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Detection of entanglement through partial knowledge of the quantum state is a challenge to implement efficiently. Here we propose a separability criterion for detecting bipartite entanglement in arbitrary dimensional quantum states using…

Quantum Physics · Physics 2024-05-28 Shruti Aggarwal , Satyabrata Adhikari , A. S. Majumdar

We study the entanglement in tripartite quantum systems by using the principal basis matrix representations of density matrices. Using the Schmidt decomposition and local unitary transformation, we first convert the general states to…

Quantum Physics · Physics 2023-10-13 Hui Zhao , Yu-Qiu Liu , Shao-Ming Fei , Zhi-Xi Wang , Naihuan Jing

A new O(N) algorithm based on a recursion method, in which the computational effort is proportional to the number of atoms N, is presented for calculating the inverse of an overlap matrix which is needed in electronic structure calculations…

Condensed Matter · Physics 2016-08-31 T. Ozaki

The fields of entanglement theory and tensor networks have recently emerged as central tools for characterising quantum phases of matter. In this article, we determine the entanglement structure of ground states of gapped symmetric quantum…

Quantum Physics · Physics 2025-10-16 Laurens Lootens , Clement Delcamp , Frank Verstraete

We develop a density matrix renormalization group (DMRG) algorithm for constrained quantum lattice models that successfully {\it{implements the local constraints as symmetries in the contraction of the matrix product states and matrix…

Strongly Correlated Electrons · Physics 2025-08-11 Ting-Tung Wang , Xiaoxue Ran , Zi Yang Meng

A variant of White's density matrix renormalisation group scheme which is designed to compute low-lying energies of one-dimensional quantum lattice models with a large number of degrees of freedom per site is described. The method is tested…

Condensed Matter · Physics 2009-10-31 R. J. Bursill

We propose a recursive lattice reduction framework for finding short non-zero vectors or dense sublattices of a lattice. The framework works by recursively searching for dense sublattices of dense sublattices (or their duals) with…

Data Structures and Algorithms · Computer Science 2025-04-22 Divesh Aggarwal , Thomas Espitau , Spencer Peters , Noah Stephens-Davidowitz

We introduce two methods for estimating the density matrix for a quantum system: Quantum Maximum Likelihood and Quantum Variational Inference. In these methods, we construct a variational family to model the density matrix of a mixed…

Quantum Physics · Physics 2019-04-15 Kyle Cranmer , Siavash Golkar , Duccio Pappadopulo

An interesting aspect of antiferromagnetic quantum spin ladders, with complete dimer coverings, is that the wave function can be recursively generated by estimating the number of coverings in the valence bond basis, which follow the fabled…

Quantum Physics · Physics 2019-02-05 Sudipto Singha Roy , Himadri Shekhar Dhar , Aditi Sen De , Ujjwal Sen

The quantum separability problem consists in deciding whether a bipartite density matrix is entangled or separable. In this work, we propose a machine learning pipeline for finding approximate solutions for this NP-hard problem in…

Quantum Physics · Physics 2023-12-12 Balthazar Casalé , Giuseppe Di Molfetta , Sandrine Anthoine , Hachem Kadri

When solving partial differential equations (PDEs) using finite difference or finite element methods, efficient solvers are required for handling large sparse linear systems. In this paper, a recursive sparse LU decomposition for matrices…

Numerical Analysis · Mathematics 2024-08-27 Zhu Xuanru , Lai Jun

By combining a parameterized Hermitian matrix, the realignment matrix of the bipartite density matrix $\rho$ and the vectorization of its reduced density matrices, we present a family of separability criteria, which are stronger than the…

Quantum Physics · Physics 2015-11-03 Shu-Qian Shen , Meng-Yuan Wang , Ming Li , Shao-Ming Fei

This paper presents an anomaly detection model that combines the strong statistical foundation of density-estimation-based anomaly detection methods with the representation-learning ability of deep-learning models. The method combines an…

Machine Learning · Computer Science 2022-11-17 Joseph Gallego-Mejia , Oscar Bustos-Brinez , Fabio A. González

This paper introduces a novel anomaly detection framework that combines the robust statistical principles of density-estimation-based anomaly detection methods with the representation-learning capabilities of deep learning models. The…

Machine Learning · Computer Science 2024-08-15 Joseph Gallego-Mejia , Oscar Bustos-Brinez , Fabio A. González

White's density matrix renormalization group ({DMRG}) method has been applied to an $S= 1/2 + 1/2$ composite-spin model, which can also be considered as a two-leg ladder model. By appropriate choices of the coupling constants this model…

Strongly Correlated Electrons · Physics 2009-10-31 Ors Legeza , Gabor Fath , Jeno Solyom

We extend our density matrix embedding theory (DMET) [Phys. Rev. Lett. 109 186404 (2012)] from lattice models to the full chemical Hamiltonian. DMET allows the many-body embedding of arbitrary fragments of a quantum system, even when such…

Strongly Correlated Electrons · Physics 2013-11-15 Gerald Knizia , Garnet Kin-Lic Chan

We have analytically obtained all the density matrix elements up to six lattice sites for the spin-1/2 Heisenberg XXZ chain at $\Delta=1/2$. We use the multiple integral formula of the correlation function for the massless XXZ chain derived…

Statistical Mechanics · Physics 2009-11-13 Jun Sato , Masahiro Shiroishi

We propose a method for reconstruction of the density matrix from measurable time-dependent (probability) distributions of physical quantities. The applicability of the method based on least-squares inversion is - compared with other…

Quantum Physics · Physics 2016-09-08 T. Opatrny , D. -G. Welsch , W. Vogel

The interplay between non-trivial band topology and strong electronic correlations is a central challenge in modern condensed matter physics. We investigate this competition on a two-leg ladder model with a p-wave-like hybridisation between…

Strongly Correlated Electrons · Physics 2025-11-13 Aminul Hussain , Nisa Ara , Rudranil Basu , Sudeshna Sen

Given in the title are two algorithms to compute the extreme eigenstate of a high-dimensional Hermitian matrix using the tensor train (TT) / matrix product states (MPS) representation. Both methods empower the traditional alternating…

Numerical Analysis · Mathematics 2014-12-02 Sergey V. Dolgov , Dmitry V. Savostyanov