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Related papers: Kinetically constrained models

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This is intended to appear as the introduction to "The CBM Physics Book: compressed baryonic matter in laboratory experiments" (ed. B. Friman, C. H\"ohne, S. Leupold, J. Knoll, J. Randrup, R. Rapp, P. Senger), to be published by Springer.…

High Energy Physics - Phenomenology · Physics 2015-05-18 Frank Wilczek

Parallel kinematic manipulators (PKM) are characterized by closed kinematic loops, due to the parallel arrangement of limbs but also due to the existence of kinematic loops within the limbs. Moreover, many PKM are built with limbs…

Robotics · Computer Science 2024-12-19 Andreas Mueller

We give an overview of the two different methods that have been introduced in order to describe the dynamics of constrained quantum systems; the symplectic formulation and the metric formulation. The symplectic method extends the work of…

Quantum Physics · Physics 2015-05-13 Anna C. T. Gustavsson

In recent years, promising mathematical models have been suggested which aim to describe conscious experience and its relation to the physical domain. Whereas the axioms and metaphysical ideas of these theories have been carefully…

Neurons and Cognition · Quantitative Biology 2020-07-15 Johannes Kleiner

The aim of this chapter is to convey the importance and usefulness of mathematical modelling as a tool to achieve a deeper understanding of stem cell biology. We introduce key mathematical concepts (random walk theory, differential…

Cell Behavior · Quantitative Biology 2020-10-30 Laura E Wadkin , Sirio Orozco-Fuentes , Irina Neganova , Majlinda Lako , Nicholas G Parker , Anvar Shukurov

Despite the growing interest in diffusion models, gaining a deep understanding of the model class remains an elusive endeavour, particularly for the uninitiated in non-equilibrium statistical physics. Thanks to the rapid rate of progress in…

Machine Learning · Computer Science 2025-05-23 Fabio De Sousa Ribeiro , Ben Glocker

Dynamic factor models have been developed out of the need of analyzing and forecasting time series in increasingly high dimensions. While mathematical statisticians faced with inference problems in high-dimensional observation spaces were…

Econometrics · Economics 2024-01-03 Matteo Barigozzi , Marc Hallin

Fundamental aspects of inverse kinetic theories for the incompressible Navier-Stokes equations [Ellero and Tessarotto, 2004, 2005] include the possibility of defining uniquely the kinetic equation underlying such models and furthermore, the…

Fluid Dynamics · Physics 2009-11-11 M. Tessarotto , M. Ellero

This lecture note covers Relativistic Kinematics, which is very useful for the beginners in the field of high-energy physics. A very practical approach has been taken, which answers "why and how" of the kinematics useful for students…

Nuclear Experiment · Physics 2016-04-12 Raghunath Sahoo

We consider a new approach to the description of the collective behavior of complex systems of mathematical biology based on the evolution equations for observables of such systems. This representation of the kinetic evolution seems, in…

Soft Condensed Matter · Physics 2020-07-07 V. I. Gerasimenko

This tutorial survey provides an overview of recent non-asymptotic advances in statistical learning theory as relevant to control and system identification. While there has been substantial progress across all areas of control, the theory…

Systems and Control · Electrical Eng. & Systems 2023-04-28 Anastasios Tsiamis , Ingvar Ziemann , Nikolai Matni , George J. Pappas

In this paper we describe a novel framework for diffusion-based generative modeling on constrained spaces. In particular, we introduce manual bridges, a framework that expands the kinds of constraints that can be practically used to form…

Machine Learning · Computer Science 2025-02-28 Saeid Naderiparizi , Xiaoxuan Liang , Berend Zwartsenberg , Frank Wood

These notes derive a number of technical results on nonlinear contraction theory, a comparatively recent tool for system stability analysis. In particular, they provide new results on the preservation of contraction through system…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Nicolas Tabareau , Jean-Jacques Slotine

Diffusion models have attained prominence for their ability to synthesize a probability distribution for a given dataset via a diffusion process, enabling the generation of new data points with high fidelity. However, diffusion processes…

Machine Learning · Computer Science 2024-11-25 Shervin Khalafi , Dongsheng Ding , Alejandro Ribeiro

This paper summarizes some challenges encountered and best practices established in several years of teaching Machine Learning for the Physical Sciences at the undergraduate and graduate level. I discuss motivations for teaching ML to…

Physics Education · Physics 2021-08-20 Viviana Acquaviva

We introduce a quantum generalization of classical kinetic Ising models, described by a certain class of quantum many body master equations. Similarly to kinetic Ising models with detailed balance that are equivalent to certain Hamiltonian…

Quantum Physics · Physics 2015-05-14 R. Augusiak , F. M. Cucchietti , F. Haake , M. Lewenstein

Group Theory has become an invaluable tool in the physics community. Despite numerous introductory books, the subject remains challenging for beginners. Mathematica has emerged as a popular tool for research and education, offering various…

This article summarises a Web-book on "Complexity" that was developed to introduce undergraduate students to interesting complex systems in the biological, physical and social sciences, and the common tools, principles and concepts used for…

Physics Education · Physics 2007-05-23 Rajesh R. Parwani

A novel formulation of fluid dynamics as a kinetic theory with tailored, on-demand constructed particles removes any restrictions on Mach number and temperature as compared to its predecessors, the lattice Boltzmann methods and their…

Computational Physics · Physics 2018-10-03 B. Dorschner , F. Bösch , I. V. Karlin

We report on recent study [1] of the role of the kinematical constraint in the CCFM equation and its non-linear extension. We compare numerical results obtained by solving the CCFM equation and argue that kinematical constraint represents…

High Energy Physics - Phenomenology · Physics 2015-05-20 Michal Deak