Why does reduction of order work for linear ODEs?

AI Thread Summary
Reduction of order is a mathematical method used to find a second solution to a linear ordinary differential equation (ODE) when one solution is already known. The assumption that the second solution can be expressed as y2(t) = v(t) * y1(t) arises from the linearity of the ODE, allowing for the construction of new solutions based on existing ones. The function v(t) is determined by substituting y2(t) back into the original equation, leading to a solvable equation for v(t). This method works consistently due to the properties of linear differential equations, which ensure that any linear combination of solutions is also a solution. Understanding this theory enhances comprehension of the behavior and solutions of linear ODEs.
theBEAST
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This is not a homework problem, I just want to understand some theory behind this mathematical method.

Specifically, if we know that one solution is y1(t), then why is the second solution in the form

y2(t) = v(t) * y1(t)?​

Where v(t) is the function that you need to solve for. Why does this assumption always work?
 
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theBEAST said:
This is not a homework problem, I just want to understand some theory behind this mathematical method.

Specifically, if we know that one solution is y1(t), then why is the second solution in the form

y2(t) = v(t) * y1(t)?​

Where v(t) is the function that you need to solve for. Why does this assumption always work?
The Wikipedia entry for reduction of order gives a good explanation.

http://en.wikipedia.org/wiki/Reduction_of_order
 
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