Ab-Initio Approach to Many-Body Quantum Spin Dynamics

• URL: http://arxiv.org/abs/2411.13190v3
• Date: Mon, 17 Feb 2025 14:21:15 GMT
• Title: Ab-Initio Approach to Many-Body Quantum Spin Dynamics
• Authors: Aditya Dubey, Zeki Zeybek, Fabian Köhler, Rick Mukherjee, Peter Schmelcher,
• Abstract summary: We use the multilayer multiconfiguration time-dependent Hartree framework to simulate the many-body spin dynamics of the Heisenberg model. Benchmarks with analytical and exact numerical approaches show that ML-MCTDH accurately captures the time evolution of one- and two-body observables. The behavior of the corresponding entanglement dynamics is analyzed to reveal the complexity of the quantum states.
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• Abstract: A fundamental longstanding problem in studying spin models is the efficient and accurate numerical simulation of the long-time behavior of larger systems. The exponential growth of the Hilbert space and the entanglement accumulation at long times pose major challenges for current methods. To address these issues, we employ the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) framework to simulate the many-body spin dynamics of the Heisenberg model in various settings, including the Ising and XYZ limits with different interaction ranges and random couplings. Benchmarks with analytical and exact numerical approaches show that ML-MCTDH accurately captures the time evolution of one- and two-body observables in both one- and two-dimensional lattices. A comparison with the discrete truncated Wigner approximation (DTWA) highlights that ML-MCTDH is particularly well-suited for handling anisotropic models and provides more reliable results for two-point observables across all tested cases. The behavior of the corresponding entanglement dynamics is analyzed to reveal the complexity of the quantum states. Our findings indicate that the rate of entanglement growth strongly depends on the interaction range and the presence of disorder. This particular relationship is then used to examine the convergence behavior of ML-MCTDH. Our results indicate that the multilayer structure of ML-MCTDH is a promising numerical framework for handling the dynamics of generic many-body spin systems.

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