Understanding the "branch cut argument"

In summary, the conversation discusses the Trapper Method and how it is used to compute contour integrals. It mentions the use of Type 5 integrals and the reason for the multiplication by a factor of ##2\pi i## in the formula. It also explains the role of the log expansion in the computation and how the ln(x) parts of the contour cancel out.
  • #1
TMO
45
1
http://web.williams.edu/Mathematics/sjmiller/public_html/302/coursenotes/Trapper_MethodsContourIntegrals.pdf

See Type 5 Integrals. I don't understand why J is equal to the original real integral multiplied by a factor of ##2\pi i##. I think the ##2\pi i## comes from the fact that as you go around ##C_2## you end up ##2\pi i## greater than when you started. But why does the difference between ##C_1, C_3## correspond to the real integral? Is it because these two segments touch the real line? I don't quite get it.
 
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  • #2
Did you read the part where the log is expanded according to ##\log z = \log r + i\theta + i 2\pi n##? Along both curves ##r \to x##. What does this mean for the integrals? What does it mean for the difference between the integrals?
 
  • #3
I think I'm missing something simple. It seems to me that the contour described amounts to computing the integral:

##\int_0^\infty \frac{ln(x)}{1+x^3}##

instead of

##\int_0^\infty \frac{1}{1+x^3}##
 
  • #4
stevendaryl said:
I think I'm missing something simple. It seems to me that the contour described amounts to computing the integral:

##\int_0^\infty \frac{ln(x)}{1+x^3}##

instead of

##\int_0^\infty \frac{1}{1+x^3}##
Not so, the ln(x) part of C1 will cancel that of C3.
 
  • #5
Orodruin said:
Not so, the ln(x) part of C1 will cancel that of C3.

Oh! Right above the real axis, you have ##ln(|x|)## and right below the real axis, you have ##ln(|x|) + 2\pi i##. So when you subtract them, all that's left is ##\pm 2\pi i##.
 
  • #6
stevendaryl said:
Oh! Right above the real axis, you have ##ln(|x|)## and right below the real axis, you have ##ln(|x|) + 2\pi i##. So when you subtract them, all that's left is ##\pm 2\pi i##.
Indeed.
 

FAQ: Understanding the "branch cut argument"

1. What is the "branch cut argument" in science?

The "branch cut argument" is a concept used in mathematics and physics to explain how certain mathematical functions can have multiple values at a single point. It is used to understand the behavior of complex functions and to determine the appropriate domain for which the function is defined.

2. How does the branch cut argument work?

The branch cut argument works by identifying points in the complex plane where a function is not well-defined or has multiple values. These points are known as branch points and the lines connecting them are called branch cuts. By carefully choosing the branch cuts, the function can be properly defined and its behavior can be understood in different regions of the complex plane.

3. Why is the branch cut argument important in science?

The branch cut argument is important in science because it allows us to better understand and define complex functions, which are often used to describe physical phenomena. By using this argument, we can avoid mathematical inconsistencies and better predict the behavior of these functions in different scenarios.

4. What are some examples of functions that use the branch cut argument?

Some examples of functions that use the branch cut argument include the logarithm, square root, and inverse trigonometric functions. These functions have multiple branches and their behavior can change depending on the chosen branch cuts. Other examples include functions used in quantum mechanics and electromagnetism.

5. How can the branch cut argument be applied in real-world situations?

The branch cut argument can be applied in various real-world situations, such as in physics and engineering. For example, in quantum mechanics, it is used to understand the behavior of wave functions and to properly define the energy levels of particles. In engineering, it can be used to analyze and optimize the behavior of complex systems, such as electrical circuits and signal processing algorithms.

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