Abstract
Inequalities play a fundamental role in both theoretical and applied mathematics and contain many patterns of symmetries. In many studies, inequalities have been used to provide estimates of some functions based on the properties of their symmetry. In this paper, we present the following new asymptotic expansion related to the ordinary gamma function , with the recurrence relation of coefficients . Furthermore, we use Padé approximants and our new asymptotic expansion to deduce the new bounds of better than some of its recent ones.
Keywords:
asymptotic expansion; Stirling’s formula; gamma function; Windschitl’s formula; Padé approximants MSC:
33B15; 41A60; 41A21
1. Introduction
Stirling’s formula
is the most well known and used approximation formula for dealing with large factorials [1,2,3]. There are many researchers who have gone to great lengths to create more accurate approximations of and its natural Gamma function extension , where ; . For example, the Stirling series is stated as follows [4]:
which is an extension of Formula (1), where constants , , are Bernoulli numbers. Another asymptotic formula is given by Laplace [4].
Moreover, there are two important approximations that are better than Burnside’s Formula (4). The first one is due to Ramanujan [6]:
which presents a refinement of Stirling’s Formula (1) and was recorded in the book “The lost notebook and other unpublished papers” as a conjecture of Ramanujan based on some numerical calculations (see also [6,7,8,9,10]). The other one is due to Gosper [2].
Mortici [11] improved the Ramanujan Formula (5) by the asymptotic formula:
which is faster than Formula (7). In 2002, in a web post, Robert H. Windschitl pointed out that the following is the case [12] (see also [13]).
Motivated by (9), Alzer [14] deduced the following double inequality:
with and being the best possible constants. Lu et al. [15] deduced the following extended formula to Windschitl’s formula:
where , , and . Chen [16] presented the following asymptotic expansion of the Gamma function related to Windschitl’s formula:
with a recurrence relation for determining coefficients . Motivated by the above results, Yang and Tian [17] provided a more accurate Windschitl-type approximation:
They developed Windschitl’s approximation formula by giving two asymptotic expansions [18]:
where and
where . Moreover, they [19] deduced the following family of high accurate approximation formulas for
Finally, they presented four new Windschitl-type approximation formulas [20]. Nemes [21] deduced that
which is much simpler than (9), and they have the same number of exact digits. Formulas (9) and (17) are stronger Ramanujan formulas. Starting from Nemes’s Formula (17), Mortici [22] constructed the continued fraction approximation:
where , , and . For more details about Gamma function applications, see [23,24] and the references therein.
2. Lemmas
In sequel, the following results are required in our conclusions.
Lemma 1
([25]). If we have the asymptotic expansion
then we obtain the following asymptotic expansion
where
Lemma 2
([25]). If we have the asymptotic expansion
then we obtain the following asymptotic expansion
where
Lemma 3
([26]). If is a null sequence, and such that
then we have
Lemma 4
([27]). Let the real-valued function defined for and . If , , then for ; if , , then for .
3. Main Results
To obtain the best possible constants and in the approximation formula
we define a sequence that satisfies
Then,
If , then sequence has a rate of worse than . So, we will consider . Moreover, to increase the rate of convergence, we use and then and . Now, by Lemma 3, we obtain the following result.
Lemma 5.
The sequence is as follows:
where
Theorem 1.
The Gamma function has the following asymptotic expansion:
where are given by
where denote Bernoulli numbers and
with
and the empty sum is understood as usual to be nil.
Proof.
From Stirling series (2) with the identity , , we have the following.
Moreover, we obtain
with
By Lemma 1, we obtain
with
Hence,
which gives us with the aid of such that
Equating coefficients of yields
□
Remark 1.
According to Theorem 1, we have the following explicit formula.
Using Lemma 2 and Theorem 1, we obtain the following result.
Theorem 2.
The Gamma function has the asymptotic expansion
where are given by
with coefficients being given by (23).
Remark 2.
According to Theorem 2, we have
which is simpler than Windschitl’s approximation (9) and has the same rate of convergence.
4. Numerical Comparisons among Some Approximation Formulas of
We have the following approximation formulas:
and
| [15] | |||
| [22] | |||
| [28] | |||
| [29] | |||
| [21] |
| [16]. |
Chen [16] showed by some numerical computations that approximation is stronger than the others. Moreover, Chen [30] showed by some numerical computations that the two approximations
and
are stronger than formula for . Table 1 shows that the approximation
is stronger than approximation .
Table 1.
Comparison among and .
Moreover, Table 2 shows that approximation
is stronger than approximation :
Table 2.
Comparison among and .
5. Some Bounds of Using Padé Approximants
Consider the following formal power series.
Then, the rational function
is called the Padé approximant of order of function [31,32,33], where
and coefficients are the solutions of the system
with for , and coefficients are given by the following.
For the formal power series , where are given by (23), we can conclude the following Padé approximations
and
Hence, we obtain the following double inequality.
Theorem 3.
The following double inequality holds for .
Proof.
Consider the function
and then
where
Using , we obtain
where
and
Now, is a decreasing function for with ; then, or for . However, ; hence, by using Lemma 4, we have for . Then, is a decreasing function for with and then for or
Now, consider the following function
and then
where
Using , we obtain
where
and
Now, is an increasing function for with ; then, or for . However, ; hence, using Lemma 4, we have for . Then, is an increasing function for with and then for or
□
6. Conclusions
The Padé approximant method and asymptotic expansions can be employed to present some new bounds of . We presented proofs to illustrate the novelty of our findings, which may be of interest to a significant portion of the readers. This method is a powerful tool for inferring inequalities for many other special functions.
Author Contributions
Writing to original draft, M.M. and H.A. All authors contributed equally to the writing of this paper. All authors have read and agreed to the published version of the manuscript.
Funding
The Deanship of Scientific Research (DSR) at King Abdulaziz University (KAU), Jeddah, Saudi Arabia has funded this Project under grant no (G: 716-130-1443).
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
Correction Statement
This article has been republished with a minor correction to the existing affiliation information. This change does not affect the scientific content of the article.
References
- Batir, N. Very accurate approximations for the factorial function. J. Math. Inequal. 2010, 4, 335–344. [Google Scholar] [CrossRef]
- Gosper, R.W. Decision procedure for indefinite hypergeometric summation. Proc. Natl. Acad. Sci. USA 1978, 75, 40–42. [Google Scholar] [CrossRef] [PubMed]
- Mortici, C. On Gospers formula for the Gamma function. J. Math. Inequal. 2011, 5, 611–614. [Google Scholar] [CrossRef]
- Abramowitz, M.; Stegun, I.A. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables; Applied Mathematical Series; Nation Bureau of Standards: Dover, DE, USA; New York, NY, USA, 1972; Volume 55. [Google Scholar]
- Burnside, W. A rapidly convergent series for logN! Messenger Math. 1917, 46, 157–159. [Google Scholar]
- Andrews, G.E.; Berndt, B.C. Ramanujan’s Lost Notebook: Part IV; Springer Science & Business Media: New York, NY, USA, 2013. [Google Scholar]
- Berndt, B.C.; Choi, Y.-S.; Kang, S.-Y. The problems submitted by Ramanujan. J. Indian Math. Soc. Contemp. Math. 1999, 236, 15–56. [Google Scholar]
- Karatsuba, E.A. On the asymptotic representation of the Euler Gamma function by Ramanujan. J. Comput. Appl. Math. 2001, 135, 225–240. [Google Scholar] [CrossRef]
- Mortici, C. On Ramanujan’s large argument formula for the Gamma function. Ramanujan J. 2011, 26, 185–192. [Google Scholar] [CrossRef]
- Ramanujan, S. The Lost Notebook and Other Unpublished Papers; Narosa Publishing House: New Delhi, India; Springer: Berlin/Heidelberg, Germany, 1988. [Google Scholar]
- Mortici, C. Improved asymptotic formulas for the Gamma function. Comput. Math. Appl. 2011, 61, 3364–3369. [Google Scholar] [CrossRef]
- Available online: http://www.rskey.org/gamma.htm (accessed on 20 April 2020).
- Smith, W.D. The Gamma Function Revisited. 2006. Available online: http://schule.bayernport.com/gamma/gamma05.pdf (accessed on 20 April 2020).
- Alzer, H. Sharp upper and lower bounds for the Gamma function. Proc. R. Soc. Edinb. 2009, 139A, 709–718. [Google Scholar] [CrossRef]
- Lu, D.; Song, L.; Ma, C. A generated approximation of the Gamma function related to Windschitl’s formula. J. Number Theory 2014, 140, 215–225. [Google Scholar] [CrossRef]
- Chen, C.-P. Asymptotic expansions of the Gamma function related to Windschitl’s formula. Appl. Math. Comput. 2014, 245, 174–180. [Google Scholar] [CrossRef]
- Yang, Z.-H.; Tian, J.-F. An accurate approximation formula for Gamma function. J. Inequal. Appl. 2018, 2018, 56. [Google Scholar] [CrossRef] [PubMed]
- Yang, Z.-H.; Tian, J.-F. Two asymptotic expansions for Gamma function developed by Windschitl’s formula. Open Math. 2018, 16, 1048–1060. [Google Scholar] [CrossRef]
- Yang, Z.-H.; Tian, J.-F. A family of Windschitl type approximations for Gamma function. J. Math. Inequal. 2018, 12, 889–899. [Google Scholar] [CrossRef]
- Yang, Z.-H.; Tian, J.-F. Windschitl type approximation formulas for the Gamma function. J. Inequal. Appl. 2018, 2018, 272. [Google Scholar] [CrossRef] [PubMed]
- Nemes, G. New asymptotic expansion for the Gamma function. Arch. Math. 2010, 95, 161–169. [Google Scholar] [CrossRef]
- Mortici, C. A continued fraction approximation of the Gamma function. J. Math. Anal. Appl. 2013, 402, 405–410. [Google Scholar] [CrossRef]
- Ahmad, S.; Ullah, A.; Akgül, A.; Jarad, F. A hybrid analytical technique for solving nonlinear fractional order PDEs of power law kernel: Application to KdV and Fornberg-Witham equations. AIMS Math. 2022, 7, 9389–9404. [Google Scholar] [CrossRef]
- Gulalai Ahmad, S.; Rihan, F.A.; Ullah, A.; Al-Mdallal, Q.M.; Akgül, A. Nonlinear analysis of a nonlinear modified KdV equation under Atangana Baleanu Caputo derivative. AIMS Math. 2022, 7, 7847–7865. [Google Scholar] [CrossRef]
- Chen, C.-P.; Elezović, N.; Vukšić, L. Asymptotic formulae associated with the Wallis power function and digamma function. J. Class. Anal. 2013, 2, 151–166. [Google Scholar] [CrossRef]
- Mortici, C. New approximations of the Gamma function in terms of the digamma function. Appl. Math. Lett. 2010, 23, 97–100. [Google Scholar] [CrossRef]
- Elbert, A.; Laforgia, A. On some properties of the Gamma function. Proc. Amer. Math. Soc. 2000, 128, 2667–2673. [Google Scholar] [CrossRef]
- Mortici, C. New improvements of the Stirling formula. Appl. Math. Comput. 2010, 217, 699–704. [Google Scholar] [CrossRef]
- Mortici, C. Ramanujan formula for the generalized Stirling approximation. Ramanujan J. 2010, 217, 2579–2585. [Google Scholar] [CrossRef]
- Chen, C.-P. Asymptotic Expansions of the Gamma Function Associated with the Windschitl and Smith Formulas. 2014. Available online: https://rgmia.org/papers/v17/v17a109.pdf (accessed on 18 April 2020).
- Baker, G.A., Jr.; Graves-Morris, P.R. Padé Approximants, 2nd ed.; Cambridge University Press: Cambridge, UK, 1996. [Google Scholar]
- Brezinski, C. Computational Aspects of Linear Control; Kluwer: Dordrecht, The Netherlands, 2002. [Google Scholar]
- Brezinski, C.; Redivo-Zaglia, M. New representations of Padé, Padé-type, and partial Padé approximants. J. Comput. Appl. Math. 2015, 284, 69–77. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).