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When interactions between individual dynamical components are sufficiently strong, coordinated dynamics at the systemic level can emerge. This is called synchronisation.
We present a few paradigmatic modelling strategies selected due to their generality in addressing the emergence of spatio-temporal structure, including criticality, synchronisation, intermittency, adaptation and forecasting.
The chapters of Part I will discuss why complexity science is important, how this science relates to other sciences and also a little bit about its philosophical status. The aim is to make clear what makes complexity science special and in which way it contributes to our understanding of the surrounding world.
Many types of emergence exist. This chapter will discuss some of the most prominent, and broadly occurring, examples of emergent structure in space and time.
The process of entities successively splitting into two or more is of great relevance: biological reproduction, infection spreading, rumour spreading, nuclear reactions and much more.
Emergent phenomena require some interdependence between components. Networks of nodes and connecting links are therefore a very natural and powerful language for the analysis and characterisation of complex systems.
We study approximations for the Lévy area of Brownian motion which are based on the Fourier series expansion and a polynomial expansion of the associated Brownian bridge. Comparing the asymptotic convergence rates of the Lévy area approximations, we see that the approximation resulting from the polynomial expansion of the Brownian bridge is more accurate than the Kloeden–Platen–Wright approximation, whilst still only using independent normal random vectors. We then link the asymptotic convergence rates of these approximations to the limiting fluctuations for the corresponding series expansions of the Brownian bridge. Moreover, and of interest in its own right, the analysis we use to identify the fluctuation processes for the Karhunen–Loève and Fourier series expansions of the Brownian bridge is extended to give a stand-alone derivation of the values of the Riemann zeta function at even positive integers.
Let $V$ be a finite-dimensional vector space over $\mathbb{F}_p$. We say that a multilinear form $\alpha \colon V^k \to \mathbb{F}_p$ in $k$ variables is $d$-approximately symmetric if the partition rank of difference $\alpha (x_1, \ldots, x_k) - \alpha (x_{\pi (1)}, \ldots, x_{\pi (k)})$ is at most $d$ for every permutation $\pi \in \textrm{Sym}_k$. In a work concerning the inverse theorem for the Gowers uniformity $\|\!\cdot\! \|_{\mathsf{U}^4}$ norm in the case of low characteristic, Tidor conjectured that any $d$-approximately symmetric multilinear form $\alpha \colon V^k \to \mathbb{F}_p$ differs from a symmetric multilinear form by a multilinear form of partition rank at most $O_{p,k,d}(1)$ and proved this conjecture in the case of trilinear forms. In this paper, somewhat surprisingly, we show that this conjecture is false. In fact, we show that approximately symmetric forms can be quite far from the symmetric ones, by constructing a multilinear form $\alpha \colon \mathbb{F}_2^n \times \mathbb{F}_2^n \times \mathbb{F}_2^n \times \mathbb{F}_2^n \to \mathbb{F}_2$ which is 3-approximately symmetric, while the difference between $\alpha$ and any symmetric multilinear form is of partition rank at least $\Omega (\sqrt [3]{n})$.
Let $A \subseteq \{0,1\}^n$ be a set of size $2^{n-1}$, and let $\phi \,:\, \{0,1\}^{n-1} \to A$ be a bijection. We define the average stretch of $\phi$ as
where the expectation is taken over uniformly random $x,x' \in \{0,1\}^{n-1}$ that differ in exactly one coordinate.
In this paper, we continue the line of research studying mappings on the discrete hypercube with small average stretch. We prove the following results.
For any set $A \subseteq \{0,1\}^n$ of density $1/2$ there exists a bijection $\phi _A \,:\, \{0,1\}^{n-1} \to A$ such that ${\sf avgStretch}(\phi _A) = O\left(\sqrt{n}\right)$.
For $n = 3^k$ let ${A_{\textsf{rec-maj}}} = \{x \in \{0,1\}^n \,:\,{\textsf{rec-maj}}(x) = 1\}$, where ${\textsf{rec-maj}} \,:\, \{0,1\}^n \to \{0,1\}$ is the function recursive majority of 3’s. There exists a bijection $\phi _{{\textsf{rec-maj}}} \,:\, \{0,1\}^{n-1} \to{A_{\textsf{rec-maj}}}$ such that ${\sf avgStretch}(\phi _{{\textsf{rec-maj}}}) = O(1)$.
Let ${A_{{\sf tribes}}} = \{x \in \{0,1\}^n \,:\,{\sf tribes}(x) = 1\}$. There exists a bijection $\phi _{{\sf tribes}} \,:\, \{0,1\}^{n-1} \to{A_{{\sf tribes}}}$ such that ${\sf avgStretch}(\phi _{{\sf tribes}}) = O(\!\log (n))$.
These results answer the questions raised by Benjamini, Cohen, and Shinkar (Isr. J. Math 2016).