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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2509.10821 |
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| _version_ | 1866909786191167488 |
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| author | Soni, Rachana Singh, Navneet Pratap |
| author_facet | Soni, Rachana Singh, Navneet Pratap |
| contents | We present an approach to simulate the Schrödinger 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10821 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Simulating and Learning Quantum Evolution: A CTQW-ML Framework Soni, Rachana Singh, Navneet Pratap Quantum Physics We present an approach to simulate the Schrödinger 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. |
| title | Simulating and Learning Quantum Evolution: A CTQW-ML Framework |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2509.10821 |