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We develop analytical tools and numerical methods for time evolving the total density matrix of the finite-size Anderson model. The model is composed of two finite metal grains, each prepared in canonical states of differing chemical…

介观与纳米尺度物理 · 物理学 2015-06-11 Manas Kulkarni , Kunal L Tiwari , Dvira Segal

(Please refer to arXiv:1810.08050, which has completely different aims but contains all the main contents of this paper) In this work, we propose to access the information of criticality and excitations of one-dimensional quantum systems by…

强关联电子 · 物理学 2018-10-22 Emanuele Tirrito , Luca Tagliacozzo , Maciej Lewenstein , Shi-Ju Ran

Numerical methods for obtaining exact dynamics of non-Markovian open quantum systems are mostly limited to either small systems or to short-time evolution only. Here, we propose a new algorithm for computing process tensors--matrix product…

量子物理 · 物理学 2026-03-10 Émile Cochin , Jonathan Keeling , Brendon W. Lovett , Alex W. Chin

Tensor network, which originates from quantum physics, is emerging as an efficient tool for classical and quantum machine learning. Nevertheless, there still exists a considerable accuracy gap between tensor network and the sophisticated…

机器学习 · 计算机科学 2023-06-07 Ye-Ming Meng , Jing Zhang , Peng Zhang , Chao Gao , Shi-Ju Ran

Tensor network states and specifically matrix-product states have proven to be a powerful tool for simulating ground states of strongly correlated spin models. Recently, they have also been applied to interacting fermionic problems,…

量子物理 · 物理学 2016-11-22 C. Krumnow , L. Veis , Ö. Legeza , J. Eisert

We study a quantum impurity coupled to the edge states of a two-dimensional helical topological superconductor, i.e., to a pair of counterpropagating Majorana fermion edge channels with opposite spin polarizations. For an impurity described…

强关联电子 · 物理学 2011-11-15 Rok Zitko , Pascal Simon

Modeling the joint distribution of high-dimensional data is a central task in unsupervised machine learning. In recent years, many interests have been attracted to developing learning models based on tensor networks, which have the…

统计力学 · 物理学 2023-02-02 Jing Liu , Sujie Li , Jiang Zhang , Pan Zhang

Tensor network states, and in particular projected entangled pair states, play an important role in the description of strongly correlated quantum lattice systems. They do not only serve as variational states in numerical simulation…

量子物理 · 物理学 2017-06-27 C. Wille , O. Buerschaper , J. Eisert

Thermodynamic properties are presented for four magnetic impurity models describing delocalized fermions scattering from a localized orbital at an energy-dependent rate $\Gamma(\epsilon)$ which vanishes precisely at the Fermi level,…

强关联电子 · 物理学 2009-10-31 Carlos Gonzalez-Buxton , Kevin Ingersent

We show that the presence of Fermi or non-Fermi liquid behavior in the SU(N) x SU(M) Anderson impurity models may be read off the infrared threshold exponents governing the spinon and holon dynamics in a slave boson representation of these…

强关联电子 · 物理学 2009-10-28 J. Kroha , P. Wölfle , T. A. Costi

We describe how to implement the time-dependent variational principle for matrix product states in the thermodynamic limit for nonuniform lattice systems. This is achieved by confining the nonuniformity to a (dynamically growable) finite…

强关联电子 · 物理学 2013-10-18 Ashley Milsted , Jutho Haegeman , Tobias J. Osborne , Frank Verstraete

A natural way to generalise tensor network variational classes to quantum field systems is via a continuous tensor contraction. This approach is first illustrated for the class of quantum field states known as continuous matrix-product…

The Grassmann time-evolving matrix product operator method has shown great potential as a general-purpose quantum impurity solver, as its numerical errors can be well-controlled and it is flexible to be applied on both the imaginary- and…

强关联电子 · 物理学 2025-10-08 Zhijie Sun , Ruofan Chen , Zhenyu Li , Chu Guo

We discuss the transient effects in the Anderson impurity model that occur when two fermionic continua with finite bandwidths are instantaneously coupled to a central level. We present results for the analytically solvable noninteracting…

介观与纳米尺度物理 · 物理学 2008-12-11 T. L. Schmidt , P. Werner , L. Muehlbacher , A. Komnik

The question of Fermi liquid vs. non-Fermi liquid behavior induced by strong correlations is one of the prominent problems in metallic local moment systems. As standard models for such systems, the SU(N)xSU(M) Anderson impurity models…

强关联电子 · 物理学 2016-11-30 Johann Kroha , Peter W"olfle

Recent work by Wu {\em et al.} [arXiv:1910.11011] proposed a numerical method, so-called matrix product operator-matrix product state (MPO-MPS) method, by which several types of quantum many-body wave functions, in particular, the projected…

强关联电子 · 物理学 2020-04-29 Hui-Ke Jin , Hong-Hao Tu , Yi Zhou

Being able to study the dynamics of quantum systems interacting with several environments is important in many settings ranging from quantum chemistry to quantum thermodynamics, through out-of-equilibrium systems. For such problems tensor…

量子物理 · 物理学 2025-05-22 Thibaut Lacroix , Brendon W. Lovett , Alex W. Chin

Anderson localization is a fundamental phenomenon in disordered quantum systems, where transport is suppressed by wave interference from extensive randomness. Moving beyond traditional multi-impurity scenarios, we investigate…

无序系统与神经网络 · 物理学 2026-03-03 Niaz Ali Khan , Munsif Jan , Muzamil Shah , Muhammad Sajid , Muhammad Mateen , Mushtaq Ali

We present a tensorization algorithm for constructing tensor train/matrix product state (MPS) representations of functions, drawing on sketching and cross interpolation ideas. The method only requires black-box access to the target function…

Thermalizing and localized many-body quantum systems present two distinct dynamical phases of matter. Recently, the fate of a localized system coupled to a thermalizing system viewed as a quantum bath received significant theoretical and…

无序系统与神经网络 · 物理学 2022-07-13 Pietro Brighi , Alexios A. Michailidis , Kristina Kirova , Dmitry A. Abanin , Maksym Serbyn