Asymptotic Expansion for a Differential Equation with a Small Parameter

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In summary, the leading order match asymptotic expansion for the given differential equation is to find the outer solution by setting \epsilon = 0 and solving for y' = f(x), then finding the inner solution near the boundary layer (x=0) and pushing both towards each other in an overlap region to ensure they match. The outer problem involves solving for y(x) = \int f(x)dx.
  • #1
haywood
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What would be the leading order match asymptotic expansion for the following differential equation?
[tex]\epsilon y'' = f(x) - y' [/tex]where f(x) is continuous, [tex]\epsilon<<1[/tex]
and y(0) = 0, y(1) = 1

Thanks in advance,
A.Haywood
 
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  • #2
First, what is an "asymptotic expansion", both in general and for this particular problem? Then what is meant by a "leading order match"?
 
  • #3
Firstly, thank you for your response.
To the best of my knowledge, an asymptotic expansion is in general defined this way:

1. First, an asymptotic sequence is formed from functions called scale, or gauge, or basis functions, denoted [tex]\phi_{1}\phi_{2},...[/tex]. These functions are well-ordered, which means that [tex]\phi_{n}=o(\phi_{m}) [/tex] as some [tex]\epsilon[/tex] (epsilon)gets really really small for all m and n that satisfy m<n

2. Now, if [tex]\phi_{1}\phi_{2},...[/tex] is an asymptotic sequence, then f(epsilon) has an asymptotic expansion to n terms, with respect to this sequence, if and only if

[tex]f = {^m}\sum_{k=1} a_{k}\phi_{k}(\epsilon)+o(\phi_{m})[/tex] for m=1,...,n as epsilon gets really really small towards like 0. The [tex]a_{k}[/tex] are independent of [tex]\epsilon[/tex].

Finally, all this enables us to write f~[tex]a_{1}\phi_{1}(\epsilon)+a_{2}\phi_{2}(\epsilon)+...+a_{n}\phi_{n}(\epsilon) [/tex] as [tex]\epsilon\rightarrow 0[/tex]. Here, the ~ denotes asymptotic.


Whew! Now, for this particular problem... I think the procedure is to find the outer solution away from the boundary layer (reduce given original equation by setting [tex]\epsilon[/tex] = 0), and then the inner solution near the boundary layer (in this case near x=0) and then push both towards each other into an overlap region in which they are supposed to match!

I have started on the outer problem thus far:
y' = f(x) so y(x) = [tex]\int f(x)dx[/tex] and now what do I do with this integral?

Thanks again!
A.Haywood
 

1. What is "leading order matched"?

Leading order matched refers to a technique used in theoretical calculations in physics and other sciences. It involves matching the leading terms in an expansion of a mathematical expression to the terms in another expression, in order to improve the accuracy of the calculation.

2. How does "leading order matched" improve the accuracy of calculations?

By matching the leading terms in an expansion, "leading order matched" takes into account the most significant contributions to a calculation, leading to more accurate results. It also helps to reduce the impact of higher-order terms, which may be less relevant or have more uncertainty.

3. What are the limitations of using "leading order matched"?

One limitation is that it may not accurately represent the behavior of a system at higher orders, especially if there are significant contributions from those terms. Additionally, the accuracy of the results relies on the chosen expansion and match, so incorrect choices may lead to inaccurate results.

4. In what fields or applications is "leading order matched" commonly used?

"Leading order matched" is commonly used in theoretical calculations in physics, such as in particle physics, cosmology, and quantum field theory. It is also used in other fields, such as chemistry, engineering, and economics, where accurate calculations are important.

5. How is "leading order matched" different from other approximation techniques?

Unlike other approximation techniques, "leading order matched" specifically focuses on matching the leading terms in an expansion, rather than estimating the overall behavior of a system. This can result in more accurate results but may also require more complex calculations. Other approximation techniques may take into account a wider range of terms or use simpler methods to estimate the behavior of a system.

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