From system of first-order to a single ODE

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Discussion Overview

The discussion revolves around the relationship between a system of first-order ordinary differential equations (ODEs) and a single nth-order ODE. Participants explore whether a system of n first-order ODEs can be equivalently represented as a single nth-order ODE, examining the implications of eigenvalues and the structure of the equations.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions how to demonstrate that a system of first-order ODEs can be equivalent to a single nth-order ODE, suggesting that manipulation is straightforward for n=2 but uncertain for larger n.
  • Another participant notes that while an nth-order ODE can always be reduced to a system of first-order ODEs, it is unclear if the reverse is universally true, raising the issue of eigenvalues associated with the system's matrix.
  • A participant proposes that if the matrix leads to n eigenvalues, it indicates an equivalent nth-order ODE, while a lack of n eigenvalues suggests the system may not correspond to an nth-order ODE.
  • One participant provides an argument based on counting unknowns in a specific case with three dependent variables, suggesting that differentiating the equations leads to a system that could potentially yield an uncoupled equation for one variable.
  • Another participant questions the validity of the argument regarding the ability to differentiate and solve for variables, hinting at possible limitations or counterexamples that could arise.
  • Several participants express confusion about the characterization of the 2x2 case as trivial, with one admitting to having previously spoken nonsensically about it.

Areas of Agreement / Disagreement

Participants express uncertainty regarding whether a system of first-order ODEs is always equivalent to a single nth-order ODE, indicating that multiple competing views remain on this topic.

Contextual Notes

Participants note that the discussion may depend on specific conditions, such as the nature of the coefficients in the equations and the structure of the system. There is also mention of potential limitations in differentiating the equations and solving for variables, which may not hold in all cases.

rsq_a
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Is there an easy way to show that the system:

<br /> \begin{align}<br /> x_1&#039; &amp;= p_{11} x_1 + p_{12} x_2 + \ldots + p_{1n} x_n \\<br /> x_2&#039; &amp;= p_{21} x_1 + p_{22} x_2 + \ldots + p_{2n} x_n \\<br /> \ldots &amp;= \ldots \\<br /> x_n&#039; &amp;= p_{n1} x_1 + p_{n2} x_2 + \ldots + p_{nn} x_n<br /> \end{align}<br />

must be equivalent to a single nth order differential equation, like
<br /> a_n y^{(n)} + a_{n-1} y^{(n-1)} + \ldots + a_0 y_n = 0<br />

All the p_{ij} = p_{ij}(t) and a_i = a_i(t). In the case that n = 2, it's easy to show just by manipulation. I assume that it's true in general, but I can't find a slick way to do it.
 
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Interesting... I never thought about it before, usually you want to reduce the nth order ode to the system and not the other way around. An nth order ode is always equivalent to a system of n first order odes. But is a system of n first order odes always equivalent to a nth order ode?

The eigenvalues of the nxn matrix of first order equations give you the n roots of the characteristic equation of the equivalent nth order ode. And the n roots of the characteristic equation of an nth order ode give you the n eigenvalues of the equivalent system.
So if the matrix leads to n eigenvalues, it gives you an equivalent nth order ode. Otherwise, the system is not equivalent to an nth order ode.
 
bigfooted said:
Interesting... I never thought about it before, usually you want to reduce the nth order ode to the system and not the other way around. An nth order ode is always equivalent to a system of n first order odes. But is a system of n first order odes always equivalent to a nth order ode?

The eigenvalues of the nxn matrix of first order equations give you the n roots of the characteristic equation of the equivalent nth order ode. And the n roots of the characteristic equation of an nth order ode give you the n eigenvalues of the equivalent system.
So if the matrix leads to n eigenvalues, it gives you an equivalent nth order ode. Otherwise, the system is not equivalent to an nth order ode.

I think in the case of a constant coefficient ODE, it's perhaps a bit easier to reason (??)

Here is one argument just by counting unknowns. Maybe the first non-trivial example is with 3 dependent variables:<br /> \begin{align}<br /> x_1&#039; &amp;= p_{11} x_1 + p_{12} x_2 + p_{13} x_3 \\<br /> x_2&#039; &amp;= p_{21} x_1 + p_{22} x_2 + p_{23} x_3 \\<br /> x_3&#039; &amp;= p_{31} x_1 + p_{32} x_2 + p_{33} x_3 <br /> \end{align}<br />

where p = p(t). Differentiating the third equation twice, we get
x_3&#039;&#039; = f(x_1, x_1&#039;, x_1&#039;&#039;, x_2, x_2&#039;, x_2&#039;&#039;, x_3, x_3&#039;, x_3&#039;&#039;)

There are thus 6 unknowns (from x1 and x2 and their two derivatives). If you look at the above system, you immediately have two equations for x1 and x2, and you get another 4 by differentiating both equation twice. Thus 6 equations and 6 unknowns. So in some cases, you can solve for {x1, x1', x1'', x2, x2', x2''} in terms of x3, and that gives you an uncoupled equation for x3.

Can someone give some thoughts on where this might fail, and what that means for the eventual high order equation in x3?
 
rsq_a said:
x_3&#039;&#039; = f(x_1, x_1&#039;, x_1&#039;&#039;, x_2, x_2&#039;, x_2&#039;&#039;, x_3, x_3&#039;, x_3&#039;&#039;)
Seems to me that if you differentiate twice it's
x_3&#039;&#039;&#039; = f(x_1, x_1&#039;, x_1&#039;&#039;, x_2, x_2&#039;, x_2&#039;&#039;, x_3, x_3&#039;, x_3&#039;&#039;)
rsq_a said:
There are thus 6 unknowns (from x1 and x2 and their two derivatives). If you look at the above system, you immediately have two equations for x1 and x2, and you get another 4 by differentiating both equation twice.
Well if you differentiate twice here you'll get for example an equation for x_1&#039;&#039;&#039;, so you'll be able to solve for {x1, x1', x1'', x2, x2', x2''} , but the expressions will involve x_1&#039;&#039;&#039; and x_2&#039;&#039;&#039;. I think I vaguely remember finding out at some point that this inversion can't be done in general, but I can't remember how to construct a counter example.
 
Also, why is the 2x2 case trivial?
 
kai_sikorski said:
Also, why is the 2x2 case trivial?

...I've no idea why I thought it was a few days ago. You're right, I was speaking nonsense.
 

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