Why we call ''nonlinear'' sigma model?

In summary, the conversation discusses the difference between the linear sigma model and the nonlinear sigma model. The linear sigma model is described by a Lagrangian equation and includes terms for the fluctuation of the field and the expectation at ground state. The nonlinear sigma model, on the other hand, is a special case of the linear model when the condition of O(N) symmetry is applied, resulting in a simplified Lagrangian equation. The term "nonlinear" may have originated from the fact that the sigma field in this model is constant, while in the linear model it has non-zero fluctuations.
  • #1
ndung200790
519
0
Please teach me this:
The linear sigma model L(Lagrangian)=[itex]\frac{1}{2}[/itex]([itex]\delta[/itex][itex]_{\mu}[/itex][itex]\Phi[/itex][itex]^{i}[/itex])[itex]^{2}[/itex] + [itex]\frac{1}{2}[/itex][itex]\mu[/itex][itex]^{2}[/itex]([itex]\Phi[/itex][itex]^{i}[/itex])[itex]^{2}[/itex] -
[itex]\frac{\lambda}{4}[/itex](([itex]\Phi[/itex][itex]^{i}[/itex])[itex]^{2}[/itex])[itex]^{2}[/itex].
The nonlinear sigma model:
L=f[itex]_{ij}[/itex]({[itex]\Phi[/itex][itex]^{i}[/itex]})[itex]\delta[/itex][itex]_{\mu}[/itex]
[itex]\Phi[/itex][itex]^{i}[/itex][itex]\delta[/itex][itex]^{\mu}[/itex][itex]\Phi[/itex][itex]{j}[/itex].
After put condition O(N) symmetry,we have Lagrangian(because after the putting f=constant):L=[itex]\frac{1}{2g^{2}}[/itex]/[itex]\delta[/itex][itex]_{\mu}[/itex]n/[itex]^{2}[/itex].
.Then the nonlinear model is a special case of the linear sigma model.So I do not understand why we call it the ''nonlinear'' model?
 
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  • #2
At the moment I think that the term nonlinear sigma model has origination from history.It was first considered as an alternative description of spontaneous symmetry breaking.In the nonlinear model the sigma field is constant(the fluctuation of the field is zero,then they call ''nonlinear'').But in the linear sigma model, the fluctuation sigma field is nonzero(then they call ''linear'') plus the expectation at ground state of field(constant).Is that correct?
 

1. Why is the sigma model called "nonlinear"?

The sigma model is called "nonlinear" because it describes a system where the output is not directly proportional to the input. In other words, the relationship between the input and output is not a straight line, but rather a curved or nonlinear function.

2. What is the significance of the term "sigma" in the sigma model?

The term "sigma" refers to the Greek letter σ, which is commonly used in mathematics to represent a sum or series. In the context of the sigma model, it represents the sum of all the possible paths or configurations that a system can take.

3. How is the sigma model used in physics?

The sigma model is used in physics to describe complex systems, such as the behavior of particles in quantum field theory or the dynamics of magnetic materials. It is also used to study phase transitions, where a system undergoes a sudden change in its properties at a critical point.

4. What is the difference between a linear and nonlinear sigma model?

In a linear sigma model, the output is directly proportional to the input, meaning that a small change in the input will result in a proportional change in the output. In a nonlinear sigma model, this relationship is not true, and the output may change in a non-proportional or unpredictable manner.

5. What are some real-world applications of the sigma model?

The sigma model has many practical applications in fields such as physics, engineering, and economics. For example, it is used to study the behavior of complex materials, predict the movements of financial markets, and model the spread of infectious diseases.

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