## Introduction to dynamical systems (lecture – 01) by soumitro

Phase room, bifurcations, chaos, the butterfly effect, strange attractors, and pattern forming are among the topics to be discussed. The course will concentrate on a few key findings from the analysis of dynamical systems that are particularly relevant to complex systems:
1. Bifurcations occur in dynamical systems when a small change in a system parameter, such as temperature or fishery harvest rate, results in a large and qualitative change in the system’s behavior.
3. It is possible for disordered behaviour to be stable. The butterfly effect causes non-periodic processes to have stable average properties. As a result, even if a system’s specifics are unpredictable, its average or statistical properties can be predicted.
4. Simple rules can lead to complex actions. Simple dynamical processes do not always produce simple outcomes. We’ll see, in particular, how simple rules can result in patterns and structures of surprising complexity.
Patricia Mellodge, the course teacher, is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Hartford in Connecticut, where she specializes in robotic device modeling and control. She attended the Complex Systems Summer School at the Santa Fe Institute in 2018. She brings her enthusiasm for sharing information as a course teacher, and she enjoys assisting students in understanding and appreciating the wonders of dynamical systems!

## Dynamical systems – stefano luzzatto – lecture 01

A dynamical system is a mathematical system in which a function defines the time dependence of a geometrical point. Mathematical models that illustrate the swinging of a clock pendulum, the movement of water in a pipe, and the number of fish in a lake in the springtime are just a few examples.
A dynamical system’s state is described by a tuple of real numbers (a vector) that can be represented by a point in an appropriate state space at any given time (a geometrical manifold). The dynamical system’s evolution rule is a feature that explains what future states result from the current state. Sometimes, the function is deterministic, meaning that only one future state follows from the current state for a given time period. 1st [two] Some processes, on the other hand, are stochastic, in the sense that random events have an effect on the evolution of the state variables.
A dynamical system is a “particle or ensemble of particles whose state changes over time and thus obeys differential equations involving time derivatives,” according to physics.
[3] An empirical solution of such equations or their integration over time by computer simulation is realized in order to make a prediction about the system’s future behavior.

### Dynamical systems and chaos: introduction to functions part

For all aspects of nonlinear dynamics, the book addresses continuous and discrete processes in systematic and sequential approaches. The mathematical theories on flow bifurcations, oscillatory solutions, symmetry analysis of nonlinear systems, and chaos theory are the book’s distinguishing features. Readers get a global summary of the subject thanks to the logically organized content and sequential orientation. A systematic mathematical approach has been taken, and a variety of detailed examples and exercises have been included. Continuous processes are covered in chapters 1–8, starting with one-dimensional flows. The Lie invariance principle and its algorithm for finding symmetries of a system are discussed in Chap. 8, and the Lie invariance principle and its algorithm for finding symmetries of a system are discussed in Chap. 8. Discrete processes, chaos, and fractals are discussed in Chapters 9–13. Proofs are used to explain the conjugacy relationship between maps and their properties. The book’s key topics include chaos theory and its relation to fractals, Hamiltonian flows, and nonlinear structure symmetries. Nonlinear structures, chaos theory, and fractals have seen exponential interest and progress in recent decades, as shown by undergraduate and postgraduate curricula around the world. The book is appropriate for advanced undergraduate and postgraduate students in mathematics, physics, and engineering who are taking courses in dynamical systems and chaos, nonlinear dynamics, and other related topics.

### Dynamical systems and chaos: introduction to functions part

Dynamical systems theory is a unifying paradigm for understanding how systems as complex as the environment and human actions change over time. I’ll give you an overview of some of the main concepts in this blog post. Since the field of dynamical systems is so huge, I’ll just scratch the surface, concentrating on low-dimensional systems with interesting properties like multiple stable states, critical transitions, hysteresis, and critical slowing down, despite their simplicity.
Though I’ve written about linear differential equations before (in the context of love affairs) and nonlinear differential equations before (in the context of infectious diseases), this post is a more gentle introduction. If you’ve never heard of dynamical systems theory before, this blog post will be easier to understand than the other two.
The majority of this blog post can be read as a preamble to Dablander, Pichler, Cika, and Bacilieri (2020), who address early warning signs and crucial changes in greater detail. I recently gave a talk about this project and had the audacity to record it (with slides available from here). If you prefer frantic hand gestures to the soothing written word, the first thirty minutes or so cover a portion of what is explained here. But, without further ado, let’s get started!