English
Related papers

Related papers: Tree tensor network impurity solver based on Cayle…

200 papers

Quantum algorithms reformulate computational problems as quantum evolutions in a large Hilbert space. Most quantum algorithms assume that the time-evolution is perfectly unitary and that the full Hilbert space is available. However, in…

Quantum Physics · Physics 2024-09-26 Marcel Niedermeier , Jose L. Lado , Christian Flindt

We present a compendium of numerical simulation techniques, based on tensor network methods, aiming to address problems of many-body quantum mechanics on a classical computer. The core setting of this anthology are lattice problems in low…

Study of scattering process in the nonlocal interaction framework leads to an integro-differential equation. The purpose of the present work is to develop an efficient approach to solve this integro-differential equation with high degree of…

Nuclear Theory · Physics 2018-08-09 N. J. Upadhyay , A. Bhagwat

The Numerical Renormalization Group is used to solve quantum impurity problems, which describe magnetic impurities in metals, nanodevices, and correlated materials within DMFT. Here we present a simple generalization of the Wilson Chain,…

Strongly Correlated Electrons · Physics 2014-03-14 Andrew K. Mitchell , Martin R. Galpin , Samuel Wilson-Fletcher , David E. Logan , Ralf Bulla

Tensor network structure search (TN-SS) aims to automatically discover optimal network topologies and rank configurations for efficient tensor decomposition in high-dimensional data representation. Despite recent advances, existing TN-SS…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Maolin Wang , Bowen Yu , Sheng Zhang , Linjie Mi , Wanyu Wang , Yiqi Wang , Pengyue Jia , Xuetao Wei , Zenglin Xu , Ruocheng Guo , Xiangyu Zhao

An acceleration of continuous time quantum Monte Carlo (CTQMC) methods is a potentially interesting branch of work as they are matchless as impurity solvers of a density functional theory in combination with a dynamical mean field theory…

Strongly Correlated Electrons · Physics 2019-08-07 Taegeun Song , Hunpyo Lee

Entanglement is the fundamental difference between classical and quantum systems and has become one of the guiding principles in the exploration of high- and low-energy physics. The calculation of entanglement entropies in interacting…

Quantum Physics · Physics 2022-08-17 Patrick Emonts , Ivan Kukuljan

Entanglement purification protocols, designed to improve the fidelity of Bell states over quantum networks for inter-node communications, have attracted significant attention over the last few decades. These protocols have great potential…

Quantum Physics · Physics 2024-05-07 Yue Shi , Chenxu Liu , Samuel Stein , Meng Wang , Muqing Zheng , Ang Li

Tensor network states (TNS) are a promising but numerically challenging tool for simulating two-dimensional (2D) quantum many-body problems. We introduce an isometric restriction of the TNS ansatz that allows for highly efficient…

Strongly Correlated Electrons · Physics 2020-02-10 Michael P. Zaletel , Frank Pollmann

Quantum Entanglement is a fundamentally important resource in Quantum Information Science; however, generating it in practice is plagued by noise and decoherence, limiting its utility. Entanglement distillation and forward error correction…

Quantum Physics · Physics 2023-07-14 Vaishnavi L. Addala , Shu Ge , Stefan Krastanov

Finite-Hamiltonian impurity solvers provide direct real-frequency spectra and a natural route to enlarged impurity Hamiltonians, but their applicability is limited by the rapid Hilbert-space growth with the number of bath or other added…

Strongly Correlated Electrons · Physics 2026-05-11 Jeongmoo Lee , Ara Go

A defining feature of quantum many-body systems is the exponential scaling of the Hilbert space with the number of degrees of freedom. This exponential complexity na\"ively renders a complete state characterization, for instance via the…

Quantum Physics · Physics 2026-05-28 Dmytro Kolisnyk , Raimel A. Medina , Romain Vasseur , Maksym Serbyn

Feynman diagrams are an essential tool for simulating strongly correlated electron systems. However, stochastic quantum Monte Carlo sampling suffers from the sign problem, particularly when solving a multiorbital quantum impurity model.…

Strongly Correlated Electrons · Physics 2025-07-28 Hirone Ishida , Natsuki Okada , Shintaro Hoshino , Hiroshi Shinaoka

The quantum state preparation of probability distributions is an important subroutine for many quantum algorithms. When embedding $D$-dimensional multivariate probability distributions by discretizing each dimension into $2^n$ points, we…

Quantum Physics · Physics 2025-06-04 Hidetaka Manabe , Yuichi Sano

Optimization problems pose challenges across various fields. In recent years, quantum annealers have emerged as a promising platform for tackling such challenges. To provide a new perspective, we develop a heuristic tensor network (TN)…

Disordered Systems and Neural Networks · Physics 2025-06-17 Anna Maria Dziubyna , Tomasz Śmierzchalski , Bartłomiej Gardas , Marek M. Rams , Masoud Mohseni

The state-of-the-art deep neural networks (DNNs) have been widely applied for various real-world applications, and achieved significant performance for cognitive problems. However, the increment of DNNs' width and depth in architecture…

Machine Learning · Computer Science 2021-11-15 Xiao Peng Li , Qi Liu , Hing Cheung So

Tensor completion is a fundamental tool for incomplete data analysis, where the goal is to predict missing entries from partial observations. However, existing methods often make the explicit or implicit assumption that the observed entries…

Machine Learning · Statistics 2022-03-18 Yuning Qiu , Guoxu Zhou , Qibin Zhao , Shengli Xie

The quantification of the entanglement present in a physical system is of para\-mount importance for fundamental research and many cutting-edge applications. Currently, achieving this goal requires either a priori knowledge on the system or…

True-time-delay (TTD) beamformers can produce wideband, squint-free beams in both analog and digital signal domains, unlike frequency-dependent FFT beams. Our previous work showed that TTD beamformers can be efficiently realized using the…

Machine Learning · Computer Science 2025-03-27 Hansaka Aluvihare , Sivakumar Sivasankar , Xianqi Li , Arjuna Madanayake , Sirani M. Perera

A tensor decomposition approach for the solution of high-dimensional, fully nonlinear Hamilton-Jacobi-Bellman equations arising in optimal feedback control of nonlinear dynamics is presented. The method combines a tensor train approximation…

Optimization and Control · Mathematics 2021-03-17 Sergey Dolgov , Dante Kalise , Karl Kunisch