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Modelling is an essential procedure in analyzing and controlling a given logical dynamic system (LDS). It has been proved that deterministic LDS can be modeled as a linear-like system using algebraic state space representation. However, due…

Optimization and Control · Mathematics 2022-03-04 Changxi Li , Jun-e Feng , Daizhan Cheng , Xiao Zhang

Mode-based model-reduction is used to reduce the degrees of freedom of high dimensional systems, often by describing the system state by a linear combination of spatial modes. Transport dominated phenomena, ubiquitous in technical and…

Numerical Analysis · Mathematics 2020-02-28 Julius Reiss

Stochastic processes have found numerous applications in science, as they are broadly used to model a variety of natural phenomena. Due to their intrinsic randomness and uncertainty, they are, however, difficult to characterize. Here, we…

Holographic representations of data encode information in packets of equal importance that enable progressive recovery. The quality of recovered data improves as more and more packets become available. This progressive recovery of the…

Information Theory · Computer Science 2021-03-01 Alfred Marcel Bruckstein , Martianus Frederic Ezerman , Adamas Aqsa Fahreza , San Ling

Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct with high fidelity,…

Quantum Physics · Physics 2022-12-21 Rishabh Gupta , Manas Sajjan , Raphael D. Levine , Sabre Kais

Continual learning systems are increasingly deployed in environments where retraining or reset is infeasible, yet many approaches emphasize task performance rather than the evolution of internal representations over time. In this work, we…

Machine Learning · Computer Science 2026-02-24 Vishnu Subramanian

This article presents a state feedback control design strategy for the stabilization of a vehicle along a reference collision avoidance maneuver. The stabilization of the vehicle is achieved through a combination of steering, acceleration…

Optimization and Control · Mathematics 2021-02-16 Penco Dario , Davins-Valldaura Joan , Godoy Emmanuel , Kvieska Pedro , Valmorbida Giorgio

Ground robots which are able to navigate a variety of terrains are needed in many domains. One of the key aspects is the capability to adapt to the ground structure, which can be realized through movable body parts coming along with…

Robotics · Computer Science 2019-03-07 Tobias Klamt , Sven Behnke

The representation of numbers by tensor product states of composite quantum systems is examined. Consideration is limited to k-ary representations of length L and arithmetic modulo k^{L}. An abstract representation on an L fold tensor…

Quantum Physics · Physics 2007-05-23 Paul Benioff

A finite-dimensional pseudo-unitary framework is set up for describing the dynamics of free elementary particles in a purely relativistic quantum mechanical way. States of any individual particles or antiparticles are defined as suitably…

Mathematical Physics · Physics 2015-02-03 Jorge G. Cardoso

We propose in this paper an alternative method for the quantisation of systems with first-class constraints. This method is a combination of the coherent-state-path-integral quantisation developed by Klauder, with the ideas of reduced state…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Charis Anastopoulos

The quantum state of a system of qubits can be represented by a Wigner function on a discrete phase space, each axis of the phase space taking values in a finite field. Within this framework, we show that one can make sense of the notion of…

Quantum Physics · Physics 2007-05-23 William K. Wootters , Daniel M. Sussman

Neural network quantum states as ansatz wavefunctions have shown a lot of promise for finding the ground state of spin models. Recently, work has been focused on extending this idea to mixed states for simulating the dynamics of open…

Quantum Physics · Physics 2024-06-21 Simon Kothe , Peter Kirton

In this paper, an automated Linear Parameter-Varying (LPV) model conversion approach is proposed for nonlinear dynamical systems. The proposed method achieves global embedding of the original nonlinear behavior of the system by leveraging…

Systems and Control · Electrical Eng. & Systems 2025-02-19 E. Javier Olucha , Patrick J. W. Koelewijn , Amritam Das , Roland Tóth

This paper describes some new results on recursive l_1-minimizing by Kalman filtering. We consider the l_1-norm as an explicit constraint, formulated as a nonlinear observation of the state to be estimated. Interpretiing a sparse vector to…

Signal Processing · Electrical Eng. & Systems 2018-08-21 Otmar Loffeld , Dunja Alexandra Hage , Miguel Heredia Conde , Ling Wang

We introduce Liouville Fock state lattices (LFSLs) as a framework for visualizing open quantum systems through matrix representations of the Lindblad master equation (LME). By vectorizing the LME, the state evolves in a doubled Hilbert…

Quantum Physics · Physics 2026-04-01 Caio B. Naves , Jonas Larson

In this work a collective of interacting stateless automata in a discrete geometric environment is considered as an integral automata-like computational dynamic object. For such distributed on the environment object different approaches to…

Formal Languages and Automata Theory · Computer Science 2010-07-15 Oleksiy Kurganskyy , Igor Potapov

We introduce new representations to formulate quantum mechanics on noncommutative coordinate space, which explicitly display entanglement properties between degrees of freedom of different coordinate components and hence could be called…

High Energy Physics - Theory · Physics 2007-05-23 S. C. Jing , Q. Y. Liu , H. Y. Fan

This paper has a dual purpose. One aim is to study the evolution of coherent states in ordinary quantum mechanics. This is done by means of a Hamiltonian approach to the evolution of the parameters that define the state. The stability of…

General Relativity and Quantum Cosmology · Physics 2012-08-27 A. A. Minzoni , Marcos Rosenbaum , Michael P. Ryan,

State-space models effectively model multivariate time series by updating over time a representation of the system state from which predictions are made. The state representation is usually a vector without any explicit structure.…

Machine Learning · Computer Science 2026-04-07 Daniele Zambon , Andrea Cini , Cesare Alippi