By Eric Bertin

ISBN-10: 3642239226

ISBN-13: 9783642239229

This concise primer (based on lectures given at summer season colleges on advanced platforms and on a masters measure path in complicated platforms modeling) will supply graduate scholars and beginners to the sphere with the fundamental wisdom of the ideas and strategies of statistical physics and its power for program to interdisciplinary topics.

Indeed, lately, statistical physics has started to draw the curiosity of a vast neighborhood of researchers within the box of complicated method sciences, starting from biology to the social sciences, economics and machine technological know-how. extra typically, increasingly more graduate scholars and researchers believe the necessity to study a few easy options and questions originating in different disciplines with out unavoidably having to grasp the entire corresponding technicalities and jargon. mostly talking, the pursuits of statistical physics should be summarized as follows: at the one hand to review platforms composed of a giant variety of interacting ‘entities’, and at the different to foretell the macroscopic (or collective) habit of the process thought of from the microscopic legislation ruling the dynamics of the person ‘entities’. those pursuits are, to some degree, additionally shared by means of what's these days referred to as ‘complex structures technology’ and for those purposes, structures studied within the framework of statistical physics could be regarded as one of the easiest examples of complicated systems—allowing moreover a slightly good built mathematical remedy.

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**Additional info for A Concise Introduction to the Statistical Physics of Complex Systems**

**Example text**

In addition, the order parameter varies as m 0 ∼ (Tc − T )β for T close to Tc , with β = 1/2 here. The exponent β is an example of critical exponent, and the value β = 1/2 is called the “mean-field value” of β, for reasons that will become clear in the next section. The notation β is standard for the critical exponent associated to the order parameter, and should not be confused with the inverse temperature β = 1/T. An important remark is that the average value m of the magnetization is still zero for T < Tc , since the two values ±m 0 of the magnetization have the same probability.

Logarithmic corrections may be needed for α = 1. • For general values of α and β, the Lévy distribution is known only through its Fourier transform. However, for a few specific values of the parameters, explicit expressions of L(z; α, β) are available. For instance, the Gaussian distribution is recovered for α = 2, whatever the value of β: 1 2 L(z; 2, β) = √ e−z /4 . 236) Note that due to the parameterization used in Eq. 236) is not equal to one. For α = 1 and β = 0, one gets the Cauchy distribution: L(z; 1, 0) = 1 .

In a physical context, the concept of disordered system could seem less natural, since all particles within a given class are identical. In this case, disorder rather comes from the possibly random position of the particles. A standard example is that of magnetic impurities (that carry a magnetic moment, or spin) diluted in a non-magnetic material. The interaction between magnetic atoms (which have to be described in the framework of quantum mechanics) is mediated by the non-magnetic atoms, and acquires an oscillatory behavior, depending on the distance ri j between the two spins: H =− J (ri j )si s j .

### A Concise Introduction to the Statistical Physics of Complex Systems by Eric Bertin

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