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A crucial question is whether the physical properties measured on a given sample are themselves random or not. Our everyday experience suggests that they are not: materials like glass, ceramics, or bronze have well-defined, reproducible physical properties that can be reliably controlled for industrial applications. | A crucial question is whether the physical properties measured on a given sample are themselves random or not. Our everyday experience suggests that they are not: materials like glass, ceramics, or bronze have well-defined, reproducible physical properties that can be reliably controlled for industrial applications. | ||
From a more mathematical point of view, it means tha physical observables — such as the free energy <math> F_N(\beta)=N f_N(\beta)</math> and its derivatives (magnetization, specific heat, susceptibility, etc.) — are self-averaging. This means that, in the limit <math> N \to \infty </math>, the distribution of the observable concentrates around | From a more mathematical point of view, it means tha physical observables — such as the free energy <math> F_N(\beta)=N f_N(\beta)</math> and its derivatives (magnetization, specific heat, susceptibility, etc.) — are self-averaging. This means that, in the limit <math> N \to \infty </math>, the distribution of the observable concentrates around its average: | ||
<center> | <center> | ||
<math> | <math> | ||
\lim_{N \to \infty} f_N =\lim_{N \to \infty} \overline{f_N}, \quad \quad \overline{f_N}=\int \, | \lim_{N \to \infty} f_N =\lim_{N \to \infty} \overline{f_N}, \quad \quad \overline{f_N}=\int \, df\, P_{f_N}(f)\, f | ||
</math> | </math> | ||
</center> | </center> |
Revision as of 15:35, 2 August 2025
Disordered systems and random energy landascape
In a system with degrees of freedom, the number of configurations grows exponentially with . For simplicity, consider Ising spins that take two values, , located on a lattice of size in dimensions. In this case, and the number of configurations is .
In the presence of disorder, the energy associated with a given configuration becomes a random quantity. For instance, in the Edwards-Anderson model:
where the sum runs over nearest neighbors , and the couplings are independent and identically distributed (i.i.d.) Gaussian random variables with zero mean and unit variance.
The energy of a given configuration is a random quantity because each system corresponds to a different realization of the disorder. In an experiment, this means that each of us has a different physical sample; in a numerical simulation, it means that each of us has generated a different set of couplings .
To illustrate this, consider a single configuration, for example the one where all spins are up. The energy of this configuration is given by the sum of all the couplings between neighboring spins:
Since the the couplings are random, the energy associated with this particular configuration is itself a Gaussian random variable, with zero mean and a variance proportional to the number of terms in the sum — that is, of order . The same reasoning applies to each of the configurations. So, in a disordered system, the entire energy landscape is random and sample-dependent.
Self-averaging observables and partition function
A crucial question is whether the physical properties measured on a given sample are themselves random or not. Our everyday experience suggests that they are not: materials like glass, ceramics, or bronze have well-defined, reproducible physical properties that can be reliably controlled for industrial applications.
From a more mathematical point of view, it means tha physical observables — such as the free energy and its derivatives (magnetization, specific heat, susceptibility, etc.) — are self-averaging. This means that, in the limit , the distribution of the observable concentrates around its average:
Hence macroscopic observables become effectively deterministic and their fluctuations from sample to sample vanish in relative terms: