A Study of the Phase Diagram of the Hubbard Model Using Modern Numerical Methods, M.Sc. Thesis Sharif University of Technology ; Vaezi, Mir Abolhassan (Supervisor)
Abstract
The Hubbard model is one of the simplest interacting models in theoretical physics, especially condensed matter physics which despite its simplicity, its solutions are highly nontrivial and intractable. After 5 decades since its introduction, its phase diagram is not fully understood and whether or not, it has a high-temperature superconducting phase. In this thesis, we aim to employ the recent advances in machine learning and GPU programming to accelerate the QMC method. By accelerated QMC methods, we can explore the Hubbard model's phase diagram more efficiently. Using massive parallelization of the GPUs can speed up the measuring process by several times. The self-learning quantum...
Cataloging briefA Study of the Phase Diagram of the Hubbard Model Using Modern Numerical Methods, M.Sc. Thesis Sharif University of Technology ; Vaezi, Mir Abolhassan (Supervisor)
Abstract
The Hubbard model is one of the simplest interacting models in theoretical physics, especially condensed matter physics which despite its simplicity, its solutions are highly nontrivial and intractable. After 5 decades since its introduction, its phase diagram is not fully understood and whether or not, it has a high-temperature superconducting phase. In this thesis, we aim to employ the recent advances in machine learning and GPU programming to accelerate the QMC method. By accelerated QMC methods, we can explore the Hubbard model's phase diagram more efficiently. Using massive parallelization of the GPUs can speed up the measuring process by several times. The self-learning quantum...
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