Understanding the Complex Bounds of the erf(x) Function

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In summary: Thanks for your help.In summary, Jack Mell provided a solution for a complex integral involving the erf function. He parameterized the path for the second integral from the origin, straight up to the point ib by letting t=iy and dt=idy. Then, erf(ib)=\int_0^{ib}e^{-t^2}dt=i\int_0^b e^{y^2}dythanks a lot!
  • #1
mnb96
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If we consider the error function [tex]\mathrm{erf}(x)=\int_{0}^{x}e^{-t^2}dt[/tex]

How can I re-express the following in terms of the erf function?[tex]f(x)=\int_{ib}^{x+ib}e^{-t^2}dt = \\ ?[/tex]

I have troubles with this kind of integrals. How should I treat an integral with complex bounds?
Thanks!
 
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  • #2
Let s = t-ib, then the complex function will appear in the exponent, wile the s integral is from 0 to x.
 
  • #3
mnb96 said:
If we consider the error function [tex]\mathrm{erf}(x)=\int_{0}^{x}e^{-t^2}dt[/tex]

How can I re-express the following in terms of the erf function?[tex]f(x)=\int_{ib}^{x+ib}e^{-t^2}dt = \\ ?[/tex]

How about if you consider a closed path from zero straight up to the point ib, straight across to the point x+ib, and then diagonally down back to the origin. The integral over that path is zero since the integrand is entire. We can then write [itex]\int_0^{ib} f(z)dz+\int_{ib}^{x+ib} f(z)dz+\int_{x+ib}^0 f(z)dz=0[/itex] or [itex]\int_{ib}^{x+ib}f(z)dz=\int_0^{x+ib} f(z)dz-\int_0^{ib}f(z)dz=erf(x+ib)-erf(ib)[/itex] given your definition of erf and [itex]f(z)=e^{-z^2}[/itex].
 
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  • #4
mathman said:
Let s = t-ib, then the complex function will appear in the exponent, wile the s integral is from 0 to x.

...then you get

[tex]
\int_{0}^{x}e^{-(s+ib)^2}ds
[/tex]

I cannot relate that integral to the erf function.
 
  • #5
thanks jackmell!
your solution is interesting!
Unfortunately I have some troubles interpreting the erf function with a complex argument: in particular, could you explain how the limit of [itex]2(erf(x+ib)-erf(ib))[/itex] for [itex]x\rightarrow \infty[/itex] gives the result of the gaussian integral, which is [itex]\sqrt{\pi}[/itex] ?
 
  • #6
Hi. I'm not an expert at this but I believe this is correct:

[itex]\lim_{x\to\infty} \int_{ib}^{x+ib} e^{-t^2}dt=\lim_{x\to\infty}\left\{\int_0^{x+ib} e^{-t^2}dt-\int_{0}^{ib} e^{-t^2}dt\right\}[/itex]

[itex]=\lim_{x\to\infty}\left\{\int_0^x +\int_x^{x+ib}-\int_0^{ib}\right\}[/itex]

and as [itex]x\to\infty [/itex], the center integral goes to zero. Then:

[itex]\lim_{x\to\infty} \int_{ib}^{x+ib} e^{-t^2}dt=\frac{\sqrt{\pi}}{2}-erf(ib)[/itex]

If you like you can parameterize the path for the second integral from the origin, straight up to the point ib by letting t=iy and dt=idy then:

[itex]erf(ib)=\int_0^{ib}e^{-t^2}dt=i\int_0^b e^{y^2}dy[/itex]
 
  • #7
thanks a lot!
now it is clear, and your solutions looks correct.
 

Related to Understanding the Complex Bounds of the erf(x) Function

1. What is the erf(x) function?

The erf(x) function, also known as the error function, is a mathematical function that is commonly used in statistics and applied mathematics. It is defined as the integral of a Gaussian function from 0 to x.

2. How is the erf(x) function calculated?

The erf(x) function is usually calculated using numerical integration methods, as there is no closed-form solution for it. However, there are approximate formulas and special algorithms that can be used to calculate erf(x) efficiently.

3. What are the main applications of the erf(x) function?

The erf(x) function is commonly used in statistics to calculate probabilities and confidence intervals. It also has applications in physics, engineering, and finance, among others.

4. What is the relationship between the erf(x) function and the normal distribution?

The erf(x) function is closely related to the normal distribution, as it is the integral of the Gaussian function, which is the probability density function of the normal distribution. In fact, the erf(x) function is sometimes referred to as the "cumulative distribution function of the normal distribution".

5. Is the erf(x) function used in real-world problems?

Yes, the erf(x) function is used in a wide range of real-world problems, such as calculating probabilities in statistical analyses, modeling random processes, and solving differential equations in physics and engineering problems.

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