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We present and test a protocol to learn the matrix-product operator (MPO) representation of an experimentally prepared quantum state. The protocol takes as an input classical shadows corresponding to local randomized measurements, and…

In this work, we combine an established method for open quantum systems -- the time evolving density matrix using orthogonal polynomials algorithm (TEDOPA) -- with the transfer tensors formalism (TTM), a new tool for the analysis,…

Quantum Physics · Physics 2016-02-25 Robert Rosenbach , Javier Cerrillo , Susana F. Huelga , Jianshu Cao , Martin Bodo Plenio

We introduce a matrix product operator (MPO) encoding of the Magnus expansion and the Dyson series for one-dimensional quantum lattice models with time-dependent Hamiltonians. The MPO construction can be made accurate up to arbitrary order…

This is a set of lectures on tensor networks with a strong emphasis on the core algorithms involving Matrix Product States (MPS) and Matrix Product Operators (MPO). Compared to other presentations, particular care has been given to…

Quantum Physics · Physics 2026-01-07 Xavier Waintal , Chen-How Huang , Christoph W. Groth

This research introduces an improved framework for constructing matrix product operators (MPOs) and tree tensor network operators (TTNOs), crucial tools in quantum simulations. A given (Hamiltonian) operator typically has a known symbolic…

Quantum Physics · Physics 2025-07-04 Hazar Çakır , Richard M. Milbradt , Christian B. Mendl

Open quantum systems (OQS's) are ubiquitous in non-equilibrium quantum dynamics and in quantum science and technology. Solving the dynamics of an OQS in a quantum many-body bath has been considered a computationally hard problem because of…

Quantum Physics · Physics 2025-09-03 Chong Chen , Ren-Bao Liu

We use the free evolution propagator to determine the quantum probability representation (i.e., the general expression of the tomogram) of any one-dimensional system described by a density state. The evolution operator for the considered…

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…

Strongly Correlated Electrons · Physics 2020-04-29 Hui-Ke Jin , Hong-Hao Tu , Yi Zhou

Open many-body quantum systems play an important role in quantum optics and condensed-matter physics, and capture phenomena like transport, interplay between Hamiltonian and incoherent dynamics, and topological order generated by…

Quantum Physics · Physics 2016-06-15 A. H. Werner , D. Jaschke , P. Silvi , M. Kliesch , T. Calarco , J. Eisert , S. Montangero

Recent years have seen rapid advances in the data-driven analysis of dynamical systems based on Koopman operator theory and related approaches. On the other hand, low-rank tensor product approximations -- in particular the tensor train (TT)…

Numerical Analysis · Mathematics 2021-08-11 Feliks Nüske , Patrick Gelß , Stefan Klus , Cecilia Clementi

We show how to simulate numerically both the evolution of 1D quantum systems under dissipation as well as in thermal equilibrium. The method applies to both finite and inhomogeneous systems and it is based on two ideas: (a) a representation…

Other Condensed Matter · Physics 2007-05-23 F. Verstraete , J. J. Garcia-Ripoll , J. I. Cirac

TENSO is a versatile and powerful open-source software package for numerically exact simulations of the dynamics of quantum systems immersed in structured thermal environments. It is based on a tree tensor network decomposition of the…

Problems in the field of open quantum systems often involve an environment that strongly influences the dynamics of excited states. Here we present a numerical method to model optical spectra of non-Markovian open quantum systems. The…

Quantum Physics · Physics 2025-05-01 Roosmarijn de Wit , Jonathan Keeling , Brendon W. Lovett , Alex W. Chin

Path-integral techniques are a powerful tool used in open quantum systems to provide an exact solution for the non-Markovian dynamics. However, the exponential scaling of the tensor size with quantum memory length of these techniques limits…

Quantum Physics · Physics 2025-08-25 L. M. J. Hall , A. Gisdakis , E. A. Muljarov

We propose a new method for computing the ground state properties and the time evolution of infinite chains based on a transverse contraction of the tensor network. The method does not require finite size extrapolation and avoids explicit…

Quantum Physics · Physics 2009-06-29 M. C. Bañuls , M. B. Hastings , F. Verstraete , J. I. Cirac

It is shown that the exact dynamics of a composite quantum system can be represented through a pair of product states which evolve according to a Markovian random jump process. This representation is used to design a general Monte Carlo…

Quantum Physics · Physics 2007-05-23 Heinz-Peter Breuer

We present a collection of methods to simulate entangled dynamics of open quantum systems governed by the Lindblad equation with tensor network methods. Tensor network methods using matrix product states have been proven very useful to…

Quantum Gases · Physics 2018-11-09 Daniel Jaschke , Simone Montangero , Lincoln D. Carr

Quantum collision models are receiving increasing attention as they describe many nontrivial phenomena in dynamics of open quantum systems. In a general scenario of both fundamental and practical interest, a quantum system repeatedly…

Quantum Physics · Physics 2022-06-07 Sergey N. Filippov , Ilia A. Luchnikov

Simulating many-body open quantum systems is an extremely challenging problem, with methods often restricted to either models with nearest-neighbor interactions or semi-classical approximations. In particular, modeling two-dimensional…

Quantum Physics · Physics 2025-12-02 Jack Dunham , Marzena H. Szymańska

Modern approaches to generative modeling of continuous data using tensor networks incorporate compression layers to capture the most meaningful features of high-dimensional inputs. These methods, however, rely on traditional Matrix Product…

Machine Learning · Computer Science 2024-12-11 Danylo Kolesnyk , Yelyzaveta Vodovozova