Derivation of second order Adams-Bashforth

In summary, the method in question is based on the idea of using the integral from xk to xk+1 to estimate the value of yk+1. To simplify the equation, the integral is moved to the origin and replaced with polynomials, specifically 1 and x. The constants c0 and c1 are then solved for to ensure that the integral is exact for all constants and linear polynomials. This approach is simpler than using higher order polynomials and still yields the desired solution.
  • #1
goggles31
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My notes state that the method is constructed based on the idea:
yk+1=yk+∫f(x,y)dx where the integral is taken from xk to xk+1
We can estimate the integral by considering
∫f(x)dx (from xk to xk+1) =c0fk+c1fk-1
To simplify the equation, we move xk to the origin such that
∫f(x)dx (from 0 to h) =c0f(0)+c1f(-h)

Starting from below, I start to get confused.
It says "Replace f(x) with the polynomials, we have"
f(x)=1 : h=c0(1)+c1(1)
f(x)=x : h2/2=c0(0)+c1(-h)
Solving for c0 and c1,
c0=3h/2 and c1=-h/2 giving
yk+1=yk+h/2*(3fk-fk-1) + O(h3)

I've gone through the working and understand where the numbers come from, but I have no idea why they replace f(x) with 1 and x. Why not x2 or x3? I've gone through some books but they derive this with the Taylor's series and I also understand that. I just don't understand the part I mentioned.
 
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  • #2
goggles31 said:
My notes state that the method is constructed based on the idea:
yk+1=yk+∫f(x,y)dx where the integral is taken from xk to xk+1
We can estimate the integral by considering
∫f(x)dx (from xk to xk+1) =c0fk+c1fk-1
To simplify the equation, we move xk to the origin such that
∫f(x)dx (from 0 to h) =c0f(0)+c1f(-h)

Starting from below, I start to get confused.
It says "Replace f(x) with the polynomials, we have"
f(x)=1 : h=c0(1)+c1(1)
f(x)=x : h2/2=c0(0)+c1(-h)
Solving for c0 and c1,
c0=3h/2 and c1=-h/2 giving
yk+1=yk+h/2*(3fk-fk-1) + O(h3)

I've gone through the working and understand where the numbers come from, but I have no idea why they replace f(x) with 1 and x. Why not x2 or x3? I've gone through some books but they derive this with the Taylor's series and I also understand that. I just don't understand the part I mentioned.

As I understand the point is to choose the constants ##c_0## and ##c_1## such that the integral ##\int_0^h f(x) dx## is exact if f(x) is a polynomial of degree ##n\leq 1##, i.e. for all constants and linear polynomials. All such polynomials can be written in the form ##p_1(x)=a\cdot 1+b\cdot x##, for some constants ##a## and ##b##. We can thus consider ##1## and ##x## as basis functions. If we determine ##c_0## and ##c_1## such that ##\int_0^h 1 dx## and ##\int_0^h x dx ## are reproduced exactly, ##\int_0^h p_1(x) dx## can be expressed in terms of the aforementioned integrals over ##1## and ##x## .
 
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  • #3
Those are the two simplest linearly independent examples of f(x) that the method needs to work for. So they are the easiest ones to use to see what c0 and c1 should be. It would be more complicated to use x2 or x3. I haven't thought it through, but those may be so complicated that they won't give you the solution for c0 and c1, but I think they will work also.

PS. Even if x2 and x3 work, they may give a different answer and not be the Adams-Bashforth method.
 
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  • #4
eys_physics said:
As I understand the point is to choose the constants ##c_0## and ##c_1## such that the integral ##\int_0^h f(x) dx## is exact if f(x) is a polynomial of degree ##n\leq 1##, i.e. for all constants and linear polynomials. All such polynomials can be written in the form ##p_1(x)=a\cdot 1+b\cdot x##, for some constants ##a## and ##b##. We can thus consider ##1## and ##x## as basis functions. If we determine ##c_0## and ##c_1## such that ##\int_0^h 1 dx## and ##\int_0^h x dx ## are reproduced exactly, ##\int_0^h p_1(x) dx## can be expressed in terms of the aforementioned integrals over ##1## and ##x## .
Yes. And it is wise to match the lower order polynomials before worrying about matching higher orders. So that makes good sense.
 

Related to Derivation of second order Adams-Bashforth

What is the Adams-Bashforth method?

The Adams-Bashforth method is a numerical integration technique used to approximate the solution of a differential equation. It is a multi-step method that uses a combination of previous and current values of the function to calculate the next value. It is commonly used in solving initial value problems in scientific and engineering applications.

How is the second order Adams-Bashforth method derived?

The second order Adams-Bashforth method is derived by using the trapezoidal rule to approximate the integral in the first order Adams-Bashforth method. This involves using two previous function values to calculate the next value. By using the trapezoidal rule, the error in the approximation is reduced to second order.

What is the formula for the second order Adams-Bashforth method?

The formula for the second order Adams-Bashforth method is given by:

yn+1 = yn + (h/2)[3f(tn,yn) - f(tn-1,yn-1)]

where h is the step size, tn and yn are the current time and function values, and tn-1 and yn-1 are the previous time and function values.

What are the advantages of using the second order Adams-Bashforth method?

The second order Adams-Bashforth method has several advantages, including:

1. It is a simple and easy to implement method.
2. It has a higher accuracy compared to the first order Adams-Bashforth method.
3. It has a larger stability region, making it more stable for larger step sizes.
4. It can be easily extended to higher order methods.
5. It is efficient for solving initial value problems with smooth solutions.

What are the limitations of using the second order Adams-Bashforth method?

Despite its advantages, the second order Adams-Bashforth method also has some limitations, including:

1. It is an explicit method, which means that the step size has to be small enough to ensure stability.
2. It can only be used for solving initial value problems, not boundary value problems.
3. It may produce inaccurate results for problems with discontinuous solutions.
4. It may become unstable for stiff problems.
5. It requires previous function values, which may not be available for certain problems.

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