Interpreting Path Ordered Exponentials with Non-Sensical Integration Variables

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In summary, the conversation discusses an integral in which the integration variables are in the limits, resulting in a triangular region in the t'-t'' plane. The reference provided explains that the term in the integral is a path on the manifold, and the formula given is a result of the contraction mapping principle. The conversation also clarifies the usage of the variable R_1(xi) in the successive approximation process.
  • #1
etotheipi
I see a term like$$\int_0^{t''} \left[ \int_{t'}^t \omega(t'') \omega(t') dt' \right] dt''$$here ##\omega## is a matrix. How to interpret this integral - the integration variables are in the limits, in places where they don't make sense. Is that a mistake? It's given that the range of integration is ##0 < t' < t'' < t##, i.e. a triangle in the ##t'##-##t''## plane. Reference is top of page 50 here. Thanks!
 
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  • #2
I think ##\omega\, : \,[0,1] \longrightarrow \operatorname{SO}(3)## is simply a path on the manifold. The point is to demonstrate why general, i.e. non-commuting matrices cannot be handled the same way as (commuting) scalars. The "let's pretend as if" part is a bit confusing, since he uses the same variables.
 
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  • #3
Hope it will be of some use

formula (3.11) at page 49 means that ##\omega(t)\in T_e(SO(3))##

formula (3.16) follows from the standard successive procedure of the contraction mapping principle for the equation ##R=E+\int_0^t\omega Rd\xi##.
 
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  • #4
That's interesting! Maybe a bit above my level of maths. Let me see what I understand; by the contraction mapping principle, the successive approximations to ##R(t)## are $$R_n(t) = 1 + \int_0^t \omega(\xi) R_{n-1}(\xi) d\xi$$So for instance$$R_1(t) = 1 + \int_0^t \omega(\xi) d\xi$$and the next approximation is$$\begin{align*}

R_2(t) = 1 + \int_0^t \omega(\xi) R_1(\xi) d\xi &= 1+ \int_0^t \omega(\xi) \left[ 1 + \int_0^t \omega(\eta) d\eta \right] d\xi \\

&= 1 + \int_0^t \omega(\xi) d\xi + \int_0^t \int_0^t \omega(\xi) \omega(\eta) d\eta d\xi

\end{align*}$$and then continue on and take ##R(t) = \lim_{n \rightarrow \infty}R_n(t)##. Except, I have some different limits in the second integral here to Tong... 🤭
 
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  • #5
You write ##R_1(\xi)## it is correct ; but then you must substitute ##R_1(\xi)=1+\int_0^\xi\omega(s)ds##
 
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  • #6
wrobel said:
You write ##R_1(\xi)## it is correct ; but then you must substitute ##R_1(\xi)=1+\int_0^\xi\omega(s)ds##

Ah, yes that's it, thanks ☺
 

1. What are path ordered exponentials?

Path ordered exponentials are mathematical operators used in quantum field theory to describe the evolution of a system over a path. They are used to calculate the probability amplitude of an event occurring at a specific time and location.

2. How are path ordered exponentials different from regular exponentials?

Regular exponentials are used to describe the time evolution of a system in a fixed reference frame, while path ordered exponentials take into account the path of the system in spacetime. This makes path ordered exponentials more suitable for describing systems in quantum field theory.

3. What is the significance of path ordered exponentials in quantum field theory?

Path ordered exponentials are essential in quantum field theory as they allow for the calculation of transition amplitudes between different states of a quantum system. They also play a crucial role in the renormalization process, which is necessary for making predictions in quantum field theory.

4. How are path ordered exponentials calculated?

Path ordered exponentials are calculated using the Dyson series, which is an infinite sum of terms involving the path ordered exponentials. This series can be approximated to any desired accuracy by summing a finite number of terms.

5. Are there any real-world applications of path ordered exponentials?

Path ordered exponentials are primarily used in theoretical physics, particularly in quantum field theory. However, they have also found applications in other fields such as condensed matter physics, where they are used to study the behavior of systems with many interacting particles.

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