English
Related papers

Related papers: Tree tensor network hierarchical equations of moti…

200 papers

We introduce a numerical tensor-network method to compute the statistics of the charge transferred across an interface partitioning an interacting one-dimensional many-body lattice system with $U(1)$ symmetry. Our approach is based on a…

Quantum Physics · Physics 2026-04-01 Hari Kumar Yadalam , Mark T. Mitchison

A nonperturbative quantum impurity solver is proposed based on a formally exact hierarchical equations of motion (HEOM) formalism for open quantum systems. It leads to quantitatively accurate evaluation of physical properties of strongly…

Strongly Correlated Electrons · Physics 2014-08-04 Dong Hou , Rulin Wang , Xiao Zheng , NingHua Tong , JianHua Wei , YiJing Yan

The unavoidable coupling of quantum systems to external degrees of freedom leads to dissipative (non-unitary) dynamics, which can be radically different from closed-system scenarios. Such open quantum system dynamics is generally described…

Quantum Physics · Physics 2022-05-27 Álvaro Gómez-León , Tomás Ramos , Diego Porras , Alejandro González-Tudela

We present a hierarchical equations of motion approach, which allows a numerically exact simulation of nonequilibrium transport in general open quantum systems involving multiple macroscopic bosonic and fermionic environments. The…

Statistical Mechanics · Physics 2021-06-18 Jakob Bätge , Yaling Ke , Christoph Kaspar , Michael Thoss

Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. This approach typically relies on deep circuits and is therefore hampered by the substantial…

Quantum Physics · Physics 2022-01-06 Alexander Miessen , Pauline J. Ollitrault , Ivano Tavernelli

Dissipaton-equation-of-motion (DEOM) theory [Y. J. Yan, J. Chem. Phys. 140, 054105 (2014)] is an exact and nonperturbative many-particle method for open quantum systems. The existing dissipaton algebra treats also the dynamics of hybrid…

Chemical Physics · Physics 2020-01-24 Yao Wang , Rui-Xue Xu , YiJing Yan

Quantum computing offers the potential for computational abilities that can go beyond classical machines. However, they are still limited by several challenges such as noise, decoherence, and gate errors. As a result, efficient classical…

Quantum Physics · Physics 2025-09-01 Aditya Dubey , Zeki Zeybek , Peter Schmelcher

The Non-Markovian Stochastic Schrodinger Equation (NMSSE) offers a promising approach for open quantum simulations, especially in large systems, owing to its low scaling complexity and suitability for parallel computing. However, its…

Quantum Physics · Physics 2024-11-26 Kaihan Lin , Xing Gao

We present a computationally tractable scheme of time-dependent transport phenomena within open-boundary time-dependent density-functional-theory. Within this approach all the response properties of a system are determined from the…

Other Condensed Matter · Physics 2009-11-11 S. Kurth , G. Stefanucci , C. -O. Almbladh , A. Rubio , E. K. U. Gross

The transfer tensor method (TTM) [Cerrillo and Cao, Phys. Rev. Lett. 2014, 112, 110401] can be considered a discrete-time formulation of the Nakajima-Zwanzig quantum master equation (NZ-QME) for modeling non-Markovian quantum dynamics. A…

Quantum Physics · Physics 2025-07-30 Ruojing Peng , Lachlan P. Lindoy , Joonho Lee

We analyze and discuss convergence properties of a numerically exact algorithm tailored to study the dynamics of interacting two-dimensional lattice systems. The method is based on the application of the time-dependent variational principle…

Strongly Correlated Electrons · Physics 2020-11-11 Benedikt Kloss , Yevgeny Bar Lev , David R. Reichman

An iterative approach is introduced, which allows the efficient solution of the hierarchical equations of motion (HEOM) for the steady state of open quantum systems. The approach combines the method of matrix equations with an efficient…

Mesoscale and Nanoscale Physics · Physics 2021-07-15 Christoph Kaspar , Michael Thoss

Non-Markovian dynamics arising from the strong coupling of a system to a structured environment is essential in many applications of quantum mechanics and emerging technologies. Deriving an accurate description of general quantum dynamics…

We investigate the disordered spin-$\frac12$Heisenberg model in two dimensions and employ tree tensor networks (TTNs) with a physics-informed structural optimization of the tree layout, to simulate dynamics in the many-body localization…

Disordered Systems and Neural Networks · Physics 2025-12-23 Lars Humpert , Dante M. Kennes , Jan-Niklas Herre

This paper is concerned with variational methods for nonlinear open quantum systems with Markovian dynamics governed by Hudson-Parthasarathy quantum stochastic differential equations. The latter are driven by quantum Wiener processes of the…

Quantum Physics · Physics 2016-11-17 Igor G. Vladimirov

In this work, we present the tree tensor network Nystr\"om (TTNN), an algorithm that extends recent research on streamable tensor approximation, such as for Tucker and tensor-train formats, to the more general tree tensor network format,…

Numerical Analysis · Mathematics 2024-12-10 Alberto Bucci , Gianfranco Verzella

This work presents a unified dissipaton-equation-of-motion (DEOM) theory and its evaluations on the Helmholtz free energy change due to the isotherm mixing of two isolated subsystems. One is a local impurity and another is a nonlocal…

Statistical Mechanics · Physics 2021-11-19 Hong Gong , Yao Wang , Hou-Dao Zhang , Qin Qiao , Rui-Xue Xu , Xiao Zheng , YiJing Yan

Tree tensor networks (TTNs) provide a compact and structured representation of high-dimensional data, making them valuable in various areas of computational mathematics and physics. In this paper, we present a rigorous mathematical…

Numerical Analysis · Mathematics 2026-04-28 Junyuan He , Zhonghao Sun , Jizu Huang

We introduce a class of quantum non-Markovian processes -- dubbed process trees -- that exhibit polynomially decaying temporal correlations and memory distributed across time scales. This class of processes is described by a tensor network…

Quantum Physics · Physics 2024-10-24 Neil Dowling , Kavan Modi , Roberto N. Muñoz , Sukhbinder Singh , Gregory A. L. White

This work presents a data-driven reduced-order modeling framework to accelerate the computations of $N$-body dynamical systems and their pair-wise interactions. The proposed framework differs from traditional acceleration methods, like the…

Computational Engineering, Finance, and Science · Computer Science 2022-04-13 Steven N. Rodriguez , Athanasios P. Iliopoulos , Kevin T. Carlberg , Steven L. Brunton , John C. Steuben , John G. Michopoulos
‹ Prev 1 4 5 6 7 8 10 Next ›