Energy-dependent cross ection and mean free path

In summary, the mean free path can be determined by using the scattering cross section and a differential equation for the intensity. This can be generalized to energy-dependent cross sections, but the average energy must also be taken into account. Monte Carlo simulations are often used for these types of problems. There are two basic formulas for calculating the mean free path, one for transmission through media and one for particle interactions, but the latter is dependent on the specific particles and medium being considered.
  • #1
tom.stoer
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The mean free path is usually determined via the scattering cross section σ; one starts with a differential equation for the intensity

[tex]dI(x)= -n\,\sigma\,I(x)\,dx[/tex]

Are there generalizations for this derivation for energy-dependent cross sections σ(E)?
 
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  • #2
You didn't say what particle you are scattering. If it is neutron or photon, then the formula still holds, but only between collisions. This is one area where Monte Carlo method is used.
 
  • #3
mathman said:
You didn't say what particle you are scattering. If it is neutron or photon, then the formula still holds, but only between collisions. This is one area where Monte Carlo method is used.
I am not looking for a specific problem, but for the general ansatz. First one would have to modify it like

[tex]dI(x)= -n\,\sigma(E)\,I(x)\,dx[/tex]

but then one has to take into account that

[tex]\langle E \rangle = f(x)[/tex]

i.e. a typical particle at x has a typical energy E. I don't see how to formulate that problem. It's clear that one can use Monte Carlo Simulation, but there should be a general ansatz
 
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  • #4
Since you need Monte Carlo for the specific problems I cited (happens to be an area where I have worked), I doubt if there is something general as you are looking for.

Using Monte Carlo the average energy isn't used.
 
  • #5
I am only looking for the ansatz, a (small set of) formula(s) I can write down. I don't care about the solution for the moment ;-)

Many problems which you can't solve analytically have a rigorous definition; you can't solve QCD analytically, but you can write down the lattice QCD lagrangian
 
  • #6
There are two basic formulas. The transmission through media, which follows an exponential law, and the interaction when a particle hits something. The latter is dependent on what particles you are considering and the medium.

I don't have any references handy.
 

Related to Energy-dependent cross ection and mean free path

1. What is energy-dependent cross section?

Energy-dependent cross section is a measure of the probability that a particle will interact with another particle when they come in contact. It takes into account the energy of the particles involved and the likelihood of their interaction.

2. How is energy-dependent cross section related to mean free path?

The energy-dependent cross section is directly related to the mean free path, as it determines the probability of interaction between particles. A higher cross section means a shorter mean free path, as there is a higher chance of particles colliding with each other.

3. What factors affect energy-dependent cross section?

The energy of the particles, the type of particles involved, and the type of interaction (such as scattering or absorption) are all factors that can affect the energy-dependent cross section. Additionally, the environment in which the particles are traveling can also impact the cross section.

4. How is energy-dependent cross section measured?

Energy-dependent cross section is typically measured using experiments and simulations that involve colliding particles of known energy and measuring the resulting interactions. These measurements are then used to calculate the cross section for different energies and types of particles.

5. What are the practical applications of understanding energy-dependent cross section and mean free path?

Understanding energy-dependent cross section and mean free path is important in many scientific fields, such as nuclear physics, astrophysics, and materials science. It can help in predicting and understanding the behavior of particles in different environments and can also inform the design of experiments and technologies that involve particle interactions.

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