English
Related papers

Related papers: Dynamics of Disordered Quantum Systems Using Flow …

200 papers

Motivated by a number of recent experimental and computational studies of the dynamics of fluids plunged in quenched-disordered external fields, we report on a theoretical investigation of this topic within the framework of the…

Soft Condensed Matter · Physics 2018-10-05 Thomas Konincks , Vincent Krakoviack

Disorder-free localization (DFL) is a phenomenon as striking as it appears to be simple: a translationally invariant state evolving under a disorder-free Hamiltonian failing to thermalize. It is predicted to occur in a number of quantum…

The flow equation approach is a robust framework applicable to a broad class of singular SPDEs, including those with fractional Laplacians, throughout the entire subcritical regime. Inspired by Wilson's renormalization group, this method…

Probability · Mathematics 2025-11-11 Paweł Duch

We introduce a method to efficiently study the dynamical properties of many-body localized systems in the regime of strong disorder and weak interactions. Our method reproduces qualitatively and quantitatively the real-time evolution with a…

Disordered Systems and Neural Networks · Physics 2019-07-03 Giuseppe De Tomasi , Frank Pollmann , Markus Heyl

Gaining and understanding the flow dynamics have much importance in a wide range of disciplines, e.g. astrophysics, geophysics, biology, mechanical engineering and biomedical engineering. As a reliable way in practice, especially for…

Fluid Dynamics · Physics 2022-06-22 Hui Xu , Wei Zhang , Yong Wang

Understanding turbulence is the key to our comprehension of many natural and technological flow processes. At the heart of this phenomenon lies its intricate multi-scale nature, describing the coupling between different-sized eddies in…

Generative models are a promising tool to address the sampling problem in multi-body and condensed-matter systems in the framework of statistical mechanics. In this work, we show that normalizing flows can be used to learn a transformation…

Computational Physics · Physics 2022-08-23 Alessandro Coretti , Sebastian Falkner , Phillip Geissler , Christoph Dellago

Recent years have seen tremendous progress in the theoretical understanding of quantum systems driven dissipatively by coupling them to different baths at their edges. This was possible because of the concurrent advances in the models used…

Quantum Physics · Physics 2022-12-15 Gabriel T. Landi , Dario Poletti , Gernot Schaller

We develop a flow renormalization approach for periodically-driven quantum systems, which reveals prethermal dynamical regimes and associated timescales via direct correspondence between real time and flow time behavior. In this formalism,…

Quantum Physics · Physics 2021-03-16 Martin Claassen

In this work, we investigate the use of normalizing flows to model conditional distributions. In particular, we use our proposed method to analyze inverse problems with invertible neural networks by maximizing the posterior likelihood. Our…

Machine Learning · Computer Science 2019-11-07 Zhisheng Xiao , Qing Yan , Yali Amit

We present a Machine Learning approach to solve electronic quantum transport equations of one-dimensional nanostructures. The transmission coefficients of disordered systems were computed to provide training and test datasets to the…

Mesoscale and Nanoscale Physics · Physics 2015-06-18 Alejandro Lopez-Bezanilla , O. Anatole von Lilienfeld

In this paper, we explore the embedding of nonlinear dynamical systems into linear ordinary differential equations (ODEs) via the Carleman linearization method. Under dissipative conditions, numerous previous works have established rigorous…

Quantum Physics · Physics 2025-02-03 Hsuan-Cheng Wu , Jingyao Wang , Xiantao Li

Quantum computing has demonstrated potential for solving complex optimization problems; however, its application to spatial regionalization remains underexplored. Spatial contiguity, a fundamental constraint requiring spatial entities to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-03 Yunhan Chang , Amr Magdy , Federico M. Spedalieri

We study the Kondo effect in quantum dots in an out-of-equilibrium state due to an applied dc-voltage bias. Using the method of infinitesimal unitary transformations (flow equations), we develop a perturbative scaling picture that naturally…

Strongly Correlated Electrons · Physics 2010-03-22 Stefan Kehrein

The dynamics of a quantum system coupled to a classical environment and subject to constraints that drive it out of equilibrium is described. The evolution of the system is governed by the quantum-classical Liouville equation. Rather than…

Statistical Mechanics · Physics 2025-01-15 Jeremy Schofield , Raymond Kapral

We review evolutionary models on quantum graphs expressed by linear and nonlinear partial differential equations. Existence and stability of the standing waves trapped on quantum graphs are studied by using methods of the variational…

Analysis of PDEs · Mathematics 2022-06-15 Adilbek Kairzhan , Diego Noja , Dmitry E. Pelinovsky

In a one-dimensional (1D) disordered potential, quantum interferences leading to Anderson lo-calization are ubiquitous, such that all wave-functions are exponentially localized. Moreover, no phase transition toward delocalization is…

Atomic Physics · Physics 2020-04-08 G. Berthet , L. Lavoine , M. Parit , A. Brolis , A. Boissé , T. Bourdel

The concepts and methods used for the study of disordered systems have proven useful in the analysis of the evolution equations of quantum chromodynamics in the high-energy regime: Indeed, parton branching in the semi-classical…

High Energy Physics - Phenomenology · Physics 2015-07-06 Stephane Munier

We propose the Parity Flow formalism, a method for tracking the information flow in quantum circuits. This method adds labels to quantum circuit diagrams such that the action of Clifford gates can be understood as a recoding of quantum…

The theory of Gaussian quantum fluctuations around classical steady states in nonlinear quantum-optical systems (also known as standard linearization) is a cornerstone for the analysis of such systems. Its simplicity, together with its…