arXiv · 2509.10821
Simulating and Learning Quantum Evolution: A CTQW-ML Framework
Abstract
We present an approach to simulate the Schr\"odinger equation through continuous time quantum walks. The CTQW-based simulation applies unitary evolution driven by a quantum walk to generate probability amplitude distributions at various time steps. Additionally, we implemented a supervised neural network model to evaluate the effectiveness of data-driven techniques. The model learns to predict the squared modulus of the wavefunction given spatial and temporal coordinates. A comparative analysis demonstrates that the ML model can reproduce the qualitative structure and temporal progression of the quantum system with high accuracy. This study provides the synergy between quantum walk-based simulation and machine learning for solving quantum dynamical equations.
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Rachana Soni, Navneet Pratap Singh. 2025-09-13. Simulating and Learning Quantum Evolution: A CTQW-ML Framework. https://arxiv.org/abs/2509.10821
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