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Several concrete examples in quantum information are discussed to demonstrate the importance of proper modeling that relates the mathematical description to real-world applications. In particular, it is shown that some commonly accepted…

Quantum Physics · Physics 2007-05-23 Horace P. Yuen

Basic problems of the semiclassical microscopic modelling of strongly interactingsystems are discussed within the framework of Quantum Molecular Dynamics (QMD). This model allows to study the influence of several types of nucleonic…

Nuclear Theory · Physics 2014-11-18 C. Hartnack , Rajeev K. Puri , J. Aichelin , J. Konopka , S. A. Bass , H. Stoecker , W. Greiner

Based on the boson realization of the Euclidean algebras, it is shown that the five-dimensional Euclidean dynamical symmetry may emerge at the triple point of the shape phase diagram of the interacting boson model, which thus offers a…

Nuclear Theory · Physics 2014-12-31 Yu Zhang , Feng Pan , Yu-xin Liu , Yan-an Luo , J. P. Draayer

Quasiprobability representations are well-established tools in quantum information science, with applications ranging from the classical simulability of quantum computation to quantum process tomography, quantum error correction, and…

Incorporating symmetries into the numerical solution of differential equations has been a mainstay of research over the last 40 years, however, one aspect is less known and under-utilised: discretisations of partial differential equations…

Numerical Analysis · Mathematics 2025-10-16 Sheehan Olver

Dynamical systems with quadratic or polynomial drift exhibit complex dynamics, yet compared to nonlinear systems in general form, are often easier to analyze, simulate, control, and learn. Results going back over a century have shown that…

Symbolic Computation · Computer Science 2025-02-17 Boris Kramer , Gleb Pogudin

Any representation of data involves arbitrary investigator choices. Because those choices are external to the data-generating process, each choice leads to an exact symmetry, corresponding to the group of transformations that takes one…

Machine Learning · Statistics 2023-06-29 Soledad Villar , David W. Hogg , Weichi Yao , George A. Kevrekidis , Bernhard Schölkopf

Supersymmetry is one of the most plausible and theoretically motivated frameworks for extending the Standard Model. However, any supersymmetry in Nature must be a broken symmetry. Dynamical supersymmetry breaking (DSB) is an attractive idea…

High Energy Physics - Theory · Physics 2008-11-26 Yael Shadmi , Yuri Shirman

Learning disentangled representations is a key step towards effectively discovering and modelling the underlying structure of environments. In the natural sciences, physics has found great success by describing the universe in terms of…

Machine Learning · Computer Science 2020-10-27 Robin Quessard , Thomas D. Barrett , William R. Clements

The reduction of dynamical systems has a rich history, with many important applications related to stability, control and verification. Reduction of nonlinear systems is typically performed in an exact manner - as is the case with…

Optimization and Control · Mathematics 2007-07-26 Paulo Tabuada , Aaron D. Ames , Agung Julius , George J. Pappas

Quasistatics is introduced so that it fits smoothly into the standard textbook presentation of electrodynamics. The usual path from statics to general electrodynamics is rather short and surprisingly simple. A closer look reveals however…

General Physics · Physics 2015-06-26 Jonas Larsson

Systems with long range interactions display some anomalies when its dynamics and thermodynamics are studied below certain conditions. Among these anomalies are the quasi- stationary states, which are exacerbated because of special initial…

Statistical Mechanics · Physics 2017-02-15 Boris Atenas , Sergio Curilef

The relevance of the partial dynamical symmetry concept for an interacting fermion system is demonstrated. Hamiltonians with partial SU(3) symmetry are presented in the framework of the symplectic shell-model of nuclei and shown to be…

Nuclear Theory · Physics 2011-07-19 Jutta Escher , Amiram Leviatan

Prediction models that capture and use the structure of state-space dynamics can be very effective. In practice, however, one rarely has access to full information about that structure, and accurate reconstruction of the dynamics from…

Chaotic Dynamics · Physics 2016-03-01 Joshua Garland , Elizabeth Bradley

The unreduced, universally nonperturbative analysis of arbitrary interaction process, described by a quite general equation, provides the truly complete, "dynamically multivalued" general solution that leads to dynamically derived,…

General Physics · Physics 2007-05-23 Andrei P. Kirilyuk

The vast majority of the literature dealing with quantum dynamics is concerned with linear evolution of the wave function or the density matrix. A complete dynamical description requires a full understanding of the evolution of measured…

In the late 1980's Sullivan initiated a programme to prove quasisymmetric rigidity in one-dimensional dynamics: interval or circle maps that are topologically conjugate are quasisymmetrically conjugate (provided some obvious necessary…

Dynamical Systems · Mathematics 2018-05-24 Trevor Clark , Sebastian van Strien

This paper aims at presenting a few models of quantum dynamics whose description involves the analysis of random unitary matrices for which dynamical localization has been proven to hold. Some models come from physical approximations…

Mathematical Physics · Physics 2011-05-03 Alain Joye

Mathematical descriptions of dynamical systems are deeply rooted in topological spaces defined by non-Euclidean geometry. This paper proposes leveraging structure-rich geometric spaces for machine learning to achieve structural…

Machine Learning · Computer Science 2025-02-20 Zack Xuereb Conti , David J Wagg , Nick Pepper

Rigid bodies, plastic impact, persistent contact, Coulomb friction, and massless limbs are ubiquitous simplifications introduced to reduce the complexity of mechanics models despite the obvious physical inaccuracies that each incurs…

Robotics · Computer Science 2020-07-31 Aaron M. Johnson , Samuel A. Burden , Daniel E. Koditschek
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