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Perturbational Decomposition Analysis for Quantum Ising Model with Weak Transverse Fields
Youning Li1, Junfeng Huang1, Chao Zhang2
1College of Science, China Agriculture University, Beijing 100083, China.
A new perturbational decomposition method enhances quantum simulations of the 1D Ising model. This approach offers improvements over standard Trotter methods in specific parameter regimes, guiding simulation strategy selection.
Area of Science:
- Quantum mechanics
- Condensed matter physics
- Computational physics
Background:
- The one-dimensional Ising model is a fundamental model in statistical mechanics.
- Simulating quantum evolution accurately is crucial for understanding complex physical systems.
- Conventional Trotter decomposition methods have limitations in certain parameter regimes.
Purpose of the Study:
- To develop and present a novel perturbational decomposition method for simulating quantum evolution.
- To investigate the effectiveness of this method for the one-dimensional Ising model with longitudinal and transverse fields.
- To identify parameter regimes and evolution time windows where the new method outperforms conventional approaches.
Main Methods:
- A perturbational decomposition method is introduced, treating transverse field terms as perturbations.
- The method is applied to the one-dimensional Ising model with both longitudinal and transverse fields.
- Systematic numerical exploration is employed to characterize performance.
Main Results:
- The perturbational decomposition method shows measurable improvements over conventional Trotter decomposition.
- Effectiveness is particularly noted in systems with moderate longitudinal fields and weak to moderate transverse fields relative to coupling strength.
- Specific parameter regimes and evolution time windows for optimal performance are identified.
Conclusions:
- The developed perturbational approach offers a more effective simulation strategy for specific parameter regimes of the 1D Ising model.
- Characterized parameter spaces provide practical guidance for selecting simulation methods.
- This work contributes to advancing computational techniques in quantum many-body systems.
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