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Carmen Pellicer-Lostao

Publications and source records attributed to Carmen Pellicer-Lostao.

9 recordsLinked to original sources

The Importance of the Strategy in Backward Orbits

This work considers reversed evolution in dynamical systems. In particular, asymptotic behavior of chaotic systems, when their orbits evolve backwards in time. Reversed dynamics reveals important aspects of the trajectories, such as a new necessary parameter. This is the strategy through which one orbit reaches an original state in the past. As a result, it is found that backward orbits exhibit sensitivity to the strategy. This gives additional evidence about the unpredictability of the past

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Notions of Chaotic Cryptography: Sketch of a Chaos based Cryptosystem

Chaotic cryptography describes the use of chaos theory (in particular physical dynamical systems working in chaotic regime as part of communication techniques and computation algorithms) to perform different cryptographic tasks in a cryptographic system. In the end, the question is, can chaotic systems provide alternative techniques able to enhance cryptographic algorithms?. This chapter can be a worthy material to guide the reader in order to answer himself this question. Thus, the objective of this chapter is to give a general vision of what chaotic cryptography is and a comprehensive example that illustrates the main techniques used in this field.

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Application of Chaotic Number Generators in Econophysics

Agent-based models have demonstrated their power and flexibility in Econophysics. However their major challenge is still to devise more realistic simulation scenarios. The complexity of Economy makes appealing the idea of introducing chaotic number generators as simulation engines in these models. Chaos based number generators are easy to use and highly configurable. This makes them just perfect for this application.

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Transition from Exponential to Power Law Distributions in a Chaotic Market

Economy is demanding new models, able to understand and predict the evolution of markets. To this respect, Econophysics offers models of markets as complex systems, that try to comprehend macro-, system-wide states of the economy from the interaction of many agents at micro-level. One of these models is the gas-like model for trading markets. This tries to predict money distributions in closed economies and quite simply, obtains the ones observed in real economies. However, it reveals technical hitches to explain the power law distribution, observed in individuals with high incomes. In this work, non linear dynamics is introduced in the gas-like model in way that an effort to overcome these flaws. A particular chaotic dynamics is used to break the pairing symmetry of agents $(i,j)\Leftrightarrow(j,i)$. The results demonstrate that a "chaotic gas-like model" can reproduce the Exponential and Power law distributions observed in real economies. Moreover, it controls the transition between them. This may give some insight of the micro-level causes that originate unfair distributions of money in a global society. Ultimately, the chaotic model makes obvious the inherent instability of asymmetric scenarios, where sinks of wealth appear and doom the market to extreme inequality.

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A Chaotic Approach to Market Dynamics

Economy is demanding new models, able to understand and predict the evolution of markets. To this respect, Econophysics is offering models of markets as complex systems, such as the gas-like model, able to predict money distributions observed in real economies. However, this model reveals some technical hitches to explain the power law (Pareto) distribution, observed in individuals with high incomes. Here, non linear dynamics is introduced in the gas-like model. The results obtained demonstrate that a chaotic gas-like model can reproduce the two money distributions observed in real economies (Exponential and Pareto). Moreover, it is able to control the transition between them. This may give some insight of the micro-level causes that originate unfair distributions of money in a global society. Ultimately, the chaotic model makes obvious the inherent instability of asymmetric scenarios, where sinks of wealth appear in the market and doom it to complete inequality.

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Money Distributions in Chaotic Economies

This paper considers the ideal gas-like model of trading markets, where each individual is identified as a gas molecule that interacts with others trading in elastic or money-conservative collisions. Traditionally this model introduces different rules of random selection and exchange between pair agents. Real economic transactions are complex but obviously non-random. Consequently, unlike this traditional model, this work implements chaotic elements in the evolution of an economic system. In particular, we use a chaotic signal that breaks the natural pairing symmetry $(i,j)\Leftrightarrow(j,i)$ of a random gas-like model. As a result of that, it is found that a chaotic market like this can reproduce the referenced wealth distributions observed in real economies (the Gamma, Exponential and Pareto distributions).

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Economic Models with Chaotic Money Exchange

This paper presents a novel study on gas-like models for economic systems. The interacting agents and the amount of exchanged money at each trade are selected with different levels of randomness, from a purely random way to a more chaotic one. Depending on the interaction rules, these statistical models can present different asymptotic distributions of money in a community of individuals with a closed economy.

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Role of Symmetry and Geometry in a chaotic Pseudo-Random Bit Generator

In this work, Pseudo-Random Bit Generation (PRBG) based on 2D chaotic mappings of logistic type is considered. The sequences generated with two Pseudorandom Bit Generators (PRBGs) of this type are statistically tested and the computational effectiveness of the generators is estimated. The role played by the symmetry and the geometrical properties of the underlying chaotic attractors is also explored. Considering these PRBGs valid for cryptography, the size of the available key spaces are calculated. Additionally, a novel mechanism called 'symmetry-swap' is introduced in order to enhance the PRBG algorithm. It is shown that it can increase the degrees of freedom of the key space, while maintaining the speed and performance in the PRBG.

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Statistical User Model for the Internet Access

A new statistical based model approach to characterize a user's behavior in an Internet access link is presented. The real patterns of Internet traffic in a heterogeneous Campus Network are studied. We find three clearly different patterns of individual user's behavior, study their common features and group particular users behaving alike in three clusters. This allows us to build a probabilistic mixture model, that can explain the expected global behavior for the three different types of users. We discuss the implications of this emergent phenomenology in the field of multi-agent complex systems.

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