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Classical simulation is essential in quantum algorithm development and quantum device verification. With the increasing complexity and diversity of quantum circuit structures, existing classical simulation algorithms need to be improved and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-15 Yaojian Chen , Zhaoqi Sun , Chengyu Qiu , Zegang Li , Yanfei Liu , Lin Gan , Xiaohui Duan , Guangwen Yang

Monte Carlo simulations are methods for simulating statistical systems. The aim is to generate a representative ensemble of configurations to access thermodynamical quantities without the need to solve the system analytically or to perform…

Statistical Mechanics · Physics 2015-06-19 Jean-Charles Walter , Gerard Barkema

A novel algorithm based on the optimized decimation of tensor networks with super-orthogonalization (ODTNS) that can be applied to simulate efficiently and accurately not only the thermodynamic but also the ground state properties of…

Statistical Mechanics · Physics 2015-06-05 Shi-Ju Ran , Wei Li , Bin Xi , Zhe Zhang , Gang Su

Dynamic tensor data are becoming prevalent in numerous applications. Existing tensor clustering methods either fail to account for the dynamic nature of the data, or are inapplicable to a general-order tensor. Also there is often a gap…

Machine Learning · Statistics 2018-09-17 Will Wei Sun , Lexin Li

We analyze the many-particle Schrodinger equation for fermions in a thermal ensemble by introducing an exponential operator expansion, defined in the context of thermofield dynamics. The expansion is optimized variationally at each time…

Statistical Mechanics · Physics 2020-01-10 Edward B. Baker

It is often assumed that for treating numerical (or experimental) data on continuous transitions the formal analysis derived from the Renormalization Group Theory can only be applied over a narrow temperature range, the "critical region";…

Statistical Mechanics · Physics 2015-05-20 I. A. Campbell , P. H. Lundow

Tensor network states provide an efficient class of states that faithfully capture strongly correlated quantum models and systems in classical statistical mechanics. While tensor networks can now be seen as becoming standard tools in the…

Quantum Physics · Physics 2022-09-27 A. Nietner , B. Vanhecke , F. Verstraete , J. Eisert , L. Vanderstraeten

High-temperature series are computed for a generalized $3d$ Ising model with arbitrary potential. Two specific ``improved'' potentials (suppressing leading scaling corrections) are selected by Monte Carlo computation. Critical exponents are…

Statistical Mechanics · Physics 2009-10-31 Massimo Campostrini , Andrea Pelissetto , Paolo Rossi , Ettore Vicari

We use network analysis to describe and characterize an archetypal quantum system - an Ising spin chain in a transverse magnetic field. We analyze weighted networks for this quantum system, with link weights given by various measures of…

Statistical Mechanics · Physics 2018-05-23 Bhuvanesh Sundar , Marc Andrew Valdez , Lincoln D. Carr , Kaden R. A. Hazzard

Evaluating a lattice path integral in terms of spectral data and matrix elements pertaining to a suitably defined quantum transfer matrix, we derive form-factor series expansions for the dynamical two-point functions of arbitrary local…

Statistical Mechanics · Physics 2023-11-03 Frank Göhmann , Karol K. Kozlowski , Mikhail D. Minin

We present a quantum Monte Carlo investigation of the finite-temperature phase diagram of the quantum dimer model on the square lattice. We use the sweeping cluster algorithm, which allows to implement exactly the dimer constraint,…

Strongly Correlated Electrons · Physics 2022-11-17 Bhupen Dabholkar , G. J. Sreejith , Fabien Alet

We introduce an approach for approximate real-time evolution of quantum systems using Tensor Renormalization Group (TRG) methods originally developed for imaginary time. We use Higher- Order TRG (HOTRG) to generate a coarse-grained time…

Quantum Physics · Physics 2024-11-11 Michael Hite , Yannick Meurice

We have discussed the tensor-network representation of classical statistical or interacting quantum lattice models, and given a comprehensive introduction to the numerical methods we recently proposed for studying the tensor-network…

Strongly Correlated Electrons · Physics 2013-05-29 H. H. Zhao , Z. Y. Xie , Q. N. Chen , Z. C. Wei , J. W. Cai , T. Xiang

The transverse-field Ising model on the Sierpi\'nski fractal, which is characterized by the fractal dimension $\log_2^{~} 3 \approx 1.585$, is studied by a tensor-network method, the Higher-Order Tensor Renormalization Group. We analyze the…

Statistical Mechanics · Physics 2018-12-19 Roman Krcmar , Jozef Genzor , Yoju Lee , Hana Čenčariková , Tomotoshi Nishino , Andrej Gendiar

We employ the numerical linked-cluster expansion to study finite-temperature properties of the uniform cubic lattice Hubbard model in the thermodynamic limit for a wide range of interaction strengths and densities. We carry out the…

Strongly Correlated Electrons · Physics 2016-09-13 Ehsan Khatami

The Ising-like anisotropy parameter $\delta$ in the Kondo necklace model is analyzed using the bond-operator method at zero and finite temperatures for arbitrary $d$ dimensions. A decoupling scheme on the double time Green's functions is…

Strongly Correlated Electrons · Physics 2009-11-13 D. Reyes , M. A. Continentino , Han-Ting Wang

The finite lattice method of series expansion has been used to extend low-temperature series for the partition function, order parameter and susceptibility of the spin-1 Ising model on the square lattice. A new formalism is described that…

High Energy Physics - Lattice · Physics 2011-07-19 I. G. Enting , A , J. Guttmann , I. Jensen

There has been considerable recent progress in identifying candidate materials for the transverse-field Ising chain (TFIC), a paradigmatic model for quantum criticality. Here, we study the local spin dynamical structure factor of different…

Strongly Correlated Electrons · Physics 2022-10-03 Jiahao Yang , Weishi Yuan , Takashi Imai , Qimiao Si , Jianda Wu , Márton Kormos

We consider a zero-temperature one-dimensional system of bosons interacting via the soft-shoulder potential in the continuum, typical of dressed Rydberg gases. We employ quantum Monte Carlo simulations, which allow for the exact calculation…

The large variation of datasets is a huge barrier for image classification tasks. In this paper, we embraced this observation and introduce the finite temperature tensor network (FTTN), which imports the thermal perturbation into the matrix…

Machine Learning · Computer Science 2021-04-27 Haoxiang Lin , Shuqian Ye , Xi Zhu