Modelli Matematici di Storie D'Amore

In questo articolo sono descritti i principali risultati finora ottenuti nel contesto della modellistica delle relazioni d’amore. I modelli sono di tipo descrittivo e stu- diano l’evoluzione dei sentimenti di due individui a partire da uno stato iniziale di indifferenza fino al raggiungimento di un regime sentimentale stazionario, periodi- co, o addirittura aperiodico. I modelli pi`u semplici sono costituiti da due equazioni differenziali (una per lei e una per lui) contenenti le informazioni essenziali sul mo- do con cui ogni individuo reagisce all’amore e al fascino dell’altro. Analizzando i modelli si possono ricavare, senza bisogno di alcun dato, le propriet`a fondamentali delle storie d’amore tra individui di varie categorie: sicuri o insicuri, non polarizzati o polarizzati (tra cui, platonici o sinergici), ... Cos`ı facendo si capisce, ad esempio, perch´e in coppie di individui sicuri ci sia una marcata tendenza ad aumentare il proprio fascino nella fase del corteggiamento, o perch´e piccole scoperte riguardanti il partner possano avere conseguenze (positive o negative) sorprendentemente grandi (catastrofi). Coppie di individui insicuri hanno invece una decisa propensione ad interrompere la relazione dopo un certo tempo. Infine, si scopre che regimi sentimentali altalenanti sono possibili a causa della copresenza di insicurezza e sinergismo e che le crisi ricorrenti possono lentamente sparire o attenuandosi o rarefacendosi nel tempo. In conclusione, per mezzo di questi modelli, propriet`a come quelle appena descritte, note agli psicanalisti che le hanno scoperte esercitando la loro professione, sono finalmente capite e spiegate: un risultato di indubbio valore. Tutti i fenomeni sopra citati riguardano coppie estremamente semplici, in cui l’evoluzione della storia d’amore `e dominata dalle interazioni tra i partner. Ma nella realt`a le relazioni interpersonali sono molto pi`u complesse perch´e risentono anche dell’ambiente sociale in cui la coppia vive. Successi e insuccessi nella pro- fessione, problemi di salute, lunghi e ripetuti periodi di assenza forzata, esistenza di importanti passioni, come quelle tipiche degli artisti, sono tutti fattori che in- terferiscono, anche notevolmente, con l’evoluzione dei sentimenti. Per modellizzare coppie cos`ı complesse, `e necessario far uso di modelli con tre o pi`u equazioni diffe- renziali, che possono essere analizzati solo per via numerica. Tali modelli possono spiegare anche regimi sentimentali caotici e, quindi, imprevedibili. Finora ci`o `e stato fatto solo per un numero limitato di casi, in particolare per relazioni tenden- zialmente instabili come quelle triangolari. Tuttavia, i risultati ottenuti sono cos`ı incoraggianti da far pensare che l’intero settore scientifico debba, in tempi brevi, espandersi significativamente. Il lettore che desideri approfondire quanto esposto in questo articolo potr`a fare riferimento al libro ”Modeling Love Dynamics”, pubblicato nel 2016 daWorld Scien- tific (autori: Sergio Rinaldi, Fabio Della Rossa, Fabio Dercole, Alessandra Gragnani e Pietro Landi). A chi sia invece interessato a una sintesi dell’argomento e a un breve commento sul senso e sul valore di questi studi si consigliano le seguenti rasse- gne critiche: “The equations of love”, di Marten Scheffer (http://blogs.nature. com/aviewfromthebridge/2016/05/20/the-equations-of-love), “A review of the book Modeling Love Dynamics”, di Gustav Feichtinger (http://www.oegor. at/files/news/news24.pdf) e “Perch`e Rossella O’Hara ha fallito? Se l’amore `e matematico”, di Anna Meldolesi (https://goo.gl/OjpKtD)

Conflicts among N armed groups: Scenarios from a new descriptive model

In this paper we propose and analyze a new descriptive model of armed conflicts among N groups. The model is composed of N2 ordinary differential equations, with 3(N2+N) constant parameters that describe military characteristics and recruitment policies, ranging from pure defensivism to pure fanaticism. The results are only preliminary, but point out interesting (though not very surprising) properties: periodic coexistence is possible, and multiple attractors can exist; governmental groups cannot go extinct if they are highly defensivist, and rebels cannot be eradicated if they are highly fanatic. Shocks due to interventions of short duration of an external army can stabilize/destabilize the system and/or eradicate some group, and the same holds true for small structural changes. Other more subtle questions concerning, for example, the existence of chaotic regimes and the systematic evaluation of the role of strategic factors like power, intelligence, and fanaticism, remain open and require further research

Profiling core-periphery network structure by random walkers

Disclosing the main features of the structure of a network is crucial to understand a number of static and dynamic properties, such as robustness to failures, spreading dynamics, or collective behaviours. Among the possible characterizations, the core-periphery paradigm models the network as the union of a dense core with a sparsely connected periphery, highlighting the role of each node on the basis of its topological position. Here we show that the core-periphery structure can effectively be profiled by elaborating the behaviour of a random walker. A curve—the core-periphery profile—and a numerical indicator are derived, providing a global topological portrait. Simultaneously, a coreness value is attributed to each node, qualifying its position and role. The application to social, technological, economical, and biological networks reveals the power of this technique in disclosing the overall network structure and the peculiar role of some specific nodes

The branching bifurcation of Adaptive Dynamics

We unfold the bifurcation involving the loss of evolutionary stability of an equilibrium of the canoncal equation of Adaptive Dynamics (AD). The equation deterministically describes the expected long-term evolution of inheritable traits phenotypes or strategies-of coevolving populations, in the limit of rare and small mutations. In the vicinity of a stable equilibium of the AD canonical equation, a mutant type can invade and coexist with the present-resident-types, whereas the fittest always win far from equilibrium. After coexistence, residents and mutants effectively diversify, according to the enlarged canonical equation, only if natural selection favors outer rather than intermediate traits-the equilibrium being evolutionarily unstable, rather than stable. Though the conditions for evolutionary branching-the joint effect of resident-mutant coexistence and evolutionary instability- have been known for long, the unfolding of the bifurcation has remained a missing tile of AD, the reason being related to the nonsmoothness of the mutant invasion fitness after branching. In this paper, we develop a methodology that allows the approximation of the invasion fitness after branching in terms of the expansion of the (smooth) fitness before branching. We then derive a canonical model or the branching bifurcation and perform its unfolding around the loss of evolutionary stability. We cast our analysis in the simplest (but classical) setting of asexual, unstructured populations living in an isolated, homogeneous, and constant abiotic environment; individual traits are one-dimensional; intra-as well as inter-specific ecological interactions are described in the vicinity of a stationary regime

A conceptual model for the prediction of sexual intercourses in permanent couples

The problem of the frequency of sexual intercourses in permanent couples is investigated for the first time with a purely conceptual model. The model, based on a few axioms involving very simple notions like sexual appetite and erotic potential, is composed of two ordinary differential equations which are exactly the same than those proposed almost one century ago in epidemiology. The model can be used to discuss the possibility of estimating strategic parameters from real data, as well as to criticize the rule of "the beans in the yar" proposed in 1970 by David Martin in The Journal of Sex Research

Small discoveries can have great consequences in love affairs: the case of "Beauty and the Beast"

A mathematical model is proposed for interpreting the love story portrayed by Walt Disney in the film 'Beauty and The Beast'. The analysis shows that the story is characterized by a sudden explosion of sentimental involvements, revealed by the existence of a saddle-node bifurcation in the model. The paper is interesting not only because it deals for the first time with catastrophic bifurcations in specific romantic relationships, but also because it enriches the list of examples in which love stories are satisfactorily described through Ordinary Differential Equations

Temporary bluffing can be rewarding in social systems: the case of romantic relationships

We show in this article that temporary bluffing has the power of promoting the transition from a bad to a good state in social systems. The analysis is carried out with reference to the simplest unit of interest in sociology - the couple - but it can be certainly extended to larger social groups. More precisely, an already available mathematical model shows that couples composed of so-called secure individuals with neither too high nor too low appeals have two alternative romantic regimes - one satisfactory and one not. Thus, if one of these couples is trapped in its unsatisfactory regime the problem is how to escape from that trap and switch to the satisfactory regime. Temporary bluffing, namely, giving to the partner for a sufficiently long time a biased impression of the involvement or of the appeal, is a very effective, though not unique, way for performing the switch. This, in a sense, attenuates the negative moral value usually given to bluffing in social behavior

Analyzing synchronized clusters in neuron networks

The presence of synchronized clusters in neuron networks is a hallmark of information transmission and processing. Common approaches to study cluster synchronization in networks of coupled oscillators ground on simplifying assumptions, which often neglect key biological features of neuron networks. Here we propose a general framework to study presence and stability of synchronous clusters in more realistic models of neuron networks, characterized by the presence of delays, different kinds of neurons and synapses. Application of this framework to two examples with different size and features (the directed network of the macaque cerebral cortex and the swim central pattern generator of a mollusc) provides an interpretation key to explain known functional mechanisms emerging from the combination of anatomy and neuron dynamics. The cluster synchronization analysis is carried out also by changing parameters and studying bifurcations. Despite some modeling simplifications in one of the examples, the obtained results are in good agreement with previously reported biological data

Pinning control of hypergraphs

A standard assumption in control of network dynamical systems is that its nodes interact through pairwise interactions, which can be described by means of a directed graph. However, in several contexts, multibody, directed interactions may occur, thereby requiring the use of directed hypergraphs rather then digraphs. For the first time, we propose a strategy, inspired by the classic pinning control on graphs, that is tailored for controlling network systems coupled through a directed hypergraph. By drawing an analogy with signed graphs, we provide sufficient conditions for controlling the network onto the desired trajectory provided by the pinner, and a dedicated algorithm to design the control hyperedges