And when not asympotic states?

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In summary, Feynman diagrams are used to calculate the probability of nuclear reactions for particles, but they are not powerful enough to consider arbitrary states. For this, Lattice gauge theory is sometimes used to make approximate calculations, which requires a lot of computational power but is well understood in principle. There are also other computer approximations, such as Monte Carlo simulations, which can be used to model physics in situations where Feynman diagrams fail. One example is lattice QCD, which can supposedly be run on a personal computer.
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StarsRuler
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Feynman diagrams is the standard for calculate the probability of nuclear reactions fo particles, but, when we want calculate the probability of evolution of an arbitratry field to another field a fixed time after, what is the mechanism??
 
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Thanx
 
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Thanx for the answers
 
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It's hard to get these things over the internet, but it looks like you are angry that no one answered your question. The truth is, it's not very clearly worded and we have to guess what you want. So here is my guess:

The rules for feynman diagrams are derived by considering asymptotic states, because asymptotic states approach free particle states. Free particle states are well understood, whereas interacting states are very poorly understood. We use feynman diagrams, based off of free particles, to try to approximate interacting states. This makes sense for scattering and decays, but for bound states it doesn't work very well. So in feynman diagrams are not powerful enough to consider arbitrary states.

For more arbitrary fields, Lattice gauge theory is used sometimes to make approximate calculations. Essentially, if you approximate space as a lattice rather than a continuum, then calculations require a lot of computational power, but are in principle well understood. Usually there is an error term proportional to the lattice spacing, so these approximations are improved by making the lattice spacing smaller, but at the cost of requiring more computational power. Using this, bound states can be considered.
 
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And there is any program for calculate this in a PC?

Thanx
 
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StarsRuler said:
And there is any program for calculate this in a PC?

Thanx

I don't know if any personal computers are powerful enough to do reasonable lattice calculations, but computing clusters these days can perform good calculations of this kind. One goal of such calculations is to compute the mass of the proton, which has been done to relatively high precision.

For more information, I would search for "lattice QCD". Other computer approximations are generally called "Monte Carlo simulations", which use all kinds of techniques to try to model physics in situations where feynman diagrams fail. The only technique I have any knowledge of is lattice gauge theory, so if you want to know more, you'll have to ask someone else.

Here is an introduction to lattice QCD techniques, which supposedly can be run on a personal computer. http://arxiv.org/abs/hep-lat/0506036
 

FAQ: And when not asympotic states?

1. What are asympotic states?

Asymptotic states refer to the states of a system at very large distances or times. In physics, these states are often used to describe the behavior of a system at the beginning or end of a process, when the system is far from equilibrium.

2. How are asympotic states different from equilibrium states?

Equilibrium states refer to the states of a system at rest, with no net energy flow. Asympotic states, on the other hand, refer to the states of a system that are far from equilibrium and experiencing a net energy flow.

3. What is the significance of studying asympotic states?

Studying asympotic states can provide insights into the dynamics and behavior of a system, especially in situations where equilibrium states are difficult to achieve or maintain. It can also help in understanding the stability and long-term evolution of a system.

4. Can asympotic states be predicted or controlled?

In some cases, yes. For simple systems with well-defined equations, asympotic states can be predicted and controlled using mathematical models and simulations. However, for complex systems such as biological or ecological systems, predicting and controlling asympotic states can be challenging.

5. How do asympotic states relate to chaos and complexity?

Asympotic states are often observed in chaotic or complex systems. The behavior of these systems can be characterized by the emergence of asympotic states, where small changes in initial conditions can lead to vastly different long-term outcomes.

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