Self-learning quantum Monte Carlo method in interacting fermion systems
The self-learning Monte Carlo method is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we extend it to an interacting fermion quantum system in the framework of the widely used determinant quantum Monte Carlo. This method can generally r...
| मुख्य लेखकों: | , , , , |
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| अन्य लेखक: | |
| स्वरूप: | लेख |
| भाषा: | English |
| प्रकाशित: |
American Physical Society
2017
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| ऑनलाइन पहुंच: | http://hdl.handle.net/1721.1/110782 https://orcid.org/0000-0001-8051-7349 https://orcid.org/0000-0002-8803-1017 |
| सारांश: | The self-learning Monte Carlo method is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we extend it to an interacting fermion quantum system in the framework of the widely used determinant quantum Monte Carlo. This method can generally reduce the computational complexity and moreover can greatly suppress the autocorrelation time near a critical point. This enables us to simulate an interacting fermion system on a 100×100 lattice even at the critical point and obtain critical exponents with high precision. |
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