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A well-known approach to describe the dynamics of an open quantum system is to compute the master equation evolving the reduced density matrix of the system. This approach plays an important role in describing excitation transfer through…

Quantum Physics · Physics 2022-10-25 Kimara Naicker , Ilya Sinayskiy , Francesco Petruccione

This article reviews the concepts and methods of variational path sampling. These methods allow computational studies of rare events in systems driven arbitrarily far from equilibrium. Based upon a statistical mechanics of trajectory space…

Chemical Physics · Physics 2025-02-05 Aditya N. Singh , Avishek Das , David T. Limmer

For many physical quantities, theory supplies weak- and strong-coupling expansions of the types $\sum a_n \alpha ^n$ and $ \alpha ^p\sum b_n (\alpha^{-2/q) ^n$, respectively. Either or both of these may have a zero radius of convergence. We…

Quantum Physics · Physics 2009-10-28 H. Kleinert

Quantum information processing relies on how dynamics unfold in open quantum systems. In this work, we study the non-Markovian dynamics in the single mode spin-boson model at strong couplings. In order to apply perturbation theory, we…

Quantum Physics · Physics 2025-01-03 Rayees A Mala , Mehboob Rashid , Muzaffar Qadir Lone

We develop a perturbation theory of quantum (and classical) master equations with slowly varying parameters, applicable to systems which are externally controlled on a time scale much longer than their characteristic relaxation time. We…

Quantum Physics · Physics 2017-08-09 Vasco Cavina , Andrea Mari , Vittorio Giovannetti

We present numerical solutions to the extended Doering-Constantin variational principle for upper bounds on the energy dissipation rate in turbulent plane Couette flow. Using the compound matrix technique in order to reformulate this…

Soft Condensed Matter · Physics 2009-10-31 Rolf Nicodemus , Siegfried Grossmann , Martin Holthaus

This article investigates the problem of dynamic spectrum access for canonical wireless networks, in which the channel states are time-varying. In the most existing work, the commonly used optimization objective is to maximize the…

Information Theory · Computer Science 2017-07-31 Yuhua Xu , Jinlong Wang , Qihui Wu , Jianchao Zheng , Liang Shen , Alagan Anpalagan

We develop variational continuous unitary transformations (VCUTs), which integrate Wegner-Wilson flow equations with tensor network techniques to approximately diagonalize many-body localized (MBL) Hamiltonians. The diagonalizing unitary is…

Disordered Systems and Neural Networks · Physics 2026-03-16 Qiyu Liu , Jan-Niklas Herre , Dante M. Kennes , Christoph Karrasch

We extend the ability of unitary quantum circuits by interfacing it with classical autoregressive neural networks. The combined model parametrizes a variational density matrix as a classical mixture of quantum pure states, where the…

Quantum Physics · Physics 2020-01-16 Jin-Guo Liu , Liang Mao , Pan Zhang , Lei Wang

Motivated by experiments on chains of superconducting qubits, we consider the dynamics of a classical Klein-Gordon chain coupled to coherent driving and subject to dissipation solely at its boundaries. As the strength of the boundary…

Statistical Mechanics · Physics 2023-03-20 Abhinav Prem , Vir B. Bulchandani , S. L. Sondhi

In this manuscript, we show how flow equation methods can be used to study localisation in disordered quantum systems, and particularly how to use this approach to obtain the non-equilibrium dynamical evolution of observables. We review the…

Disordered Systems and Neural Networks · Physics 2020-02-27 S. J. Thomson , M. Schiró

This work discusses a variational approach to determining the time evolution operator. We directly see a glimpse of how a generalization of the quantum geometric tensor for unitary operators plays a central role in parameter evolution. We…

Quantum Physics · Physics 2025-04-15 Michael Vogl

We study classical stochastic systems with discrete states, coupled to switching external environments. For fast environmental processes we derive reduced dynamics for the system itself, focusing on corrections to the adiabatic limit of…

Statistical Mechanics · Physics 2019-03-27 Peter G. Hufton , Yen Ting Lin , Tobias Galla

It is known that the same physical system can be described by different effective theories depending on the scale at which it is observed. In this work, we formulate a prescription for finding the unitary that best approximates the large…

Quantum Physics · Physics 2026-02-17 Antonio F. Rotundo , Paolo Perinotti , Alessandro Bisio

In this paper, we consider linear boundary port-Hamiltonian distributed parameter systems on a time-varying spatial domain. We derive the specific time-varying Dirac structure that these systems give rise to and use it to formally establish…

Optimization and Control · Mathematics 2025-07-17 T. J. Meijer , A. Das , S. Weiland

The widespread deployment of power electronic technologies is transforming modern power systems into fast, nonlinear, and heterogeneous networks. Conventional modeling and control approaches, rooted in quasi-static analysis and centralized…

Systems and Control · Electrical Eng. & Systems 2026-03-31 Hiya Gada , Rupamathi Jaddivada , Marija Ilic

We derive Markovian master equations of single and interacting harmonic systems in different scenarios, including strong internal coupling. By comparing the dynamics resulting from the corresponding Markovian master equations with exact…

Quantum Physics · Physics 2010-11-18 Ángel Rivas , A. Douglas K. Plato , Susana F. Huelga , Martin B. Plenio

There have been assertions in the literature that the variational and unitary forms of coupled cluster theory lead to the same energy functional. Numerical evidence from previous authors was inconsistent with this claim, yet the small…

Strongly Correlated Electrons · Physics 2020-05-14 Gaurav Harsha , Toru Shiozaki , Gustavo E. Scuseria

Forecasting tasks using large datasets gathering thousands of heterogeneous time series is a crucial statistical problem in numerous sectors. The main challenge is to model a rich variety of time series, leverage any available external…

Machine Learning · Computer Science 2024-04-18 Etienne David , Jean Bellot , Sylvain Le Corff

To make predictions or design control, information on local sensitivity of initial conditions and state-space contraction is both central, and often instrumental. However, it is not always simple to reliably determine instability fields or…