Generalizing separation technique

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In summary, the conversation discusses the possibility of using the separation technique to solve the equation y'(x) = A(x)y(x), where A(x) is a linear operator and y(x) is a vector. It is noted that this method can be generalized to give an explicit formula for the solution y(x), but it is not practical to use in most cases. Instead, it is used to prove existence and uniqueness of the solution. The conversation also discusses the idea of using iterations to find the solution, but it is not clear how to do this with integrals.
  • #1
jostpuur
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[tex]
\left[\begin{array}{c}
y'_1(x) \\ \vdots \\ y'_n(x) \\
\end{array}\right]
=
\left[\begin{array}{ccc}
f_{11}(y) & \cdots & f_{1n}(y) \\
\vdots & & \vdots \\
f_{n1}(y) & \cdots & f_{nn}(y) \\
\end{array}\right]
\left[\begin{array}{c}
g_1(x) \\ \vdots \\ g_n(x) \\
\end{array}\right]
[/tex]

If n=1, then this can be solved with the separation technique. Suppose n>1 and that [itex]f[/itex] is invertible. Could the separation technique be generalized to give some explicit formula for solution y(x)? I tried without success. Anyone dealt with problems like this ever?
 
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  • #2
As written I cannot say I do not know what y on the right hand side means.

If you mean, or have use for
[tex]\left[\begin{array}{c}y'_1(x) \\ \vdots \\ y'_n(x) \\\end{array}\right]=\left[\begin{array}{ccc}f_{11}(x) & \cdots & f_{1n}(x) \\\vdots & & \vdots \\f_{n1}(x) & \cdots & f_{nn}(x) \\\end{array}\right]\left[\begin{array}{c}y_1(x) \\ \vdots \\ y_n(x) \\\end{array}\right][/tex]

Then yes this is called the method of Peano-Baker.
A good reference is Ince Ordinary differential equations.
The idea is
y'=Ay
A and y being functions of x
A a linear operator y a vector
let I be integration say from 0 to x
suppose when x=0 y=c
y=c+IAy
y'=Ac+AIAy
y=c+IAc+IAIAy
y=c+IAc+IAIAc+IAIAIAy
leting the sum go to infinity we have a geometric series
y=((IA)^0+(IA)^1+(IA)^2+...)c
or
y={[(IA)^0-(IA)^1]^-1}c
we can prove this works.
It can be used in principle, but is more usefule to prove existence-uniqueness since it is highly impractical.
we may think of this as a generalization of
y'=Ay,A'=0,y(0)=c->y=exp(Ax)c
ie
y'=Ay,y(0)=c->y={[(IA)^0-(IA)^1]^-1}c
in both cases the "explicit" formula as written is not enough we often want to know more
 
  • #3
I see. The equation

[tex]
y'(x) = A(x)y(x)
[/tex]

is equivalent with

[tex]
y(x) = y(0) + \int\limits_0^x du\; A(u)y(u),
[/tex]

so the iteration attempt

[tex]
y_0(x) = y(0)
[/tex]

[tex]
y_{n+1}(x) = y(0) + \int\limits_0^x du\; A(u)y_n(u)
[/tex]

seems natural. If the iterations converge towards the solution, it follows that the solution is given by the series

[tex]
y(x) \;=\; \Big(1 \;+\; \int\limits_0^x du\; A(u) \;+\; \int\limits_0^x du\; \int\limits_0^u du'\; A(u)A(u') \;+\; \int\limits_0^x du\; \int\limits_0^u du'\; \int\limits_0^{u'} du''\; A(u) A(u') A(u'') \;+\; \cdots\Big)y(0).
[/tex]

But I didn't quite get the geometric series part. From equation

[tex]
S = 1 + q + q^2 + q^3 + \cdots
[/tex]

follows

[tex]
qS = q \;+\; q^2 \;+\; q^3 \;+\; \cdots = S - 1\quad\implies\quad S = \frac{1}{1-q},
[/tex]

but how do you do the same with the iterated integrals? If we define the time evolution operator to be

[tex]
U(x) \;=\; 1 \;+\; \int\limits_0^x du\; A(u) \;+\; \int\limits_0^x du\;\int\limits_0^u du'\; A(u) A(u') \;+\; \cdots,
[/tex]

then the calculation

[tex]
\int\limits_0^{x'} dx\; A(x)U(x) \;=\; \int\limits_0^{x'} dx\; A(x) \;+\; \int\limits_0^{x'} dx\;\int\limits_0^x du\; A(x) A(u) \;+\; \cdots \;=\; U(x') \;-\; 1
[/tex]

doesn't lead anywhere.
 
Last edited:

What is generalizing separation technique?

Generalizing separation technique is a process used in scientific research to separate and identify various components of a mixture. It involves using different physical and chemical methods to isolate and purify substances for further analysis.

What are some common methods used in generalizing separation technique?

Some common methods used in generalizing separation technique include filtration, distillation, chromatography, and centrifugation. Each of these methods has its own unique principles and applications, and they can be combined to achieve more effective separation.

Why is generalizing separation technique important in scientific research?

Generalizing separation technique is important in scientific research because it allows scientists to isolate and analyze individual components of a mixture, which can provide valuable information about their properties and behavior. This can lead to a better understanding of the mixture as a whole and the development of new technologies and products.

What are some challenges in generalizing separation technique?

One of the main challenges in generalizing separation technique is the complexity and diversity of mixtures. Some mixtures may contain a large number of components with similar properties, making it difficult to separate them using traditional methods. Additionally, some substances may be present in very small quantities, requiring highly sensitive techniques for detection and separation.

How can generalizing separation technique be applied in real-world situations?

Generalizing separation technique has a wide range of applications in various industries, including pharmaceuticals, environmental science, and food production. For example, it can be used to purify and extract active ingredients from natural sources for drug development, or to remove pollutants from water and air. It is also commonly used in food processing to separate and purify different components of a food product.

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