Numerical Analysis/stability of Multistep methods

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For multistep methods, the problems involved with consistence, convergence and stability are complicated because of the number of approximations involved at each step. In the one step method, the approximation w_{i+1} depends only on the previous approximation w_i, whereas the multistep methods use at least two of the previous approximations, and the usual method that are employed involve more.

Stable Multistep Method[edit]

Characteristic polynominals[edit]

For the multistep method:


the polynominal

P(\lambda)=\lambda^m-a_{m-1}\lambda^{m-1}-a_{m-2}\lambda^{m-2}-...a_1\lambda-a_0 ,

is called the characteristic polynominal of the above mutistep method.

The stability of a multistep method with respect to round-off error is dictated by the magnitudes of the zeros of the characteristic polynominal.

Root condition[edit]

Let \lambda_1,\lambda_2,...,\lambda_m, denote the (not necessarily distinct) roots of the characteristic equation

P(\lambda)=\lambda^m-a_{m-1}\lambda^{m-1}-a_{m-2}\lambda^{m-2}-...a_1\lambda-a_0=0 ,

associated with the multistep difference method


If the absolute value |\lambda_i|\le 1, for each i=1,2,...,m, and all roots with abosolute value 1 are the simple roots, then the difference method is said to satisfy the root condition.

Stability Definitions[edit]

  1. Methods that satisfy the root condition and have \lambda=1 as the only root of the characteristic equation of the magnitude one are called strongly stable.
  2. Methods that satisfy the root condition and have more than one distinct root with magnitude one are called weakly stable.
  3. Methods that do not satisfy the root condition are called unstable.

Stable Multistep methods[edit]

A multistep method of the form


is stable if and only if it satisfies the root condition. Moreover, if the difference method is consistent with the differential equation, then the method is stable if and only if it is convergent.



The fourth-order Adams-Bashfoth method is


where f_i=f(t_i,w_i)\,. The characteristic equation is


so we find the characteristic roots to be


Thus the 4th-order Adams Method satisfies the root condition and is strongly stable.

Example 2[edit]

Milne's Method is


where f_i=f(t_i,w_i)\,. The characteristic equation is


so the characteristic roots are \lambda_1=1,\quad\lambda_2=-1,\quad\lambda_3=i,\quad\text{and}\quad\lambda_4=-i.

Thus the 4th-order Milne's Method satisfies the root condition, but it is only weakly stable.

Absolute Stability & Region of Absolute stability[edit]


Apply a numerical method to initial-value problem

y'=\lambda y
y(0)=\alpha \quad\text{where}\quad \text{Re}(\lambda)<0\,.

Suppose that a round off error \xi_0 is introduced in the initial condition for this method. At the nth step the round off error is \xi_n. Provided the step size h is chosen to satisfy |\xi_n|<|\xi_0|, the numerical method is said to be absolutely stable for the step size h. And R=\{h\lambda \in \mathbb{C} | |\xi_n|<|\xi_0| \} is said to be region of absolute stability for numerical method.

Region of absolute stability for one-step method[edit]

In general, when a one-step method is applied to the test equation, a function Q exists with the property that the difference method gives


The initial round-off error \xi_{0} and the round-off error at the ith step \xi_{i} will satisfy \xi_{i+1}=Q(h\lambda)\xi_i which is \xi_{i+1}=Q^i(h\lambda)\xi_0.

The inequality |\xi_i|<|\xi_0| will hold if |Q(h\lambda)|<1. Thus, region R of absolute stability for a one-step method is

R=\{h\lambda \in \mathbb{C} | |Q(h\lambda)|<1 \}\,.

Region of absolute stability for multistep methods[edit]

Consider the k-step method

w_{n+1}=\sum_{j=1}^{k} a_{k-j} w_{n+1-j}+h \sum_{j=0}^{k} b_{k-j} f_{n-j+1}

Applying it to

y'=\lambda y

we get

w_{n+1}=\sum_{j=1}^{k} a_{k-j} w_{n+1-j}+\lambda h \sum_{j=0}^{k} b_{k-j} w_{n-j+1}
\Leftrightarrow (1-\lambda h b_k)w_{n+1}-\sum_{j=1}^{k}(a_{k-j}-\lambda h b_{k-j})w_{n+1-j}=0\,.

The characteristic polynominal of the method is

 Q(z,h\lambda)=(1-\lambda h b_k)z^k-\sum_{j=1}^{k}(a_{k-j}-  \lambda h b_{k-j})z^{k-j}=0

The region R of absolute stability for a multistep method is

R=\{h\lambda \in \mathbb{C} | |\beta_j|<1,\text{ for all zeros }\beta_{j}\text{ of }Q(z,h\lambda) \}.


Determine the region of absolute stability for two step method w_{i+1}=w_i+h/2(3f_i-f_{i-1}).

Applying this method to: y'=\lambda y, gives

w_{i+1}=w_{i}+\lambda h (3w_{i}-w_{i-1})/2
\Leftrightarrow w_{i+1}-(1+3h \lambda/2)w_{i}+\lambda h/2 w_{i-1}=0\,.

The characteristic polynominal of above method is


All the zeros of the characteristic polynominal are

z_{1,2}={+(1+3h \lambda/2)\pm\sqrt{1+\lambda h+ 9 \lambda^2 h^2/4}\over2}\,.

Thus the region of absolute stability for this method is R=\{h\lambda \in \mathbb{C} | |z_{1,2}|<1 \}.


Exercise 1[edit]

Find the region of the absolute stability of Euler's method:


Exercise 2[edit]

Find the region R of the absolute stability of Trapezoidal method


Exercise 3[edit]

Make a table of the interval of absolute stability for four one-step methods: Euler's method, Backward- Euler, M-Euler and Trapezoidal method.

Exercise 4[edit]

Find the Region of absolute stability of Adams-Bashforth explict Four-step Method



The following is a quiz covering information presented on the associated multistep method.

1. True or False: The multistep methods are always stable methods.


2. True or False: If the multistep method is strongly stable then it is weakly stable.


3. Check all that apply: Which of the following statements are right?...

The root condition can always be satisfied for the multistep method.
Methods that satisfy the root condition and have more than one distinct root with magnitude one are called strongly stable.
Methods that do not satisfy the root condition are unstable.
The Euler's method and the Backward Euler method have the same region of absolute stability.

4. Given the following ODE method

y'=-e^xy+x+1, 0\le x \le 1


then which h make sure the absolute stability of the method.


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