Solving inexact ODE

In summary, "Solving inexact ODE" discusses methods for addressing ordinary differential equations (ODEs) that may not have precise solutions or require approximations. It emphasizes the importance of numerical techniques and analytical approaches to handle the inherent uncertainties in the equations. The text explores various strategies, including perturbation methods and numerical integration, to derive solutions that provide meaningful insights despite the lack of exactness. Overall, it highlights the relevance of these methods in practical applications where exact solutions are unattainable.
  • #1
member 731016
Homework Statement
Please see below
Relevant Equations
Please see below
For this problem,
1716444809818.png

1716444830751.png

Does someone please know how they combined the two equations for H to get the finial equation ##H(x,y) = .... = c##?

Thanks!
 
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  • #2
ChiralSuperfields said:
Homework Statement: Please see below
Relevant Equations: Please see below

For this problem,
View attachment 345763
View attachment 345764
Does someone please know how they combined the two equations for H to get the finial equation ##H(x,y) = .... = c##?

Thanks!
Take ##H-H## using both expressions. You find that
$$
0=H-H = \xi_1(y) - \frac{y^2}{2} - \xi_2(x)
$$
Moving the ##x##-dependent term to the LHS
$$
\xi_2(x) = \xi_1(y) - \frac{y^2}{2}
$$
The LHS depends only on ##x##, but the RHS does not depend on ##x## so both sides must be equal to the same constant ##-c##. It follows that
$$\xi_2(x) = c$$
and so
$$-xy +\frac{y^2}{2} + x^2y = c$$
 
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  • #3
Here's another way to explain how they came up with H(x, y).

In the first screen shot of the OP, the author found that ##H(x, y) = x^2 - xy + \xi_1(y)## and that ##H(x, y) = -xy + \frac{y^2}2 + x^2y + \xi_2(x)##. The ##\xi_i## functions are functions of a single variable only.

Since the 2nd version of H(x, y) contains a term in y alone, namely ##\frac{y^2}2##, this means that ##\xi_1(y) = \frac{y^2}2##. Also, since the 1st version of H contains no term in x alone, this means that ##\xi_2(x) = 0##. After all, both versions of H(x, y) must be the same.

Hence ##H(x, y) = x^2y - xy + \frac{y^2}2##

The differential equation that was derived from the original pair of equations (that involved t) is ##(2xy - y)dx +(-x + y + x^2)dy = 0##. This can be seen as ##\frac{\partial H(x, y)}{\partial x}dx + \frac{\partial H(x, y)}{\partial y} dy = 0##.

The LHS of the last equation is the total differential of H(x, y). Since the total differential is zero, it must be true that H(x, y) = c, a constant.

BTW, the thread title is misleading, since the equation you're dealing with is exact, not inexact.
 
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  • #4
Thank you for your replies @Orodruin and @Mark44!

Sorry there is a typo in the title. It should be a exact equation.

Thanks!
 
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FAQ: Solving inexact ODE

What is an inexact ordinary differential equation (ODE)?

An inexact ordinary differential equation (ODE) refers to a differential equation where the data or the initial/boundary conditions may be uncertain or imprecise. This can arise from measurement errors, model simplifications, or inherent variability in the system being modeled. Solving inexact ODEs often requires specialized numerical techniques that can accommodate this uncertainty.

How do I approach solving an inexact ODE?

To solve an inexact ODE, one can start by reformulating the problem to account for the uncertainties. This may involve using probabilistic methods, such as stochastic differential equations, or incorporating fuzzy logic. Numerical methods, such as perturbation techniques or Monte Carlo simulations, can also be employed to explore the solution space and quantify the effects of the inexactness.

What are common numerical methods for solving inexact ODEs?

Common numerical methods for solving inexact ODEs include the Euler method, Runge-Kutta methods, and adaptive step-size methods. Additionally, techniques like finite difference methods, finite element methods, and spectral methods can be adapted for inexact scenarios. These methods can be modified to include uncertainty quantification and error analysis to better understand the impact of the inexactness on the solutions.

How does uncertainty in initial conditions affect the solution of an ODE?

Uncertainty in initial conditions can lead to significant variations in the solution of an ODE, particularly in systems that exhibit sensitivity to initial values, a phenomenon known as chaos. Small changes in the initial conditions can result in large differences in the trajectory of the solution over time. Therefore, it is crucial to analyze how these uncertainties propagate through the solution, often using techniques like sensitivity analysis or ensemble methods.

Can inexact ODEs be solved analytically?

While inexact ODEs are often more challenging to solve analytically compared to exact ODEs, certain cases may allow for analytical solutions under specific assumptions about the nature of the inexactness. For example, if the uncertainties can be modeled using specific probability distributions, one might derive solutions that are valid in a statistical sense. However, in many cases, numerical methods are preferred due to the complexity introduced by the inexactness.

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