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Article

Solving Second-Order Homogeneous Linear Differential Equations in Terms of the Tri-Confluent Heun’s Function

Mathematics Department, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Symmetry 2024, 16(6), 678; https://doi.org/10.3390/sym16060678
Submission received: 5 May 2024 / Revised: 26 May 2024 / Accepted: 27 May 2024 / Published: 31 May 2024
(This article belongs to the Section Mathematics)

Abstract

:
In this paper, we state an algorithm that checks whether a given second-order linear differential equation can be reduced to the tri-confluent Heun’s equation. The algorithm provides a method for finding solutions of the form exp ( r ( x ) d x ) · HeunT ( q , α , γ , δ , ϵ , f ( x ) ) , where the parameters α , β , λ C , the functions r , f C ( x ) , and f are not constant.

1. Introduction

The tri-confluent Heun’s function, HeunT ( q , α , γ , δ , ϵ , x ) , is a solution for the tri-confluent Heun’s differential equation [1]
y + ( γ + δ x + ϵ x 2 ) y + ( α x q ) y = 0 ,
where λ , α , β C . The equation corresponds to the following differential operator:
L H T = 2 + ( γ + δ x + ϵ x 2 ) + ( α x q ) ,
where = d d x . There are many applications for the Heun’s functions in different fields of science such as quantum mechanics, gravitational physics, astrophysics, nuclear physics, chemical dynamics, mathematical chemistry, mathematical physics, etc. [2,3,4].
Applying the change of variables transformation [5], which is the substitution
( x , ) f C H ( f , 1 f )
where f C ( x ) and f is not constant, on  L HT gives a second-order differential operator L ˜ C ( x ) [ ] . Note that L ˜ has a solution of the form HeunT ( q , α , γ , δ , ϵ , f ( x ) ) . Also, applying the exp-product transformation [5], which is
r E X r ,
where r C ( x ) , on L ˜ produces a second-order differential operator L C ( x ) [ ] . From the definition of the transformations, the operator L has a solution of the form
exp ( r ( x ) d x ) · HeunT ( q , α , γ , δ , ϵ , f ( x ) ) .
If L is obtained from L HT by ( 3 ) and ( 4 ) , we write L HT f C H L ˜ r E X L , and the operator L is denoted by L ˜ ( r ) .
Consider the second-order linear differential equations with solutions of the form    
exp ( r ( x ) d x ) · y ( f ( x ) ) ,
where r , f C ( x ) , and y is a special function (e.g., Bessel, Kummer, and the hypergeometric functions   2 F 1 ( α , β ; λ ; x ) ,   1 F 1 ( α ; λ ; x ) , and   0 F 1 ( λ ; x ) ) that satisfies a second-order linear differential equation (see [6]). These kinds of equations are studied by many authors (e.g., [7,8,9,10,11]). In the general case, where y is not a special function, Algorithm 17 in [12] reduces the second-order linear differential equations with solutions of the form y ( f ( x ) ) to the same order with solutions of the form y by detecting the change of variable transformation ( 3 ) . Our algorithm in [13] studies the second-order differential equations with solutions of the form
exp ( r ( x ) d x ) · HeunC ( α , β , γ , δ , η , f ( x ) ) ,
where HeunC is the confluent Heun’s function.
Let L = 2 + a ( x ) + b ( x ) be an irreducible second-order differential operator with coefficients in C ( x ) . The goal of this paper is to reduce L “if and only if it is possible” to L HT , ( 2 ) , by detecting the parameters of the transformations ( 3 ) and ( 4 ) . The main contribution of this paper is an algorithm that reduces L to L HT if L is obtained from L HT by ( 3 ) and ( 4 ) . The algorithm will extend the ability of the existing software that solves the tri-confluent Heun’s equations to solve second-order differential equations in terms of the tri-confluent Heun’s function.
Example 1.
Given
L = 2 ( 9 x 8 + x 6 4 x 5 16 x 4 10 x 3 + x 2 + 9 ) 3 x 4 ( x 2 + 1 ) ( 180 x 7 9 x 6 + 190 x 5 17 x 4 160 x 3 77 x 2 170 x 9 ) 45 x 4 ( x 2 + 1 ) .
The algorithm in this paper reduces L to  L HT = 2 ( 3 x 2 + 1 3 ) 2 x + 1 5  by computing the parameter of the transformations
f ( x ) = x 2 1 x and r ( x ) = 2 3 x .
By use of the command dsolve in Maple software 2021, the functions
y 1 ( x ) = HeunT ( 1 5 , 1 , 1 3 , x ) and y 2 ( x ) = e x 3 + x 3 HeunT ( 1 5 , 1 , 1 3 , x )
are solutions of L HT . Therefore, the functions
Y i ( x ) = exp ( 2 3 x d x ) · y i ( x 2 1 x ) ,
where i = 1 , 2 , are solutions of L.
The importance of this paper lies in the application of the exp-product and the change of variable transformations or choosing certain values of the parameters of a well-known differential equation that could lead to another well-known differential equation. For example, the differential equation y + 2 ϵ 2 ( a x 2 + b x 4 ) y = 0 is obtained by substituting the quartic potential v ( x ) = a x 2 + b x 4 , where a R and b R + , into y + 2 ( ϵ v ( x ) ) y = 0 , which is the one-dimensional Schrödinger equation. The solutions of the equation can be expressed in terms of the tri-confluent Heun’s functions [14]. Also, some forms of the one-dimensional Schrödinger equation can be solved by transforming them to the confluent and bi-confluent Heun equations [15,16,17]. A class of the quantum two-state problem models can be solved in terms of the tri-confluent Heun’s functions, and the class is symmetric for some values of the parameters of the class and the change of variable transformation (some second-order linear differential equations have Lie point symmetries which can be interpreted as the change of variables transformations of the form x a x + b , where a and b are constants) [4,18].

2. Preliminaries

A differential operator of order n with coefficients in C ( x ) takes the form i = 0 n a i ( x ) i , where a i ( x ) C ( x ) and = d d x . It corresponds to the homogeneous linear differential equation
a n ( x ) y ( n ) + a n 1 ( x ) y ( n 1 ) + + a 0 ( x ) y = 0 .
A function y ( x ) is a solution of L C ( x ) [ ] if L ( y ) = 0 .
Let L = 2 + A ( x ) + B ( x ) , where A ( x ) and B ( x ) are in C ( x ) . A point c C is a singular point of L if c is a pole of A ( x ) or B ( x ) . If c is a pole of ( x c ) A ( x ) or ( x c ) 2 B ( x ) , it is an irregular singular point of L ; otherwise, it is a regular singular point. The point x = is a singular point of L if 0 is a singular point of L 1 x , which is obtained from L by applying ( 3 ) on L and f ( x ) = 1 x . The local parameter of c C is t c = x c if c and t c = 1 x if c = .
The operator L has two generalized series solutions at c C { } of the form
Y 1 = exp ( e 1 t c d t c ) U 1 , Y 2 = exp ( e 2 t c d t c ) U 2 ,
where e j C [ t c 1 m j ] and U j = i = 0 Z j , i t c i m j such that Z j , i C [ log ( t c ) ] and Z j , 0 0 for j = 1 , 2 , as shown in Definition 1 in [10]. In ( 8 ) ,   e 1 and e 2 are called the generalized exponents of L at c , and Y 1 and Y 2 are called the formal solutions of L at c . If c is not a singular point of L, then the generalized exponents of L at c are e 1 = 0 and e 2 = 1 [19]. At the regular singularities of L , the generalized exponents are constants [20]. If c is an irregular singular point of L , then at least one of the generalized exponents of L at c is non-constant [11].

3. The Effects of the Transformations on the Singularities and the Generalized Exponents of the Tri-Confluent Heun’s Operator

Let L be a second-order differential operator with coefficients in C ( x ) such that
L HT f C H L ˜ r E X L .
where r , f C ( x ) , and f is not constant. In  ( 9 ) , the operator L ˜ is called a proper pullback of L HT by f , and the operator L is called a weak pullback of L HT by f (Definition 4.1 in [9]). If L = 2 + A ( x ) + B ( x ) and L ˜ = 2 + c 1 ( x ) + c 0 ( x ) , we can rewrite ( 9 ) as follows:
L HT f C H L ˜ c 1 ( x ) 2 E X N F ( L ) A ( x ) 2 E X L ,
where
N F ( L ) = L ( A ( x ) 2 ) = 2 + B ( x ) ( A ( x ) ) 2 4 ( A ( x ) ) 2 ,
and L = L ˜ ( r ( x ) ) , where r ( x ) = c 1 ( x ) A ( x ) 2 . The operator N F ( L ) is called the normal form of L , and it is used to remove the singularities of L that are not singularities of L ˜ .
Let L C ( x ) [ ] be as in ( 9 ) . To reduce L to L HT , we need to compute f and c 1 ( x ) in ( 10 ) . Algorithm 17 in [12] reduces L ˜ to L HT by computing the pullback function f C ( x ) if C C ( f ( x ) ) C ( x ) . Therefore, we need to compute c 1 ( x ) in ( 10 ) to have a complete method for reducing weak pullback operators of L HT . For this, we study the effects of the transformations on the singularities and the generalized exponents of L HT .
The operator L HT has only one singular point, which is x = , and the singular point is irregular. The generalized exponents (we use the command gen_exp in Maple software to compute them) of L HT at are e 1 = α ϵ and e 2 = ϵ t 3 + δ t 2 + γ t 1 + 2 α ϵ , and the generalized exponents of L HT at any other point in C are 0 and 1 .
Lemma 1.
Let  L ˜  be a proper pullback of  L HT by f C ( x ) and f be not constant.
  • If c is a root of f with multiplicity  m N ,  then c is a regular singular point of L, and the generalized exponents of   L ˜  at c are e 1 = 0  and  e 2 = m ;
  • If c is a pole of f of order m N ,  then c is an irregular singular point of  L ˜ , and the generalized exponents of L at c are  e 1 = m ( α ϵ )  and  e 2 = i = 3 m 1 a i t c i + m ( 2 α ϵ ) , where   a 3 m , , a 1 C .
The proof is similar to the proof of Theorem 2 [5].
Let L ˜ = 2 + c 1 ( x ) + c 0 ( x ) be as in ( 9 ) , and let { e 1 , e 2 } be the set of the generalized exponents of L ˜ at c . If e is the generalized exponent of r at c , then { e 1 + e , e 2 + e } is the set of the generalized exponents of L ˜ ( r ) at c (Lemma 4 in [5]). If { e 1 = i = j 1 0 a 1 , i t c i , e 2 = i = j 2 0 a 2 , i t c i } where j 1 , j 2 Z { 0 } is the set of the generalized exponents of L ˜ at c , then the Laurent series of c 1 ( x ) at c is e 1 e 2 j 1 j 2 + 1 t c + i = 0 a i ( t c ) i (see Section 3.5 in [21] and Lemma 3.4 in [22]). Therefore, the set of the generalized exponents of L ˜ ( c 1 ( x ) 2 ) at c is
{ e 1 e 2 j 1 j 2 + 1 2 , e 1 + e 2 j 1 j 2 + 1 2 }
because the generalized exponent of c 1 ( x ) 2 at c is e 1 e 2 j 1 j 2 + 1 2 .
Lemma 2.
Let L be a weak pullback of  L HT  by  f C ( x ) C .  Then, the set of the generalized exponents of   N F ( L )  at a singular point  c C { }  is of the form  { m + 1 2 , m + 1 2 }  or  { i = 3 m 1 a i t c i 2 m α ϵ + 5 m + 1 2 , i = 3 m 1 a i t c i 2 m α ϵ + m + 1 2 } .
Proof. 
Let L ˜ = 2 + c 1 ( x ) + c 0 ( x ) C ( x ) [ ] be the proper pullback of L HT by f . Then, N F ( L ) = N F ( L ˜ ) = L ˜ ( c 1 ( x ) 2 ) . Since the set of the generalized exponents of L ˜ at a singular point c is of the form { 0 , m } or { m ( α ϵ ) , i = 3 m 1 a i t c i + m ( 2 α ϵ ) } (Lemma 1 ) , the generalized exponents of N F ( L ) at c are of the form { m + 1 2 , m + 1 2 } or { i = 3 m 1 a i t c i 2 m α ϵ + 5 m + 1 2 , i = 3 m 1 a i t c i 2 m α ϵ + m + 1 2 } , and it is computed by substituting the generalized exponents of L ˜ at c in ( 11 ) .    □

4. Reducing a Weak Pullback of the Tri-Confluent Heun’s Operator

Let L be a weak pullback of L HT by f such that
L HT f C H L ˜ r E X L .
The generalized exponents of N F ( L ) at its singularities can be used to compute the parameter of the exp-product transformation that transfers N F ( L ) to L ˜ (Lemmas 1 and 2). If c is a regular singular point of N F ( L ) and { m + 1 2 , m + 1 2 } is the set of the generalized exponents of N F ( L ) at c , the generalized exponents of the operators N F ( L ) ( + m + 1 2 t c ) and L ˜ at c are 0 and m . Also, if c is an irregular singular point of N F ( L ) and { i = 3 m 1 a i t c i 2 α ϵ + 5 m + 1 2 , i = 3 m 1 a i t c i 2 m α ϵ + m + 1 2 } is the set of the generalized exponents of N F ( L ) at c , and the operators N F ( L ) ( + i = 3 m 1 a i t c i 2 + m + 1 2 t c ) and L ˜ have the same set of generalized exponents at c .
Let S reg = { c 1 , c 2 , , c n } and S irr = { v 1 , v 2 , , v k } be the sets of the regular and irregular singularities of N F ( L ) , respectively. If c S reg and { m + 1 2 , m + 1 2 } is the set of the generalized exponents of N F ( L ) at c , we take r c ( x ) = m + 1 2 t c if c and r c ( x ) = 0 if c = (if the constant parts of the generalized exponents of N F ( L ) ( r ) are equal to the constant parts of the generalized exponents L ˜ at each finite singular point, the constant parts of the generalized exponents of the operators at are equal (Fuchs’s relation, shown in [21,23])). If v S irr and { i = j 1 a i t v i + a 0 , 1 , i = j 1 a i t v i + a 0 , 2 } are the set of the generalized exponents of N F ( L ) at v , we take
r v , 1 ( x ) = i = j 1 a i t v i + j 3 + 1 2 t v and r v , 2 ( x ) = i = j 1 a i t v i + j 3 + 1 2 t v
if v , and
r v , 1 ( x ) = i = j 1 a i t v i t v and r v , 2 ( x ) = i = j 1 a i t v i t v
if v = . The parameter of the exp-product transformation that reduces N F ( L ) to L ˜ is a function of the form
Y z 1 , , z k = ( r c 1 ( x ) + + r c n ( x ) + r v 1 , z 1 ( x ) + + r v k , z k ( x ) ) ,
for z 1 , , z k { 1 , 2 } . Therefore, the operator L ˜ in ( 12 ) is equal to one of the operators
L z 1 , , z k = N F ( L ) ( Y z 1 , , z k ) ,
for z 1 , , z k { 1 , 2 } .
Notation 1.
Let L be in  C ( x ) [ ] , where  C C  is a field of characteristic  0 . Let P ( x ) C [ x ] be the denominator of L such that P ( x ) = ( P 1 ( x ) ) s 1 ( P j ( x ) ) s j and P i ( x ) is an irreducible in C [ x ] . If q 1 , , q s 1 and q s are the roots of P i ( x ) , the sets of the generalized exponents of L at q 1 , , q s 1 and q s are the same. Also, the sets of the generalized exponents of L ( Tr ( e x q j ) ) at q 1 , , q s 1 , and q s are the same ( Tr ( e x q j ) is the trace of e x q j over the field extension C ( x , q j ) / C ( x ) , and it is the sum of e x q j and its conjugates. Note that Tr ( e x q j ) C ( x ) ) .

5. The Algorithm

Given a monic second-order differential operator, L C ( x ) [ ] , where C C . In this section, we state an algorithm that reduces L to L HT if L is a weak pullback of L HT by f and C C ( f ( x ) ) C ( x ) .
Example 2.
Given
L = 2 + ( 8 x 7 19 x 6 4 x 5 + 10 x 4 36 x 3 + 78 x 2 72 x + 24 ) 2 x 7 ( x 2 ) + ( 8 x 7 22 x 6 6 x 5 3 x 4 + 29 x 3 58 x 2 + 76 x 40 ) 4 x 8 ( x 2 ) .
The commands dsolve and Heunsols in Maple software 2021 do not find solutions for L. However, Algorithm 1 finds that L is a weak pullback of L ¯ = 2 + 4 x 3 + x 2 + 6 2 x 4 + ( 2 x 11 ) 4 x 5 by f ( x ) = x 2 x 1 and finds r ( x ) = 1 x such that
L ¯ x 2 x 1 C H L ˜ 1 x E X L ,
so the solutions of L can be computed by using the solutions of L ¯ and the parameters of the transformations. Since the functions
y 1 ( x ) = HeunT ( 1 2 , 1 4 , 1 2 , 1 x ) and y 2 ( x ) = exp ( x 2 + 2 2 x 3 ) HeunT ( 1 2 , 1 4 , 1 2 , 1 x )
are solutions of L ¯ , the functions
Y 1 = 1 x y 1 ( x 2 x 1 ) and Y 2 = 1 x y 2 ( x 2 x 1 )
are solutions of L.
Algorithm 1 Reduce weak proper pullback of tri-confluent Heun’s operator to LHT and find the pullback function f.
  • Input:  L = 2 + A ( x ) + B ( x ) C ( x ) [ ] where C C is a field of characteristic 0 .
  • Output: A tri-confluent Heun’s differential operator, the pullback function f , and the parameter of the exp-product transformation r or “failed” (failed means L is not a weak pullback of L HT by non-trivial pullback function f (f is not a Möbius transformation)).
1.
Compute the normal form of L , which is N F ( L ) = L ( A ( x ) 2 ) .
2.
Let P ( x ) C [ x ] be the denominator of N F ( L ) , and factor P ( x ) over C .
3.
If P ( x ) = ( P 1 ( x ) ) s 1 ( P j ( x ) ) s j , where P i ( x ) is an irreducible in C [ x ] , take q i to be a root of P i ( x ) .
4.
For each q i , compute the generalized exponent, e i , 1 and e i , 2 , of N F ( L ) at q i .
  • Case 1 : If e i , 1 and e i , 2 are in Q and e i , 1 e i , 2 Z , take r i ( x ) = Tr ( e i , 1 t q i ) if e i , 1 e i , 2 . If e i , 1 and e i , 2 are constants but not in Q or e i , 1 e i , 2 Z , return “failed” (from Lemmas 1 and 2, it is clear that L is not obtained from L HT by the transformations ( 3 ) and ( 4 ) ).
  • Case 2 : If e i , 1 = k = j 1 a k t q i k + a 0 , 1 and e i , 2 = k = j 1 ( a k ) t q i k + a 0 , 2 , then take v i , 1 ( x ) = k = j 1 a k t q i k + j 3 + 1 2 t q i and v i , 2 ( x ) = k = j 1 a k t q i k + j 3 + 1 2 t q i otherwise return “failed”.
5.
Put r ( x ) = 0 if S irr . However, if  S irr and
e i , 1 = k = j 1 a k t k + a 0 , 1 and e i , 2 = k = j 1 ( a k ) t k + a 0 , 2 ,
take v , 1 ( x ) = i = j 1 a i t i t and v v , 2 ( x ) = i = j 1 a i t i t otherwise return “failed".
6.
From Case 1 of Step 4 , if q s 1 , , q s k are the regular singularities of N F ( L ) , take R = r s 1 ( x ) + r s 2 ( x ) + + r s k ( x ) where s 1 , , s k { 1 , , j } .
7.
From Case 2 in Step 4, if  q z 1 , , q z t are the irregular singularities of N F ( L ) , let
H = { { v q z 1 , 1 ( x ) , v q z 1 , 2 ( x ) } , , { v q z t , 1 ( x ) , v q z t , t ( x ) } , { v , 1 ( x ) , v , 2 ( x ) } } ,
and G is the set of the combinations of choosing one element from each set in H .
8.
For each G i = { v q z 1 , w 1 ( x ) , v q z 2 , w 2 ( x ) , , v q z t , w t ( x ) , v , w ( x ) } G , where w 1 , w 2 , , w { 1 , 2 } ,
(a)
Take Y = R + v q z 1 , w 1 ( x ) + v q z 2 , w 2 ( x ) + + v q z t , w t ( x ) + v , w ( x ) , where R is as in Step 6 , and find L ˜ = N F ( L ) ( + Y ) .
(b)
Apply Algorithm 17 in [12] on L ˜ . If it reduces L ˜ to L ¯ and finds non-trivial pullback function f ( f is not a Möbius transformation ) , return L ¯ , f and r ( x ) = Y A ( x ) 2 , where L = L ˜ ( r ( x ) ) .
(c)
If Algorithm 17 in [12] does not reduce L ˜ , go to the next element of G .
9.
Return “failed” if the previous step does not reduce L .

6. Conclusions

We have provided an algorithm that reduces second-order differential operators, whose solutions are in the form
exp ( r ( x ) d x ) · HeunT ( q , α , γ , δ , ϵ , f ( x ) )
where r , f C ( x ) and C C ( f ( x ) ) C ( x ) , to the tri-confluent Heun’s operator, ( 2 ) . The algorithm detects the parameters of the transformations ( 3 ) and ( 4 ) by using the generalized exponents of the given differential operators. Related work for the other forms of Heun’s equations is in progress.

Funding

This work is supported by Researchers Supporting Project number (RSPD2024R839), King Saud University, Riyadh, Saudi Arabia.

Data Availability Statement

Data are contained within the article.

Acknowledgments

This work is supported by Researchers Supporting Project number (RSPD2024R839), King Saud University, Riyadh, Saudi Arabia.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Ronveaux, A. Heun’s Differential Equations; Oxford University Press: Oxford, UK, 1995. [Google Scholar]
  2. Fiziev, P. The Heun functions as a modern powerful tool for research in different scientific domains. arXiv 2015, arXiv:1512.04025. [Google Scholar]
  3. Hortaçsu, M. Heun functions and some of their applications in physics. Adv. High Energy Phys. 2018, 2018, 8621573. [Google Scholar] [CrossRef]
  4. Shahverdyan, T.; Ishkhanyan, T.; Grigoryan, A.; Ishkhanyan, A. Analytic solutions of the quantum two-state problem in terms of the double, bi-and triconfluent Heun functions. J. Contemp. Phys. Armen. Acad. Sci. 2015, 50, 211–226. [Google Scholar] [CrossRef]
  5. Debeerst, R.; van Hoeij, M.; Koepf, W. Solving differential equations in terms of Bessel functions. In Proceedings of the Twenty-First International Symposium on Symbolic and Algebraic Computation, Linz/Hagenberg, Austria, 20–23 July 2008; ACM: New York, NY, USA, 2008; pp. 39–46. [Google Scholar]
  6. Kristensson, G. Second Order Differential Equations: Special Functions and Their Classification; Springer Science & Business Media: Berlin, Germany, 2010. [Google Scholar]
  7. Fang, T. Solving Linear Differential Equations in Terms of Hypergeometric Functions by 2-Descent; The Florida State University: Tallahassee, FL, USA, 2012. [Google Scholar]
  8. Kunwar, V. Hypergeometric Solutions of Linear Differential Equations with Rational Function Coefficients; Florida State University: Tallahassee, FL, USA, 2014. [Google Scholar]
  9. Van Hoeij, M.; Weil, J. Solving second order linear differential equations with Klein’s theorem. In Proceedings of the 2005 International Symposium on Symbolic and Algebraic Computation, Beijing China, 24–27 July 2005; ACM: New York, NY, USA, 2005; pp. 340–347. [Google Scholar]
  10. Van Hoeij, M.; Yuan, Q. Finding all Bessel type solutions for linear differential equations with rational function coefficients. In Proceedings of the 2010 International Symposium on Symbolic and Algebraic Computation, Munich, Germany, 25–28 July 2010; ACM: New York, NY, USA, 2010; pp. 37–44. [Google Scholar]
  11. Debeerst, R. Solving Differential Equations in Terms of Bessel Functions. Master’s Thesis, Universität Kassel, Kassel, Germany, 2007. [Google Scholar]
  12. Aldossari, S. Computing pullback function of second order differential operators by using their semi-invariants. J. Symb. Comput. 2023, 119, 38–49. [Google Scholar] [CrossRef]
  13. Aldossari, S. Solving second-order differential equations in terms of confluent Heun’s functions. Math. Methods Appl. Sci. 2024, 47, 7780–7792. [Google Scholar] [CrossRef]
  14. Dong, Q.; Sun, G.; Aoki, M.; Chen, C.; Dong, S. Exact solutions of a quartic potential. Mod. Phys. Lett. A 2019, 34, 1950208. [Google Scholar] [CrossRef]
  15. Marcilhacy, G.; Pons, R. The Schrödinger equation for the interaction potential x2+λx2/(1+gx2) and the first Heun confluent equation. J. Phys. A Math. Gen. 1985, 18, 2441. [Google Scholar] [CrossRef]
  16. Ovsiyuk, E.; Amirfachrian, M.; Veko, O. On Schrödinger equation with potential V(r)=−αr−1+βr+kr2 and the bi-confluent Heun functions theory. Nonlinear Phenom. Complex Syst. 2012, 15, 163. [Google Scholar]
  17. Lévai, G. Potentials from the polynomial solutions of the confluent Heun equation. Symmetry 2023, 15, 461. [Google Scholar] [CrossRef]
  18. Hydon, P. Discrete point symmetries of ordinary differential equations. Proc. R. Soc. Lond. Ser. A Math. Phys. Eng. Sci. 1998, 454, 1961–1972. [Google Scholar] [CrossRef]
  19. Van Hoeij, M. Factorization of Linear Differential Operators. Ph.D. Thesis, Universiteit Nijmegen, Nijmegen, The Netherlands, 1996. [Google Scholar]
  20. Van Hoeij, M. Formal solutions and factorization of differential operators with power series coefficients. J. Symb. Comput. 1997, 24, 1–30. [Google Scholar] [CrossRef]
  21. Aldossari, S. Algorithms for Simplifying Differential Equations. Ph.D. Thesis, Florida State University, Tallahassee, FL, USA, 2020. [Google Scholar]
  22. Van Hoeij, M. Factorization of differential operators with rational functions coefficients. J. Symb. Comput. 1997, 24, 537–561. [Google Scholar] [CrossRef]
  23. Corel, E. On Fuchs’ relation for linear differential systems. Compos. Math. 2004, 140, 1367–1398. [Google Scholar] [CrossRef]
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Aldossari, S. Solving Second-Order Homogeneous Linear Differential Equations in Terms of the Tri-Confluent Heun’s Function. Symmetry 2024, 16, 678. https://doi.org/10.3390/sym16060678

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Aldossari S. Solving Second-Order Homogeneous Linear Differential Equations in Terms of the Tri-Confluent Heun’s Function. Symmetry. 2024; 16(6):678. https://doi.org/10.3390/sym16060678

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Aldossari, Shayea. 2024. "Solving Second-Order Homogeneous Linear Differential Equations in Terms of the Tri-Confluent Heun’s Function" Symmetry 16, no. 6: 678. https://doi.org/10.3390/sym16060678

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