Abstract
We use Newton’s method to solve previously unsolved problems, expanding the applicability of the method. To achieve this, we used the idea of restricted domains which allows for tighter Lipschitz constants than previously seen, this in turn led to a tighter convergence analysis. The new developments were obtained using special cases of functions which had been used in earlier works. Numerical examples are used to illustrate the superiority of the new results.
1. Introduction
Let be a differentiable operator in the sense of Fréchet, where and are Banach spaces and is a nonempty and open set. A plethora of problems from many diverse disciplines are formulated using modeling which looks like
Hence, the problem of locating a solution for Equation (1) is very important. Most people develop iterative algorithms approximating under some conditions, since a closed form solution cannot easily be obtained in general. The most widely used iterative method is Newton’s method defined for an initial point by
Numerous convergence results appear in the literature based on which .
In this article, we introduce new semilocal convergence results based on our idea of restricted convergence region through which we locate a more precise set containing . This way, the majorizing constants and scalar functions are tighter leading to a finer convergence analysis.
To provide the semilocal convergence analysis Kantorovich used the condition [1]
Let function be non-decreasing and continuous. A weaker condition is [2,3,4,5,6]
We shall find a tighter domain than , where Equation (4) is satisfied. This way the new convergence analysis shall be at least as precise.
2. Semilocal Convergence
Theorem 1
(Kantorovich’s theorem [1]). Let and be Banach spaces. Let also be a twice continuously differentiable operator in the sense of Fréchet where Ω is a non-empty open and convex region. Assume:
- and there existswith,
- ,
- , ,
- ,
- , where.
Then, Newton’s sequence defined in Equation (2) converges to a solution of the equation . Moreover, , , for all Furthermore, the solution is unique in , where , if , and in , if , for some . Furthermore, the following error bounds hold
and
where
and
The Kantorovich theorem can be improved as follows:
Theorem 2.
Let and be Banach spaces. Let be a twice continuously differentiable operator in the sense of Fréchet. Assume:
- and there exists with ,
- ,
- , ,
- , ,
- , where ,
- , where .
Then, sequence generated by Method (2) converges to . Moreover, , , . Furthermore, the solution is unique in , where
and in
for some . Furthermore, the following error bounds hold
and
where
and
Proof.
The iterates stay in by the proof of the Kantorovich theorem, which is a more precise location for the solution than , since . □
Remark 1.
If , Theorem 1 reduces to the Kantorovich theorem, where k is the Lipschitz constant for used in [1]. We get and so holds in general.
Notice that
so the Newton–Kantorovich sufficient convergence condition has been improved and under the same effort, because the computation of k requires the computation of or as special cases.
Moreover, notice that if provided that and of Theorem 2 holds on with replacing , then Theorem 2 can be extended even further with , , replacing and , respectively, since , so .
Concerning majorizing sequences, define
where
According to the proofs, and are majorizing sequences tighter than and , respectively, and as such, they converge under the same convergence criteria. Notice also that and .
Example 1.
Let , , , and .
Case 1.. Then, we have that
and
so
We see that Kantorovich’s result [4] (see Theorem 1) cannot be applied, since
Case 2.. Then, we get
where
so by Theorem 2, Newton’s method converges for
since
Case 3. provided that . In this case, we obtain from
so
Therefore, we must have that
and
which are true for since , so . Hence, we have extended the convergence interval of the previous cases.
The sufficient convergence criterion for the modified Newton’s method
is the same as the Kantorovich condition . In [7], though we proved that this condition can be replaced by which is weaker if . In the case of the example at hand, we have that this condition is satisfied as in the previous case interval. Therefore, by restricting the convergence domain, sufficient convergence criteria can be obtained for Newton’s method identical to the ones required for the convergence of the modified Newton’s method. The same advantages are obtained if the preceding Lipschitz constants are replaced by the functions that follow.
It is worth noting that the center-Lipschitz condition (not introduced in earlier studies) makes it possible to restrict the domain from to (or ), where the iterates actually lie and where
can be used instead of the less tight estimate
used in Theorem 1 and in other related earlier studies using only condition in Theorem 1.
Next, the condition
is replaced by
Next, we show how to improve these results by relaxing Equation (5) using even weaker conditions
where is a non-decreasing continuous function satisfying . Suppose that equation has at least one positive solution. Denote by the smallest such solution.
If function v is strictly increasing, then we can choose .
Notice that Equation (5) implies Equations (6) and (7) or Equations (6) and (8) but not necessarily vice versa. Moreover, we have that
and
Next, we show that or can replace in the results obtained in Reference [4]. Then, in view of Equations (9)–(11), the new results are finer and are provided without additional cost, since requires the computation functions v, and as special cases. Notice that function v is needed to determine (i. e., and ) and that and .
3. Bratu’s Equation
Bratu’s equation is defined by the following nonlinear integral equation
where , and the kernel T is the Green’s function
Let and . It follows from [8] that Equation (12) has two solutions such that , provided that for for each , where . Next, we show a sketch of both solutions in Figure 1.
Figure 1.
The two real solutions of Bratu’s Equation (12).
Bratu’s equation appears in connection to many problems: combustion, heat transfer, chemical reactions, and nanotechnology [9].
Using Newton’s method, we approximate the solutions of Bratu’s equation. Let be defined by
Therefore, it is clear that is not bounded in a general domain . However, it is hard to find a region containing a solution of and such that is bounded there.
Our aim is to solve using Newton’s method
Then, we solve
Using m nodes in the Gauss-Legendre quadrature formula
where the nodes and the weights are known. We can write
or
where
We shall relate sequence with its majorizing sequence
Clearly, Theorems 1 and 2 hold if operator F is defined by Equation (16) and Newton’s method in the form of Equation (14) is used.
We shall verify the hypotheses of these theorems, so we can solve our problem. To achieve this, sets
and
where and . Moreover, we have
and , where we used the infinity norm. Notice that is not bounded, since is increasing as a function of . Hence, Theorem 1 or Theorem 2 cannot be used.
Remark 2.
Notice that Kantorovich’s Theorem 1 cannot apply, although is Lipschitz continuous.
We look for a bound for in such domain ([6]). If solves Equation (16), we have , where and () are roots of the scalar equation . (See Figure 2). We choose such that with .
Figure 2.
.
Example 2.
Let us consider Bratu’s Equation (12) with , and to obtain and By choosing , , , we see that with
so ,
The conditions of Theorem 2 hold.
Consequently, we obtain the solution after three iterations (see Table 1).
Table 1.
The solution of Equation (12) for , and .
Concerning Theorem 1, we define
as an auxiliary function to construct majorazing sequence . We also use the sequence
Note then that , , and . We also obtain the a priori error estimates shown in Table 2, which shows that the error bounds are improved under our new approach.
Table 2.
Absolute error and a priori error estimates.
In this section, we consider the alternative to Equation (4) condition
since is non-decreasing. Then, we look for a function
The solution of Equation (21) is given by
Define also
We suppose in what follows that
Otherwise, i.e., if , then the following results hold with replacing .
Notice that is the function obtained by Kantorovich if and , .
For Bratu’s equation, we have and function (22) is reduced to
with and defined in Equations (17) and (18), respectively. Next, we need the auxiliary results for function .
Lemma 1.
Let be the function defined in Equation (23) and
Then:
- is the unique minimum of in .
- is non-increasing in .
- If , the equation has at least one root in . If is the smallest positive root of , we have .
Next, we define the scalar sequence
Lemma 2.
We need an auxiliary result relating sequence to .
Lemma 3.
Proof.
Observe that
We prove the following four items for all :
- There exists such that ,
- ,
- ,
- .
Firstly, from
exists and
Thirdly,
Fourthly,
Then, if – hold for all , we show in an analogous way that these items hold for too. □
The conditions shall be used:
- and there exists such that ,
- ,
- for ,
- , where is the smallest root of the equation in .
Notice that is increasing and in , since , so that is strictly increasing in . Hence, with .
Theorem 3.
Proof.
Sequence converges, since is its majorizing sequence. Then, if , , for all . Moreover, the sequence is bounded. By the continuity of F, we have , since and .
To show the uniqueness of , let be another solution of Equation (16) in . Notice that . From
it follows that , provided that the operator is invertible. To prove that Q is invertible, we prove equivalently that there exists the operator , where . Indeed, as
so exists. □
Remark 3.
We have by Equation (22) that , where
Remark 4.
- (a)
- If , the results in this study coincide with the ones in [4]. Moreover, if inequality in Equations (9)–(11) is strict, then, the new results have the following advantages: weaker sufficient convergence conditions, tighter error estimates on , and at least as precise information on the location of the solution .
- (b)
- These results can be improved even further, if we simply use the conditionand majorizing function (as in with , ) (also see the numerical section).
Remark 5.
- (a)
- It is worth noting that there are alternative approaches to the root-finding other than Newton’s method [10,11], where the latter one has cubic order of convergence, whereas Newton’s is only quadratic.
- (b)
- If the solution is sufficiently smooth, then one can use generalized Gauss quadrature rules for splines. This way, instead of projecting f into a space of higher-degree polynomials as is done in our article, one can project it to a spline space (see [12,13,14]). These quadratures in general do not affect the convergence order, but they do make the computation more efficient, since fewer quadrature points are required to reach a certain error tolerance.
4. Specialized Bratu’s Equation
Consider the equation
We transform Equation (27) into a finite dimensional problem, as we have done above, with , so that Equation (27) is equivalent to Equation (16) with , , . For this case, we have
where , and
where and .
In Section 2, we have seen that , so that is not bounded. Then, any solution of the particular system given by Equation (16) should satisfy . We can take the region , with and and , where is bounded and contains the solution (see Figure 2). The convergence of Newton’s method to follows Kantorovich’s Theorem 1.
In Theorem 3, set and (according to Remark 3), we have
so, we can choose and
Then, function is defined by
Then, we define
so
Next, we find the solutions and of the equations and to be, respectively:
and
We see that but . Then, the results in [4] cannot assure convergence to but our results guarantee convergence.
Moreover, we have that
5. Conclusions
In this article, we first introduce new Kantorovich-type results for the semilocal convergence on Newton’s method for Banach space valued operators using our idea of convergence regions. Hence, we expand the applicability of Newton’s method. Then, we focus our results on solving Bratu’s equation.
Author Contributions
These authors contributed equally to this work.
Funding
This research received no external funding.
Acknowledgments
We would like to express our gratitude to the anonymous reviewers for their help with the publication of this paper.
Conflicts of Interest
The authors declare no conflict of interest.
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