induced collapse. The dough analogy is expected to extend to other quantum phenomena. Finally, we provide a dough based picture, attempting to unify interference, entanglement, and tunneling as manifestations of the same underlying phenomenon.