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Action-dependent field theories are systems where the Lagrangian or Hamiltonian depends on new variables that encode the action. They model a larger class of field theories, including non-conservative behavior, while maintaining a…

High Energy Physics - Theory · Physics 2025-05-01 Manuel de León , Jordi Gaset Rifà , Miguel C. Muñoz-Lecanda , Xavier Rivas , Narciso Román-Roy

A first-principles approach to describe electron dynamics in open quantum systems driven far from equilibrium via external time-dependent stimuli is introduced. Within this approach, the driven Liouville von Neumann methodology is used to…

Mesoscale and Nanoscale Physics · Physics 2023-05-10 Annabelle Oz , Abraham Nitzan , Oded Hod , Juan E. Peralta

These lecture notes present a computation driven pathway from classical complex analysis to the theory of compact Riemann surfaces and their connections to algebraic geometry. The exposition follows a compute first then abstract philosophy,…

We develop a generic method in Liouville space to describe the dissipative dynamics of coherent interacting quantum dots with adiabatic time dependence beyond linear response. We show how the adiabatic response can be related to effective…

Mesoscale and Nanoscale Physics · Physics 2012-07-25 Oleksiy Kashuba , Herbert Schoeller , Janine Splettstoesser

We develop a nonperturbative dynamical theory (NDT) that is useful for treating nonequilibrium transport in a system with strong correlation. We apply our NDT to the single-impurity Anderson model in equilibrium to check its reliability by…

Strongly Correlated Electrons · Physics 2011-11-09 Jongbae Hong , Wonmyung Woo

The dynamic linear response of a quantum system is critical for understanding both the structure and dynamics of strongly-interacting quantum systems, including neutron scattering from materials, photon and electron scattering from atomic…

Quantum Physics · Physics 2019-09-18 Alessandro Roggero , Joseph Carlson

Linear typed $\lambda$-calculi are more delicate than their simply typed siblings when it comes to metatheoretic results like preservation of typing under renaming and substitution. Tracking the usage of variables in contexts places more…

Programming Languages · Computer Science 2022-01-03 James Wood , Robert Atkey

This note provides a comprehensive examination of the various approaches to formulating relativistic hydrodynamics, with a particular emphasis on the canonical approach. Relativistic hydrodynamics plays a crucial role in understanding the…

High Energy Physics - Theory · Physics 2025-02-11 Luca Martinoia , Rajeev Singh

The authors give a detailed information about symmetry (Lie, non-Lie, conditional) of nonlinear PDEs for spinor, vector and scalar fields; using advanced methods of group-theoretical, symmetry analysis construct wide families of classical…

Mathematical Physics · Physics 2007-05-23 Wilhelm Fushchych , Renat Zhdanov

We apply the linear $\delta$-expansion (LDE), originally developed as a nonperturbative, analytical approximation scheme in quantum field theory, to problems involving noninteracting electrons in disordered solids. The initial idea that the…

Disordered Systems and Neural Networks · Physics 2009-10-30 M. P. Blencowe , A. P. Korte

The Kubo-Ando theory deals with connections for positive bounded operators. On the other hand, in various analysis related to von Neumann algebras it is impossible to avoid unbounded operators. In this article we try to extend a notion of…

Operator Algebras · Mathematics 2021-02-03 Fumio Hiai , Hideki Kosaki

Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physics-based methods related to Koopman theory has been introduced, offering…

Computational Physics · Physics 2020-07-01 Omri Azencot , N. Benjamin Erichson , Vanessa Lin , Michael W. Mahoney

Changing some of its parameters over time is a paradigmatic way of driving an otherwise isolated many-body quantum system out of equilibrium, and a vital ingredient for building quantum computers and simulators. Here, we further develop a…

Quantum Physics · Physics 2024-11-06 Lennart Dabelow , Peter Reimann

The universe is smooth on large scales but very inhomogeneous on small scales. Why is the spacetime on large scales modeled to a good approximation by the Friedmann equations? Are we sure that small-scale non-linearities do not induce a…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-18 Daniel Baumann , Alberto Nicolis , Leonardo Senatore , Matias Zaldarriaga

This survey is meant to provide an introduction to the fundamental theorem of linear algebra and the theories behind them. Our goal is to give a rigorous introduction to the readers with prior exposure to linear algebra. Specifically, we…

Machine Learning · Computer Science 2022-07-29 Jun Lu

The existence and analyticity of solutions to linear systems of moment differential equations with analytic coefficients is studied. The relation of solutions of such systems with respect to linear moment differential equations is…

Classical Analysis and ODEs · Mathematics 2025-01-09 Alberto Lastra

This work connects two mathematical fields - computational complexity and interval linear algebra. It introduces the basic topics of interval linear algebra - regularity and singularity, full column rank, solving a linear system, deciding…

Computational Complexity · Computer Science 2016-02-02 Jaroslav Horáček , Milan Hladík , Michal Černý

This paper analyzes the nonlinear correspondence between the reflectivity profile (model) and the plane wave impulse response at the boundary (data) for a three-dimensional half space consisting of a sequence of homogeneous horizontal…

Mathematical Physics · Physics 2012-06-14 Peter C. Gibson

The electromagnetic fields in Maxwell's theory satisfy linear equations in the classical vacuum. This is modified in classical non-linear electrodynamic theories. To date there has been little experimental evidence that any of these…

Mathematical Physics · Physics 2015-05-14 T. Dereli , R. W. Tucker

We present a novel data-driven approach for learning linear representations of a class of stable nonlinear systems using Koopman eigenfunctions. By learning the conjugacy map between a nonlinear system and its Jacobian linearization through…

Machine Learning · Computer Science 2022-05-31 Petar Bevanda , Johannes Kirmayr , Stefan Sosnowski , Sandra Hirche