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We show how to construct a tensor network representation of the path integral for reduced staggered fermions coupled to a non-abelian gauge field in two dimensions. The resulting formulation is both memory and computation efficient because…

High Energy Physics - Lattice · Physics 2023-12-27 Muhammad Asaduzzaman , Simon Catterall , Yannick Meurice , Ryo Sakai , Goksu Can Toga

We study a tensor network formulation of the two dimensional lattice $\mathcal{N}=1$ Wess-Zumino model with Wilson derivatives for both fermions and bosons. The tensor renormalization group allows us to compute the partition function…

High Energy Physics - Lattice · Physics 2018-04-18 Ryo Sakai , Daisuke Kadoh , Yoshinobu Kuramashi , Yoshifumi Nakamura , Shinji Takeda , Yusuke Yoshimura

The study of lattice gauge theories with Monte Carlo simulations is hindered by the infamous sign problem that appears under certain circumstances, in particular at non-zero chemical potential. So far, there is no universal method to…

High Energy Physics - Lattice · Physics 2017-03-27 Mari Carmen Bañuls , Krzysztof Cichy , J. Ignacio Cirac , Karl Jansen , Stefan Kühn , Hana Saito

We perform a tensor network simulation of the (1+1)-dimensional $O(3)$ nonlinear $\sigma$-model with $\theta=\pi$ term. Within the Hamiltonian formulation, this field theory emerges as the finite-temperature partition function of a modified…

High Energy Physics - Lattice · Physics 2021-12-28 Wei Tang , X. C. Xie , Lei Wang , Hong-Hao Tu

The Hubbard model is an important tool to understand the electrical properties of various materials. More specifically, on the honeycomb lattice it is used to describe graphene predicting a quantum phase transition from a semimetal to a…

Strongly Correlated Electrons · Physics 2023-03-31 Johann Ostmeyer

Based on the scheme of variational Monte Carlo sampling, we develop an accurate and efficient two-dimensional tensor-network algorithm to simulate quantum lattice models. We find that Monte Carlo sampling shows huge advantages in dealing…

Strongly Correlated Electrons · Physics 2021-06-28 Wen-Yuan Liu , Yi-Zhen Huang , Shou-Shu Gong , Zheng-Cheng Gu

We present a tensor-network formulation for the strong-coupling expansion of QCD with staggered quarks at nonzero chemical potential, for arbitrary number of dimensions, colors, and flavors. We integrate out the gauge and quark degrees of…

High Energy Physics - Lattice · Physics 2026-04-14 Thomas Samberger , Jacques Bloch , Robert Lohmayer , Tilo Wettig

We study the two-dimensional square lattice Ising ferromagnet and antiferromagnet with a magnetic field by using tensor network method. Focusing on the role of guage fixing, we present the partition function in terms of a tensor network.…

Statistical Mechanics · Physics 2025-01-03 Myung-Hoon Chung

We have developed a tensor network approach to the two-dimensional fully frustrated classical XY spin model on the kagome lattice, and clarified the nature of the possible phase transitions of various topological excitations.We find that…

Strongly Correlated Electrons · Physics 2023-07-24 Feng-Feng Song , Guang-Ming Zhang

The structure of string-net lattice models, relevant as examples of topological phases, leads to a remarkably simple way of expressing their ground states as a tensor network constructed from the basic data of the underlying tensor…

Strongly Correlated Electrons · Physics 2009-03-01 O. Buerschaper , M. Aguado , G. Vidal

Tensor network states and parton wave functions are two pivotal methods for studying quantum many-body systems. This work connects these two subjects as we demonstrate that a variety of parton wave functions, such as projected Fermi sea and…

Strongly Correlated Electrons · Physics 2020-06-22 Ying-Hai Wu , Lei Wang , Hong-Hao Tu

We use the Grassmann tensor renormalization group method to investigate the $N_f=2$ Schwinger model with the staggered fermions in the presence of a $2\pi$ periodic $\theta$ term in a broad range of mass. The method allows us to deal with…

High Energy Physics - Lattice · Physics 2025-11-12 Hayato Kanno , Shinichiro Akiyama , Kotaro Murakami , Shinji Takeda

We propose a novel algorithm with a modified Tucker decomposition for tensor network that allows for efficiently and precisely calculating the ground state and thermodynamic properties of two-dimensional (2D) quantum spin lattice systems,…

Strongly Correlated Electrons · Physics 2011-12-13 Shi-Ju Ran , Wei Li , Gang Su

We show that gauge invariant quantum link models, Abelian and non-Abelian, can be exactly described in terms of tensor networks states. Quantum link models represent an ideal bridge between high-energy to cold atom physics, as they can be…

Quantum Gases · Physics 2014-06-10 E. Rico , T. Pichler , M. Dalmonte , P. Zoller , S. Montangero

We show the feasibility of tensor network solutions for lattice gauge theories in Hamiltonian formulation by applying matrix product states algorithms to the Schwinger model with zero and non-vanishing fermion mass. We introduce new…

High Energy Physics - Lattice · Physics 2013-12-10 M. C. Bañuls , K. Cichy , K. Jansen , J. I. Cirac

We investigate the $N_f=2$ Schwinger model with the massive staggered fermions in the presence of a $2\pi$ periodic $\theta$ term, using the Grassmann tensor renormalization group. Thanks to the Grassmann tensor network formulation, there…

High Energy Physics - Lattice · Physics 2025-01-27 Hayato Kanno , Shinichiro Akiyama , Kotaro Murakami , Shinji Takeda

We discuss simulation strategies for the massless lattice Schwinger model with a topological term and finite chemical potential. The simulation is done in a dual representation where the complex action problem is solved and the partition…

High Energy Physics - Lattice · Physics 2018-04-18 Daniel Göschl

One of the challenging problems in the condensed matter physics is to understand the quantum many-body systems, especially, their physical mechanisms behind. Since there are only a few complete analytical solutions of these systems, several…

Statistical Mechanics · Physics 2020-03-27 Jozef Genzor , Tomotoshi Nishino , Andrej Gendiar

Trial wavefunctions that can be represented by summing over locally-coupled degrees of freedom are called tensor network states (TNSs); they have seemed difficult to construct for two-dimensional topological phases that possess protected…

Mesoscale and Nanoscale Physics · Physics 2015-11-25 J. Dubail , N. Read

Tensor Network methods have been established as a powerful technique for simulating low dimensional strongly-correlated systems for over two decades. Employing the formalism of Matrix Product States, we investigate the phase diagram of the…

High Energy Physics - Lattice · Physics 2017-10-30 Mari Carmen Bañuls , Krzysztof Cichy , Ying-Jer Kao , C. -J. David Lin , Yu-Ping Lin , David Tao-Lin Tan
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