Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Hai-Jun Liao"'
Publikováno v:
Physical Review X, Vol 9, Iss 3, p 031041 (2019)
Differentiable programming is a fresh programming paradigm which composes parameterized algorithmic components and optimizes them using gradient search. The concept emerges from deep learning but is not limited to training neural networks. We present
Externí odkaz:
https://doaj.org/article/ddc7560ee545467ca47ac8ed964d2a53
Autor:
Xing-Jie Han, Yu Liu, Zhi-Yuan Liu, Xin Li, Jing Chen, Hai-Jun Liao, Zhi-Yuan Xie, B Normand, Tao Xiang
Publikováno v:
New Journal of Physics, Vol 18, Iss 10, p 103004 (2016)
We introduce a slave-fermion formulation in which to study the charge dynamics of the half-filled Hubbard model on the square lattice. In this description, the charge degrees of freedom are represented by fermionic holons and doublons and the Mott-in
Externí odkaz:
https://doaj.org/article/53036d7995ef436b90ec4f0cf1e0dbee
Publikováno v:
Physical Review B. 106
We investigate the physics of projected d-wave pairing states using their fermionic projected entangled pair state (fPEPS) representation. First, we approximate a d-wave Bardeen-Cooper-Schrieffer state using the Gaussian fPEPS. Next, we translate the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cf44d6e7306face13d2364f1f297005
http://arxiv.org/abs/2208.04566
http://arxiv.org/abs/2208.04566
We study the entanglement properties of non-Hermitian free fermionic models with translation symmetry using the correlation matrix technique. Our results show that the entanglement entropy has a logarithmic correction to the area law in both one-dime
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f383d271fc43f02ed0b130bcfce918bd
Autor:
Dong-Hong Xu, Yi-Cong Yu, Xing-Jie Han, Xi Chen, Kang Wang, Ming-Pu Qin, Hai-Jun Liao, Tao Xiang
Publikováno v:
Chinese Physics Letters. 39:067403
We propose an extended BCS–Hubbard model and investigate its ground state phase diagram in an external magnetic field. By mapping the model onto a model of spinless fermions coupled with conserving Z 2 variables which are mimicked by pseudospins, t
We perform the state-of-the-art tensor network simulations directly in the thermodynamic limit to clarify the critical properties of the $q$-state clock model on the square lattice. We determine accurately the two phase transition temperatures throug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43898213a5e408715dc270bc63aa047f
http://arxiv.org/abs/1912.11416
http://arxiv.org/abs/1912.11416
Autor:
Hai-Jun Liao, Hui-Hai Zhao, Wei Li, Yuzhi Liu, Zhi-Yuan Xie, Y. Q. Guo, Lei Wang, Bin-Bin Chen, Tao Xiang, Yuan Gao
Tensor renormalization group (TRG) constitutes an important methodology for accurate simulations of strongly correlated lattice models. Facilitated by the automatic differentiation technique widely used in deep learning, we propose a uniform framewor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2886e0a8b5e9b177e0628b27678f6cb
http://arxiv.org/abs/1912.02780
http://arxiv.org/abs/1912.02780
Publikováno v:
Physical Review X, Vol 9, Iss 3, p 031041 (2019)
Differentiable programming is a fresh programming paradigm which composes parameterized algorithmic components and trains them using automatic differentiation (AD). The concept emerges from deep learning but is not only limited to training neural net
Autor:
Xing-Jie Han, Hai-Jun Liao, Hai-Dong Xie, Jing Chen, Rui-Zhen Huang, Chuang Chen, Tao Xiang, Zi Yang Meng, Bruce Normand
The Mott insulator is the quintessential strongly correlated electronic state. We obtain complete insight into the physics of the two-dimensional Mott insulator by extending the slave-fermion (holon-doublon) description to finite temperatures. We fir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d7e0373282b4b234e795f74b2943c7b
http://arxiv.org/abs/1808.09994
http://arxiv.org/abs/1808.09994