Is this the Correct Equation for Approximating y(0.8) Using Euler's Method?

In summary, the conversation is about using Euler's method to approximate the value of y at a given point in a differential equation. The person is given a problem and is trying to find the correct term for the top right box in the table, which represents y(0.4). They are given the correct answer of 0.20000 and are asked to find the correct term for the top right box, which is y(0.8). They use different values for Δt to approximate y(0.4) and y(0.8) and discuss the formula for finding the number of iterations needed.
  • #1
alane1994
36
0
OK, my homework system says that the 0.20000 is correct... but all of my others are incorrect...

Is this the correct term for the top right box?:confused:

[tex]y(0.8)=y(0.4)+(\Delta{t} \times y^{\prime}(0.4))[/tex]
OR
[tex]y(0.8)=y(0.4)-(\Delta{t} \times y^{\prime}(0.4))[/tex]

According to the 0.20000 answer... the top one is correct.

[FONT=MathJax_Main]Δ[/FONT][FONT=MathJax_Math]t[/FONT]​
Approximations of y(0.4)Approximations of y(0.8)
0.40.20000?
0.2
0.1
0.05
 
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  • #2
Since you have been given another problem, I'll work the original in full.

We are given:

$\displaystyle \frac{dy}{dx}=-2y$ where $\displaystyle y(0)=1$

I would generalize as follows:

Using Euler's method for this IVP, we find the recursion:

$\displaystyle y_{n+1}=y_{n}\left(1-2\Delta t \right)$ where $\displaystyle y_0=1$

which gives us the closed-form:

$\displaystyle y_n=\left(1-2\Delta t \right)^n$

a) To approximate $\displaystyle y(0.4)$, we find with:

i) $\displaystyle \Delta t=0.4\,\therefore\,n=1$ we have

$\displaystyle y(0.4)\approx y_1=1-2(0.4)=0.2$

ii) $\displaystyle \Delta t=0.2\,\therefore\,n=2$ we have

$\displaystyle y(0.4)\approx y_2=(1-2(0.2))^2=0.36$

iii) $\displaystyle \Delta t=0.1\,\therefore\,n=4$ we have

$\displaystyle y(0.4)\approx y_4=(1-2(0.1))^4=0.4096$

iv) $\displaystyle \Delta t=0.05\,\therefore\,n=8$ we have

$\displaystyle y(0.4)\approx y_8=(1-2(0.05))^8=0.43046721$

b) To approximate $\displaystyle y(0.8)$, we find with:

i) $\displaystyle \Delta t=0.4\,\therefore\,n=2$ we have

$\displaystyle y(0.4)\approx y_2=(1-2(0.4))^2=0.04$

ii) $\displaystyle \Delta t=0.2\,\therefore\,n=4$ we have

$\displaystyle y(0.4)\approx y_4=(1-2(0.2))^4=0.1296$

iii) $\displaystyle \Delta t=0.1\,\therefore\,n=8$ we have

$\displaystyle y(0.4)\approx y_8=(1-2(0.1))^8=0.16777216$

iv) $\displaystyle \Delta t=0.05\,\therefore\,n=16$ we have

$\displaystyle y(0.4)\approx y_{16}=(1-2(0.05))^{16}=0.185302018885$
 
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  • #3
Suppose we are given the IVP:

$\displaystyle \frac{dy}{dx}=ky$ where $\displaystyle 0\ne k\in{R}$ and $\displaystyle y(x_0)=y_0$

We then obtain using Euler's method:

$\displaystyle y_{n+1}=y_0(1+k\Delta x)^n$

where $\displaystyle \Delta x=\frac{x_n-x_0}{n}$

So, by solving the IVP, we should expect then that:

$\displaystyle y_0\lim_{n\to\infty}\left(1+\frac{k(x_n-x_0)}{n} \right)^n=y_0e^{k(x_n-x_0)}$

You should verify this is true using L'Hôpital's rule.
 
  • #4
I GOT IT! (Party)(Party)(Dance)(Dance)(Bigsmile)...(Cool)

In the table at the top the [tex]y(0.4)=y(t_{k})[/tex].

You have the equation [tex]t_{k}=\Delta{t} \times k[/tex]

You know the [tex]y(t_{k})[/tex] , as well as the [tex]\Delta{t}[/tex], you then just solve for "k"!

"k" is the number of iterations of it that you have to do.
 
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  • #5


It appears that the top right box is asking for the correct term for the equation for approximating y(0.8). Based on the given information, the top equation (y(0.8)=y(0.4)+(\Delta{t} \times y^{\prime}(0.4))) is the correct one. The 0.20000 answer confirms this. However, it is unclear what the other incorrect answers are referring to. It is important to carefully check the equations and calculations to ensure accuracy when using Euler's Method.
 

FAQ: Is this the Correct Equation for Approximating y(0.8) Using Euler's Method?

What is Euler's Method Continued?

Euler's Method Continued is an extension of the original Euler's Method, which is a numerical method used to approximate solutions to ordinary differential equations. It is a simple and effective way to approximate solutions to differential equations, even when the equations cannot be solved analytically.

How does Euler's Method Continued differ from the original Euler's Method?

Euler's Method Continued is similar to the original method in that it uses a step-by-step approach to approximate solutions. However, it also uses a correction term to improve the accuracy of the approximation, making it more reliable for solving complex differential equations.

When should I use Euler's Method Continued?

Euler's Method Continued is most useful when the differential equation cannot be solved analytically, or when it is too complicated to solve using other numerical methods. It is also a good choice when a rough approximation of the solution is sufficient.

What are the limitations of Euler's Method Continued?

One limitation of Euler's Method Continued is that it can only approximate solutions to first-order differential equations. It also may not produce accurate results for highly nonlinear or rapidly changing functions. Additionally, the step size used in the method can greatly affect the accuracy of the approximation.

Are there any alternatives to Euler's Method Continued?

Yes, there are many alternatives to Euler's Method Continued, including higher-order methods such as the Runge-Kutta method and the Adams-Bashforth method. These methods may provide more accurate solutions, but they also require more computational resources. The choice of method ultimately depends on the specific needs and constraints of the problem at hand.

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