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We propose a new tensor network renormalization group (TNR) scheme based on global optimization and introduce a new method for constructing the finite-temperature density matrix of two-dimensional quantum systems. Combining these two into a…

强关联电子 · 物理学 2026-05-13 Atsushi Ueda , Sander De Meyer , Adwait Naravane , Victor Vanthilt , Frank Verstraete

We introduce a coarse-graining transformation for tensor networks that can be applied to study both the partition function of a classical statistical system and the Euclidean path integral of a quantum many-body system. The scheme is based…

强关联电子 · 物理学 2015-11-04 Glen Evenbly , Guifre Vidal

We study the quantum phase diagram of the spin-$1/2$ nearest-neighbor Heisenberg model on the maple-leaf lattice using infinite projected entangled pair states (iPEPS) combined with a corner transfer matrix renormalization group scheme…

强关联电子 · 物理学 2025-12-24 Samuel Nyckees , Pratyay Ghosh , Frédéric Mila

We use the recently developed tensor network algorithm based on infinite projected entangled pair states (iPEPS) to study the phase diagram of frustrated antiferromagnetic J1-J2 Heisenberg model on a checkerboard lattice. The simulation…

强关联电子 · 物理学 2012-05-01 Yang-hao Chan , Yong-jian Han , Luming Duan

We present a spectroscopy scheme for the lattice field theory by using the tensor renormalization group method combining with the transfer matrix formalism. By using the scheme, we cannot only compute the energy spectrum for the lattice…

高能物理 - 格点 · 物理学 2024-08-29 Fathiyya Izzatun Az-zahra , Shinji Takeda , Takeshi Yamazaki

We present a functional renormalization group flow for many-fermion lattice models into phases with broken spin-rotational symmetry. The flow is expressed purely in terms of fermionic vertex functions. The symmetry breaking is seeded by a…

强关联电子 · 物理学 2012-10-11 Stefan A. Maier , Carsten Honerkamp

We present three dimensional realizations of the model introduced recently by (Karlin, B\"osch, Chikatamarla, Phys. Rev. E 2014) and review the role of the entropic stabilizer. The presented models achieve outstanding numerical stability in…

流体动力学 · 物理学 2015-07-10 Fabian Bösch , Shyam S. Chikatamarla , Ilya Karlin

We study phase transition in the ferromagnetic Potts model with invisible states that are added as redundant states by mean-field calculation and Monte Carlo simulation. Invisible states affect the entropy and the free energy, although they…

统计力学 · 物理学 2010-08-30 Ryo Tamura , Shu Tanaka , Naoki Kawashima

A universal (supervised) neural network (NN), which is only trained once on a one-dimensional lattice of 200 sites, is employed to study the phase transition of the two-dimensional (2D) 5-state ferromagnetic Potts model on the square…

统计力学 · 物理学 2021-11-30 Yuan-Heng Tseng , Yun-Hsuan Tseng , Fu-Jiun Jiang

Symmetry-protected topological (SPT) phases are short-range entangled phases of matter with a non-local order parameter which are preserved under a local symmetry group. Here, by using unsupervised learning algorithm, namely the diffusion…

强关联电子 · 物理学 2021-11-18 En-Jui Kuo , Hossein Dehghani

A ferromagnetic-paramagnetic phase transition of the two-dimensional frustrated Ising model on a hyperbolic lattice is investigated by use of the corner transfer matrix renormalization group method. The model contains ferromagnetic…

统计力学 · 物理学 2009-06-12 R. Krcmar , T. Iharagi , A. Gendiar , T. Nishino

Binary magnetic square lattice Ising system with nearest neighbour interactions were simulated using the Monte Carlo technique. Two types of ions were randomly distributed on the lattice sites, one type interacting ferromagnetic and the…

统计力学 · 物理学 2013-01-23 Ike Q. Sikakana

We accurately simulate the phase diagram and critical behavior of the $q$-state clock model on the square lattice by using the state-of-the-art loop optimization for tensor network renormalzation(loop-TNR) algorithm. The two phase…

统计力学 · 物理学 2023-12-05 Guanrong Li , Kwok Ho Pai , Zheng-Cheng Gu

Machine learning techniques such as artificial neural networks are currently revolutionizing many technological areas and have also proven successful in quantum physics applications. Here we employ an artificial neural network and deep…

Capturing the dynamics of active particles, i.e., small self-propelled agents that both deform and are deformed by a fluid in which they move is a formidable problem as it requires coupling fine scale hydrodynamics with large scale…

软凝聚态物质 · 物理学 2025-09-09 Sadra Saremi , Amirhossein Ahmadkhan Kordbacheh

We propose an iterative proposal to estimate critical points for statistical models based on configurations by combing machine-learning tools. Firstly, phase scenarios and preliminary boundaries of phases are obtained by…

无序系统与神经网络 · 物理学 2019-10-23 X. L. Zhao , L. B. Fu

We calculate the quantum Renyi entropy in a phase space representation for either fermions or bosons. This can also be used to calculate purity and fidelity, or the entanglement between two systems. We show that it is possible to calculate…

其他凝聚态物理 · 物理学 2015-05-28 Laura E. C. Rosales-Zárate , P. D. Drummond

We study the $q$ states Potts model with four site interaction on the square lattice. Based on the asymptotic behaviour of lattice animals, it is argued that when $q\leq 4$ the system exhibits a second-order phase transition, and when $q >…

统计力学 · 物理学 2018-03-14 Nir Schreiber , Reuven Cohen , Simi Haber

We construct an algorithm to simulate imaginary time evolution of translationally invariant spin systems with local interactions on an infinite, symmetric tree. We describe the state by symmetric iPEPS and use translation-invariant…

量子物理 · 物理学 2015-05-28 Adam Nagy

We study a model of two dimensional, topological superconductivity on a square lattice. The model contains hopping, spin orbit coupling and a time reversal symmetry breaking Zeeman term. This term, together with the chemical potential act…

强关联电子 · 物理学 2017-03-08 Jan Borchmann , T. Pereg-Barnea