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Related papers: Mapping the Hubbard model to the t-J model using g…

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In this paper, the distinguishability of multipartite geometrically uniform quantum states obtained from a single reference state is studied in the symmetric subspace. We specially focus our attention on the unitary transformation in a way…

Quantum Physics · Physics 2015-03-24 M. A. Jafarizadeh , P. Sadeghi , d. Akhgar , P. Mahmoudi

We propose random tight-binding models that host macroscopically degenerate zero energy modes and belong to the unitary class. Specifically, we employ the molecular-orbital representation, where a Hamiltonian is constructed by a set of…

Mesoscale and Nanoscale Physics · Physics 2023-03-03 Tomonari Mizoguchi , Yasuhiro Hatsugai

We study spin-state transition and phase separation involving this transition based on the milti-orbital Hubbard model. Multiple spin states are realized by changing the energy separation between the two orbitals and the on-site Hund…

Strongly Correlated Electrons · Physics 2015-05-13 Ryo Suzuki , Tsutomu Watanabe , Sumio Ishihara

We introduce an unsupervised machine-learning framework that discovers optimally compressed representations of quantum many-body ground states. Using an autoencoder neural network architecture on data from $L$-site Fermi-Hubbard models, we…

Quantum Physics · Physics 2025-12-15 Felix Frohnert , Emiel Koridon , Stefano Polla

Using quantum Monte Carlo simulations, results of a strong-coupling expansion, and Luttinger liquid theory, we determine quantitatively the ground state phase diagram of the one-dimensional extended Hubbard model with on-site and…

Strongly Correlated Electrons · Physics 2009-11-10 A. W. Sandvik , L. Balents , D. K. Campbell

Diffusion Monte Carlo is one of the most accurate scalable many-body methods for solid state systems. However, to date, spin-orbit interactions have not been incorporated into these calcualtions at a first-principles level; only having been…

Materials Science · Physics 2020-03-04 Yueqing Chang , Lucas K. Wagner

We present a method incorporating biorthogonal orbital-optimization, symmetry projection, and double-occupancy screening with a non-unitary similarity transformation generated by the Gutzwiller factor $ n_{i\uparrow}n_{i\downarrow}$, and…

Strongly Correlated Electrons · Physics 2016-10-10 Jacob M. Wahlen-Strothman , Gustavo E. Scuseria

The application of functional integral methods and the Hubbard--Stratonovich transformation to the Hubbard model is discussed. For the attractive case, using a simple gauge transformation of the superconducting order parameter field, the…

Condensed Matter · Physics 2007-05-23 H. J. Schulz

A derivation of the t-J model of a highly-correlated solid is given starting from the general many-electron Hamiltonian with account of the non-orthogonality of atomic wave functions. Asymmetry of the Hubbard subbands (i.e. of ``electron''…

Strongly Correlated Electrons · Physics 2009-10-30 V. Yu. Irkhin

We consider the 2D Hubbard model in the strong-coupling case (U>>W) and at low electron density (nd^2<<1). We find an antibound state as a pole in the two-particle T-matrix. The contribution of this pole in the self-energy reproduces a…

Strongly Correlated Electrons · Physics 2015-05-28 M. Yu. Kagan , V. V. Val'kov , P. Woelfle

For an anyon model in two spatial dimensions described by a modular tensor category, the topological S-matrix encodes the mutual braiding statistics, the quantum dimensions, and the fusion rules of anyons. It is nontrivial whether one can…

Quantum Physics · Physics 2016-03-04 Jeongwan Haah

Effect of quantum fluctuations concerned with the orbital degrees of freedom is discussed for the model with SU(4) symmetry in one dimension. An effective Hamiltonian is derived from the orbitally degenerate Hubbard model at quarter…

Strongly Correlated Electrons · Physics 2009-10-31 Yasufumi Yamashita , Naokazu Shibata , Kazuo Ueda

Quantum Monte Carlo methods are used to study a quantum phase transition in a 1D Hubbard model with a staggered ionic potential (D). Using recently formulated methods, the electronic polarization and localization are determined directly…

Strongly Correlated Electrons · Physics 2009-10-31 Tim Wilkens , Richard M. Martin

We investigate the ground-state magnetism of a Hubbard model in a system consisting of a main frame (subsystem) and a particle bath (center sites). The hole doping in the main frame is controlled by adjusting the chemical potential of the…

Strongly Correlated Electrons · Physics 2025-05-09 Hiroaki Onishi , Seiji Miyashita

We study unfrustrated spin Hamiltonians that consist of commuting tensor products of Pauli matrices. Assuming translation-invariance, a family of Hamiltonians that belong to the same phase of matter is described by a map between modules…

Quantum Physics · Physics 2013-10-22 Jeongwan Haah

We reconsider the quantum inverse scattering approach to the one-dimensional Hubbard model and work out some of its basic features so far omitted in the literature. It is our aim to show that $R$-matrix and monodromy matrix of the Hubbard…

Statistical Mechanics · Physics 2009-10-28 Frank Göhmann , Shuichi Murakami

We study the ground state of the Hubbard model on a square lattice with two degenerate orbitals per site and at integer fillings as a function of onsite Hubbard repulsion $U$ and Hund's intra-atomic exchange coupling $J$. We use a…

Strongly Correlated Electrons · Physics 2021-12-08 Arun Kumar Maurya , Md. Tahir Hossain Sarder , Amal Medhi

Starting from a precise two-nucleon potential, we use the method of unitary transformations to construct an effective potential that involves only momenta less than a given maximal value. We describe this method for an S-wave potential of…

Nuclear Theory · Physics 2009-10-31 E. Epelbaoum , W. Glöckle , Ulf-G. Meißner

A new variational method is developed to calculate the ground state energy of Fermi systems with strong short-range correlations. A trial wave function of Gutzwiller's type contains additional variational parameters corresponding to…

Strongly Correlated Electrons · Physics 2009-09-25 Yu. B. Kudasov

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode…

Machine Learning · Computer Science 2014-04-10 Victor Kurbatsky , Nikita Tomin , Vadim Spiryaev , Paul Leahy , Denis Sidorov , Alexei Zhukov