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This package is a careful implementation of the Gosper and Zeilberger algorithms for indefinite and definite summation of hypergeometric terms, respectively. Extensions of these algorithms are also included that are valid for ratios of products of powers, factorials, \(\Gamma \) function terms, binomial coefficients, and shifted factorials that are rational-linear in their arguments.
Authors: Gregor Stölting and Wolfram Koepf.
\( \newcommand {\funkdef }[3]{\left \{\begin {array}{cc} #1 & \textrm {if } #2 \\ #3 & \textrm {otherwise} \end {array}\right .} \)This package is a careful implementation of the Gosper51 and Zeilberger algorithms for indefinite, and definite summation of hypergeometric terms, respectively. Further, extensions of these algorithms given by the first author are covered. An expression \(a_k\) is called a hypergeometric term (or closed form), if \(a_{k}/a_{k-1}\) is a rational function with respect to \(k\). Typical hypergeometric terms are ratios of products of powers, factorials, \(\Gamma \) function terms, binomial coefficients, and shifted factorials (Pochhammer symbols) that are integer-linear in their arguments.
The extensions of Gosper’s and Zeilberger’s algorithm mentioned in particular are valid for ratios of products of powers, factorials, \(\Gamma \) function terms, binomial coefficients, and shifted factorials that are rational-linear in their arguments.
The Gosper algorithm [Gos78] is a decision procedure, that decides by algebraic calculations whether or not a given hypergeometric term \(a_k\) has a hypergeometric term antidifference \(g_k\), i.e. \(g_{k}-g_{k-1}=a_k\) with rational \(g_k/g_{k-1}\), and returns \(g_k\) if the procedure is successful, in which case we call \(a_k\) Gosper-summable. Otherwise no hypergeometric term antidifference exists. Therefore if the Gosper algorithm does not return a closed form solution, it has proved that no such solution exists, an information that may be quite useful and important. The Gosper algorithm is the discrete analogue of the Risch algorithm for integration in terms of elementary functions.
Any antidifference is uniquely determined up to a constant, and is denoted by \[ g_k=\sum \nolimits _k a_k \;. \] Finding \(g_k\) given \(a_k\) is called indefinite summation. The antidifference operator \(\Sigma \) is the inverse of the downward difference operator \(\nabla a_k=a_{k}-a_{k-1}\). There is an analogous summation theory corresponding to the upward difference operator \(\Delta a_k=a_{k+1}-a_k\).
In case, an antidifference \(g_k\) of \(a_k\) is known, any sum \[ \sum _{k=m}^{n} a_k=g_{n}-g_{m-1} \] can be easily calculated by an evaluation of \(g\) at the boundary points like in the integration case. Note, however, that the sum \begin {equation} \sum _{k=0}^n \binom {n}{k} \label {eq:nchoosek} \end {equation} e. g. is not of this type since the summand \(\binom {n}{k}\) depends on the upper boundary point \(n\) explicitly. This is an example of a definite sum that we consider in the next section.
Our package supports the input of powers (a^k), factorials (factorial(k)), \(\Gamma \) function terms (gamma(a)), binomial coefficients (Binomial(n,k)), shifted factorials (Pochhammer(a,k)\(=a(a+1)\cdots (a+k-1)=\Gamma (a+k)/\Gamma (a)\)), and partially products (prod(f,k,k1,k2)). It takes care of the necessary simplifications, and therefore provides you with the solution of the decision problem as long as the memory or time requirements are not too high for the computer used.
The (fast) Zeilberger algorithm [Zei90]–[Zei91] deals with the definite summation of hypergeometric terms. Zeilberger’s paradigm is to find (and return) a linear homogeneous recurrence equation with polynomial coefficients (called holonomic equation) for an infinite sum \[ s(n)=\sum _{k=-\infty }^{\infty } f(n,k) \;, \] the summation to be understood over all integers \(k\), if \(f(n,k)\) is a hypergeometric term with respect to both \(k\) and \(n\). The existence of a holonomic recurrence equation for \(s(n)\) is then generally guaranteed.
If one is lucky, and the resulting recurrence equation is of first order \[ p(n)\,s(n-1)+q(n)\,s(n)=0 \quad \quad (p,q\;\mbox {polynomials}) \;, \] \(s(n)\) turns out to be a hypergeometric term, and a closed form solution can be easily established using a suitable initial value, and is represented by a ratio of Pochhammer or \(\Gamma \) function terms if the polynomials \(p\), and \(q\) can be factored.
Zeilberger’s algorithm does not guarantee to find the holonomic equation of lowest order, but often it does.
If the resulting recurrence equation has order larger than one, this information can be used for identification purposes: Any other expression satisfying the same recurrence equation, and the same initial values, represents the same function.
Note that a definite sum \(\sum \limits _{k=m_1}^{m_2} f(n,k)\) is an infinite sum if \(f(n,k)=0\) for \(k<m_1\) and \(k>m_2\). This is often the case, an example of which is the sum (\ref {eq:nchoosek}) considered above, for which the hypergeometric recurrence equation \(2 s(n-1) - s(n) = 0\) is generated by Zeilberger’s algorithm, leading to the closed form solution \(s(n)=2^n\).
Definite summation is trivial if the corresponding indefinite sum is Gosper-summable analogously to the fact that definite integration is trivial as soon as an elementary antiderivative is known. If this is not the case, the situation is much more difficult, and it is therefore quite remarkable and non-obvious that Zeilberger’s method is just a clever application of Gosper’s algorithm.
Our implementation is mainly based on [Koo93] and [Koe94b]. More examples can be found in [PS95], [Str93], [Wil90], and [Wil93] many of which are contained in the test file zeilberg.tst.
The gosper operator is an implementation of the Gosper algorithm.
gosper(a,k) determines a closed form antidifference. If it does not return a closed form solution, then a closed form solution does not exist.
gosper(a,k,m,n) determines \[ \sum _{k=m}^n a_k \] using Gosper’s algorithm. This is only successful if Gosper’s algorithm applies.
Example:
2: gosper((-1)^(k+1)*(4*k+1)*factorial(2*k)/ (factorial(k)*4^k*(2*k-1)*factorial(k+1)),k); k - ( - 1) *factorial(2*k) ------------------------------------ 2*k 2 *factorial(k + 1)*factorial(k)
This solves a problem given in SIAM Review ([OK94], Problem 94–2) where it was asked to determine the infinite sum \[ S=\lim _{n\rightarrow \infty } S_n \;, \quad \quad \quad S_n=\sum _{k=1}^n \frac {(-1)^{k+1}(4k+1)(2k-1)!!}{2^k(2k-1)(k+1)!} \;, \] (\((2k-1)!!=1\cdot 3 \cdots (2k-1)=\frac {(2k)!}{2^k\,k!}\)). The above calculation shows that the summand is Gosper-summable, and the limit \(S=1\) is easily established using Stirling’s formula.
The implementation solves further deep and difficult problems some examples of which are:
3: gosper(sub(n=n+1,binomial(n,k)^2/binomial(2*n,n))- binomial(n,k)^2/binomial(2*n,n),k); 2 ((binomial(n + 1,k) *binomial(2*n,n) 2 - binomial(2*(n + 1),n + 1)*binomial(n,k) ) 2 *(2*k - 3*n - 1)*(k - n - 1) )/(( 2*(2*(n + 1) - k)*(2*n + 1)*k 2 - (3*n + 1)*(n + 1) ) *binomial(2*(n + 1),n + 1)*binomial(2*n,n)) 4: gosper(binomial(k,n),k); (k + 1)*binomial(k,n) ----------------------- n + 1 5: gosper((-25+15*k+18*k^2-2*k^3-k^4)/ (-23+479*k+613*k^2+137*k^3+53*k^4+5*k^5+k^6),k); 2 - (2*k - 15*k + 8)*k ---------------------------- 3 2 23*(k + 4*k + 27*k + 23)
The Gosper algorithm is not capable to give antidifferences depending on the harmonic numbers \[ H_k:=\sum _{j=1}^k\frac {1}{j} \;, \] e. g. \(\sum _k H_k=(k+1)(H_{k+1}-1)\), but, is able to give a proof, instead, for the fact that \(H_k\) does not possess a closed form evaluation:
6: gosper(1/k,k); ***** Gosper algorithm: no closed form solution exists
The following code gives the solution to a summation problem proposed in Gosper’s original paper [Gos78]. Let \[ f_k=\prod _{j=1}^k (a+b\,j+c\,j^2) \quad \quad \mbox {and}\quad \quad g_k=\prod _{j=1}^k (e+b\,j+c\,j^2) \;. \] Then a closed form solution for \[ \sum \nolimits _k\frac {f_{k-1}}{g_{k}} \] is found by the definitions
7: operator ff,gg$
8: let {ff(~k+~m) => ff(k+m-1)*(c*(k+m)^2+b*(k+m)+a)
when (fixp(m) and m>0),
ff(~k+~m) => ff(k+m+1)/(c*(k+m+1)^2+b*(k+m+1)+a)
when (fixp(m) and m<0)}$
9: let {gg(~k+~m) => gg(k+m-1)*(c*(k+m)^2+b*(k+m)+e)
when (fixp(m) and m>0),
gg(~k+~m) => gg(k+m+1)/(c*(k+m+1)^2+b*(k+m+1)+e)
when (fixp(m) and m<0)}$
and the calculation
10: gosper(ff(k-1)/gg(k),k); ff(k) --------------- (a - e)*gg(k) 11: clear ff,gg$
Similarly closed form solutions of \(\sum \nolimits _k\frac {f_{k-m}}{g_{k}}\) for positive integers \(m\) can be obtained, as well as of \(\sum _k\frac {f_{k-1}}{g_{k}}\) for \[ f_k=\prod _{j=1}^k (a+b\,j+c\,j^2+d\,j^3) \quad \quad \mbox {and}\quad \quad g_k=\prod _{j=1}^k (e+b\,j+c\,j^2+d\,j^3) \] and for analogous expressions of higher degree polynomials.
The extended_gosper operator is an implementation of an extended version of Gosper’s algorithm given by Koepf [Koe94b].
extended_gosper(a,k) determines an antidifference \(g_k\) of \(a_k\) whenever there is a number \(m\) such that \(h_{k}-h_{k-m}=a_k\), and \(h_k\) is an \(m\)-fold hypergeometric term, i.e. \[ h_{k}/h_{k-m}\quad \mbox {is a rational function with respect to $k$.} \] If it does not return a solution, then such a solution does not exist.
extended_gosper(a,k,m) determines an \(m\)-fold antidifference \(h_k\) of \(a_k\), i.e. \(h_{k}-h_{k-m}=a_k\), if it is an \(m\)-fold hypergeometric term.
Examples:
12: extended_gosper(binomial(k/2,n),k); k k - 1 (k + 2)*binomial(---,n) + (k + 1)*binomial(-------,n) 2 2 ------------------------------------------------------- 2*(n + 1) 13: extended_gosper(k*factorial(k/7),k,7); k (k + 7)*factorial(---) 7
The sumrecursion operator is an implementation of the (fast) Zeilberger algorithm.
sumrecursion(f,k,n) determines a holonomic recurrence equation for \[ \texttt {summ(n)} =\sum \limits _{k=-\infty }^\infty f(n,k) \] with respect to \(n\), applying extended_sumrecursion if necessary, see § 20.65.7. The resulting expression equals zero.
sumrecursion(f,k,n,j) searches for a holonomic recurrence equation of order \(j\). This operator does not use extended_sumrecursion automatically. Note that if \(j\) is too large, the recurrence equation may not be unique, and only one particular solution is returned.
A simple example deals with Equation (\ref {eq:nchoosek})52
14: sumrecursion(binomial(n,k),k,n); 2*summ(n - 1) - summ(n)
The whole hypergeometric database of the Vandermonde, Gauß, Kummer, Saalschütz, Dixon, Clausen and Dougall identities (see [Wil93]), and many more identities (see e. g. [Koe94b]), can be obtained using sumrecursion. As examples, we consider the difficult cases of Clausen and Dougall:
15: summand:=factorial(a+k-1)*factorial(b+k-1)/ (factorial(k)*factorial(-1/2+a+b+k)) *factorial(a+n-k-1)*factorial(b+n-k-1)/ (factorial(n-k)*factorial(-1/2+a+b+n-k))$ 16: sumrecursion(summand,k,n); (2*a + 2*b + 2*n - 1)*(2*a + 2*b + n - 1)*summ(n)*n - 2*(2*a + n - 1)*(a + b + n - 1)*(2*b + n - 1)*summ(n - 1) 17: summand:=pochhammer(d,k)*pochhammer(1+d/2,k)* pochhammer(d+b-a,k)*pochhammer(d+c-a,k)* pochhammer(1+a-b-c,k)*pochhammer(n+a,k)* pochhammer(-n,k)/(factorial(k)*pochhammer(d/2,k)* pochhammer(1+a-b,k)*pochhammer(1+a-c,k)* pochhammer(b+c+d-a,k)*pochhammer(1+d-a-n,k)* pochhammer(1+d+n,k))$ 18: sumrecursion(summand,k,n); - (n - 1 + d + c + b - a)*(n - 1 - d + a) *(b - n - a)*(c - n - a)*summ(n) - (d - n + c + b - 2*a)*(n - 1 + b)*(n - 1 + c) *(d + n)*summ(n - 1)
corresponding to the statements \[ _4 F_3\left . \left ( \begin {array}{c} a\;, b\;, 1/2-a-b-n\;, -n\\[1mm] 1/2+a+b \;, 1-a-n\;, 1-b-n \end {array} \right | 1\right ) =\frac {(2a)_n\,(a+b)_n\,(2b)_n} {(2a+2b)_n\,(a)_n\,(b)_n} \] and \[ _7 F_6\left . \left ( \begin {array}{c} d\;, 1+d/2\;, d+b-a\;, d+c-a\;, 1+a-b-c\;, n+a\;, -n\\[1mm] d/2\;, 1+a-b\;, 1+a-c\;, b+c+d-a \;, 1+d-a-n\;, 1+d+n \end {array} \right | 1\right ) \] \[ =\frac {(d+1)_n\,(b)_n\,(c)_n\,(1+2\,a-b-c-d)_n} {(a-d)_n\,(1+a-b)_n\,(1+a-c)_n\,(b+c+d-a)_n} \] (compare next section), respectively.
Other applications of the Zeilberger algorithm are connected with the verification of identities. To prove the identity \[ \sum _{k=0}^n \binom {n}{k}^3 = \sum _{k=0}^n \binom {n}{k}^2 \binom {2k}{n} \;, \] e. g., we may prove that both sums satisfy the same recurrence equation
19: sumrecursion(binomial(n,k)^3,k,n); 2 2 8*(n - 1) *summ(n - 2) - summ(n)*n 2 + (7*n - 7*n + 2)*summ(n - 1) 20: sumrecursion(binomial(n,k)^2*binomial(2*k,n),k,n); 2 2 8*(n - 1) *summ(n - 2) - summ(n)*n 2 + (7*n - 7*n + 2)*summ(n - 1)
and finally check the initial conditions:
21: sub(n=0,k=0,binomial(n,k)^3); 1 22: sub(n=0,k=0,binomial(n,k)^2*binomial(2*k,n)); 1 23: sub(n=1,k=0,binomial(n,k)^3) +sub(n=1,k=1,binomial(n,k)^3); 2 24: sub(n=1,k=0,binomial(n,k)^2*binomial(2*k,n))+ sub(n=1,k=1,binomial(n,k)^2*binomial(2*k,n)); 2
The extended_sumrecursion operator is an implementation of an extension of the (fast) Zeilberger algorithm given by Koepf [Koe94b].
extended_sumrecursion(f,k,n,m,l) determines a holonomic recurrence equation for \(\texttt {summ(n)} =\sum \limits _{k=-\infty }^\infty f(n,k)\) with respect to \(n\) if \(f(n,k)\) is an \((m,l)\)-fold hypergeometric term with respect to \((n,k)\), i.e. \[ \frac {F(n,k)}{F(n-m,k)} \quad \mbox {and} \quad \frac {F(n,k)}{F(n,k-l)} \] are rational functions with respect to both \(n\) and \(k\). The resulting expression equals zero.
Internally, sumrecursion(f,k,n) calls (with suitable values \(m\) and \(l\)) extended_sumrecursion(f,k,n,m,l) and covers therefore the extended algorithm completely.
Examples:
25: extended_sumrecursion(binomial(n,k)*binomial(k/2,n), k,n,1,2); summ(n - 1) + 2*summ(n)
which can be obtained automatically by
26: sumrecursion(binomial(n,k)*binomial(k/2,n),k,n); summ(n - 1) + 2*summ(n)
Similarly, we get
27: extended_sumrecursion(binomial(n/2,k),k,n,2,1);
2*summ(n - 2) - summ(n)
28: sumrecursion(binomial(n/2,k),k,n);
2*summ(n - 2) - summ(n)
29: sumrecursion(hyperterm({a,b,a+1/2-b,1+2*a/3,-n},
{2*a+1-2*b,2*b,2/3*a,1+a+n/2},4,k)/(factorial(n)*2^(-n)/
factorial(n/2))/
hyperterm({a+1,1},{a-b+1,b+1/2},1,n/2),k,n);
summ(n - 2) - summ(n)
In the last example, the progam chooses \(m=2\), and \(l=1\) to derive the resulting recurrence equation (see [Koe94b], Table 3, (1.3)).
Sums to which the Zeilberger algorithm applies, in general are special cases of the generalized hypergeometric function \[ _{p}F_{q}\left .\left (\begin {array}{cccc} a_{1},&a_{2},&\cdots ,&a_{p}\\ b_{1},&b_{2},&\cdots ,&b_{q}\\ \end {array}\right | x\right ) := \sum _{k=0}^\infty \frac {(a_{1})_{k}\cdot (a_{2})_{k}\cdots (a_{p})_{k}} {(b_{1})_{k}\cdot (b_{2})_{k}\cdots (b_{q})_{k}\,k!}x^{k} \label {eq:coefficientformula} \] with upper parameters \(\{a_{1}, a_{2}, \ldots , a_{p}\}\), and lower parameters \(\{b_{1}, b_{2}, \ldots , b_{q}\}\). If a recursion for a generalized hypergeometric function is to be established, you can use the following REDUCE operator:
hyperrecursion(upper,lower,x,n) determines a holonomic recurrence equation with respect to \(n\) for \(_{p}F_{q}\left .\left (\begin {array}{cccc} a_{1},&a_{2},&\cdots ,&a_{p}\\ b_{1},&b_{2},&\cdots ,&b_{q}\\ \end {array}\right | x\right ) \), where upper\(=\{a_{1}, a_{2}, \ldots , a_{p}\}\) is the list of upper parameters, and lower\(=\{b_{1}, b_{2}, \ldots , b_{q}\}\) is the list of lower parameters depending on \(n\). If Zeilberger’s algorithm does not apply, extended_sumrecursion of § 20.65.7 is used.
hyperrecursion(upper,lower,x,n,j) \((j\in \mathbb {N})\) searches only for a holonomic recurrence equation of order \(j\). This operator does not use extended_sumrecursion automatically.
Therefore
30: hyperrecursion({-n,b},{c},1,n);
(b - c - n + 1)*summ(n - 1) + (c + n - 1)*summ(n)
establishes the Vandermonde identity \[ _2 F_1\left . \left ( \begin {array}{c} -n\;,\;\;b\\[1mm] c \end {array} \right | 1\right ) =\frac {(c-b)_n}{(c)_n} \;, \] whereas
31: hyperrecursion({d,1+d/2,d+b-a,d+c-a,1+a-b-c,n+a,-n},
{d/2,1+a-b,1+a-c,b+c+d-a,1+d-a-n,1+d+n},1,n);
- (n - 1 + d + c + b - a)*(n - 1 - d + a)
*(b - n - a)*(c - n - a)*summ(n) -
(d - n + c + b - 2*a)*(n - 1 + b)*(n - 1 + c)
*(d + n)*summ(n - 1)
proves Dougall’s identity, again.
If a hypergeometric expression is given in hypergeometric notation, then the use of hyperrecursion is more natural than the use of sumrecursion.
Moreover you may use the REDUCE operator
hyperterm(upper,lower,x,k) that yields the hypergeometric term \[ \frac {(a_{1})_{k}\cdot (a_{2})_{k}\cdots (a_{p})_{k}} {(b_{1})_{k}\cdot (b_{2})_{k}\cdots (b_{q})_{k}\,k!}x^{k} \] with upper parameters upper\(=\{a_{1}, a_{2}, \ldots , a_{p}\}\), and lower parameters lower\(=\{b_{1}, b_{2}, \ldots , b_{q}\}\)
in connection with hypergeometric terms.
The operator sumrecursion can also be used to obtain three-term recurrence equations for systems of orthogonal polynomials with the aid of known hypergeometric representations. By ([NUS91], (2.7.11a)), the discrete Krawtchouk polynomials \(k_n^{(p)}(x,N)\) have the hypergeometric representation \[ k_n^{(p)}(x,N)= (-1)^n\,p^n\,\binom {N}{n}\; _2 F_1\left . \left ( \begin {array}{c} -n\;,\;\;-x\\[1mm] -N \end {array} \right | \frac {1}{p}\right ) \;, \] and therefore we declare
32: krawtchoukterm:=
(-1)^n*p^n*binomial(NN,n)*hyperterm({-n,-x},{-NN},1/p,k)$
and get the three three-term recurrence equations
33: sumrecursion(krawtchoukterm,k,n); ((2*p - 1)*n - nn*p - 2*p + x + 1)*summ(n - 1) - (n - nn - 2)*(p - 1)*summ(n - 2)*p - summ(n)*n 34: sumrecursion(krawtchoukterm,k,x); (2*(x - 1)*p + n - nn*p - x + 1)*summ(x - 1) - ((x - 1) - nn)*summ(x)*p - (p - 1)*(x - 1)*summ(x - 2) 35: sumrecursion(krawtchoukterm,k,NN); (x + 1 + n + (p - 2)*nn)*summ(nn - 1) - ( (x + 1 - nn)*summ(nn - 2) - (n - nn)*(p - 1)*summ(nn))
with respect to the parameters \(n\), \(x\), and \(N\) respectively.
With the operator hypersum, hypergeometric sums are directly evaluated in closed form whenever the extended Zeilberger algorithm leads to a recurrence equation containing only two terms:
hypersum(upper,lower,x,n) determines a closed form representation for \(_{p}F_{q}\left .\left (\begin {array}{cccc} a_{1},&a_{2},&\cdots ,&a_{p}\\ b_{1},&b_{2},&\cdots ,&b_{q}\\ \end {array}\right | x\right ) \), where upper\(=\{a_{1}, a_{2}, \ldots , a_{p}\}\) is the list of upper parameters, and lower\(=\{b_{1}, b_{2}, \ldots , b_{q}\}\) is the list of lower parameters depending on \(n\). The result is given as a hypergeometric term with respect to \(n\).
If the result is a list of length \(m\), we call it \(m\)-fold symmetric, which is to be interpreted as follows: Its \(j^{th}\) part is the solution valid for all \(n\) of the form \(n=mk+j-1 \;(k\in \mathbb {N}_0)\). In particular, if the resulting list contains two terms, then the first part is the solution for even \(n\), and the second part is the solution for odd \(n\).
Examples [Koe94b]:
36: hypersum({a,1+a/2,c,d,-n},{a/2,1+a-c,1+a-d,1+a+n},1,n);
pochhammer(a - c - d + 1,n)*pochhammer(a + 1,n)
-------------------------------------------------
pochhammer(a - c + 1,n)*pochhammer(a - d + 1,n)
37: hypersum({a,1+a/2,d,-n},{a/2,1+a-d,1+a+n},-1,n);
pochhammer(a + 1,n)
-------------------------
pochhammer(a - d + 1,n)
Note that the operator togamma converts expressions given in factorial-\(\Gamma \)-binomial-Pochhammer notation into a pure \(\Gamma \) function representation:
38: togamma(ws); gamma(a - d + 1)*gamma(a + n + 1) ----------------------------------- gamma(a - d + n + 1)*gamma(a + 1)
Here are some \(m\)-fold symmetric results:
39: hypersum({-n,-n,-n},{1,1},1,n);
n/2 2 n 1 n
( - 27) *pochhammer(---,---)*pochhammer(---,---)
3 2 3 2
{----------------------------------------------------,
n 2
factorial(---)
2
0}
40: hypersum({-n,n+3*a,a},{3*a/2,(3*a+1)/2},3/4,n);
2 n 1 n
pochhammer(---,---)*pochhammer(---,---)
3 3 3 3
{-----------------------------------------------------,
3*a + 2 n 3*a + 1 n
pochhammer(---------,---)*pochhammer(---------,---)
3 3 3 3
0,
0}
These results correspond to the formulas (compare [Koe94b]) \[ _3 F_2\left . \left ( \begin {array}{c} -n\;, -n\;, -n\\[1mm] 1 \;, 1 \end {array} \right | 1\right ) = \funkdef {0}{n\;\mbox {odd}}{\displaystyle \frac {(1/3)_{n/2}\,(2/3)_{n/2}}{(n/2)!^2}\,(-27)^{n/2} } \] and \begin {multline*} _3 F_2\left . \left ( \begin {array}{c} -n\;, n+3a\;, a\\[1mm] 3a/2\;,(3a+1)/2 \end {array} \right | \frac {3}{4}\right ) \\ = \funkdef {0}{n\neq 0 {\mbox { (mod }} 3)}{\displaystyle \frac {(1/3)_{n/3}\,(2/3)_{n/3}} {(a+1/3)_{n/3}\,(a+2/3)_{n/3}} } \end {multline*}
With the operator sumtohyper, sums given in factorial-\(\Gamma \)-binomial-Pochhammer
notation are converted into hypergeometric notation.
sumtohyper(f,k) determines the hypergeometric representation of \(\sum \limits _{k=-\infty }^\infty f_k\), i.e. its
output is c*hypergeometric(upper,lower,x), corresponding to the
representation \[ \sum \limits _{k=-\infty }^\infty f_k=c\cdot \; _{p}F_{q}\left .\left (\begin {array}{cccc} a_{1},&a_{2},&\cdots ,&a_{p}\\ b_{1},&b_{2},&\cdots ,&b_{q}\\ \end {array}\right | x\right ) \;, \] where upper\(=\{a_{1}, a_{2}, \ldots , a_{p}\}\) and lower\(=\{b_{1}, b_{2}, \ldots , b_{q}\}\) are the lists of upper and lower parameters.
Examples:
41: sumtohyper(binomial(n,k)^3,k);
hypergeometric({ - n, - n, - n},{1,1},-1)
42: sumtohyper(binomial(n,k)/2^n
-sub(n=n-1,binomial(n,k)/2^n),k);
- n + 2 - n
- hypergeom({----------, - n},{------},-1)
2 2
---------------------------------------------
n
2
For the decision that an expression \(a_k\) is a hypergeometric term, it is necessary to find out whether or not \(a_{k}/a_{k-1}\) is a rational function with respect to \(k\). For the purpose to decide whether or not an expression involving powers, factorials, \(\Gamma \) function terms, binomial coefficients, and Pochhammer symbols is a hypergeometric term, the following simplification operators can be used:
simplify_gamma(f) simplifies an expression f involving only rational, powers and \(\Gamma \) function terms according to a recursive application of the simplification rule \(\Gamma \:(a+1)=a\,\Gamma \:(a)\) to the expression tree. Since all \(\Gamma \) arguments with integer difference are transformed, this gives a decision procedure for rationality for integer-linear \(\Gamma \) term product ratios.
simplify_combinatorial(f) simplifies an expression f involving powers, factorials, \(\Gamma \) function terms, binomial coefficients, and Pochhammer symbols by converting factorials, binomial coefficients, and Pochhammer symbols into \(\Gamma \) function terms, and applying simplify_gamma to its result. If the output is not rational, it is given in terms of \(\Gamma \) functions. If you prefer factorials you may use
gammatofactorial (rule) converting \(\Gamma \) function terms into factorials using \(\Gamma \:(x)\rightarrow (x-1)!\).
simplify_gamma2(f) uses the duplication formula of the \(\Gamma \) function to simplify \(f\).
simplify_gamman(f,n) uses the multiplication formula of the \(\Gamma \) function to simplify \(f\).
The use of simplify_combinatorial(f) is a safe way to decide the rationality for any ratio of products of powers, factorials, \(\Gamma \) function terms, binomial coefficients, and Pochhammer symbols.
Example:
43: simplify_combinatorial(sub(k=k+1,krawtchoukterm)/ krawtchoukterm); (k - n)*(k - x) -------------------- (k - nn)*(k + 1)*p
From this calculation, we see again that the upper parameters of the hypergeometric representation of the Krawtchouk polynomials are given by \(\{-n,-x\}\), its lower parameter is \(\{-N\}\), and the argument of the hypergeometric function is \(1/p\).
Other examples are
44: simplify_combinatorial(binomial(n,k)/binomial(2*n,k-1)); gamma( - (k - 2*n - 2))*gamma(n + 1) ---------------------------------------- gamma( - (k - n - 1))*gamma(2*n + 1)*k 45: ws where gammatofactorial; factorial( - k + 2*n + 1)*factorial(n) ---------------------------------------- factorial( - k + n)*factorial(2*n)*k 46: simplify_gamma2(gamma(2*n)/gamma(n)); 2*n 2*n + 1 2 *gamma(---------) 2 ----------------------- 2*sqrt(pi) 47: simplify_gamman(gamma(3*n)/gamma(n),3); 3*n 3*n + 2 3*n + 1 3 *gamma(---------)*gamma(---------) 3 3 ---------------------------------------- 2*sqrt(3)*pi
If you set
48: on zb_trace;
tracing is enabled, and you get intermediate results, see [Koe94b].
Example for the Gosper algorithm:
49: gosper(pochhammer(k-n,n),k); k - 1 a(k)/a(k-1):= ----------- k - n - 1 Gosper algorithm applicable p:= 1 q:= k - 1 r:= k - n - 1 degreebound := 0 1 f:= ------- n + 1 Gosper algorithm successful pochhammer(k - n,n)*k ----------------------- n + 1
Example for the Zeilberger algorithm:
50: sumrecursion(binomial(n,k)^2,k,n);
2
n
F(n,k)/F(n-1,k):= ----------
2
(k - n)
2
(k - n - 1)
F(n,k)/F(n,k-1):= --------------
2
k
Zeilberger algorithm applicable
applying Zeilberger algorithm for order:= 1
2 2 2
p:= zb_sigma(1)*k - 2*zb_sigma(1)*k*n + zb_sigma(1)*n + n
2 2
q:= k - 2*k*n - 2*k + n + 2*n + 1
2
r:= k
degreebound := 1
2*k - 3*n + 2
f:= ---------------
n
2 2 2 3 2
- 4*k *n + 2*k + 8*k*n - 4*k*n - 3*n + 2*n
p:= -------------------------------------------------
n
Zeilberger algorithm successful
4*summ(n - 1)*n - 2*summ(n - 1) - summ(n)*n
51: off zb_trace;
The following global variables and switches can be used in connection with the ZEILBERG package:
zb_trace, switch; default setting off. Turns tracing on and off.
zb_direction, variable; settings: down, up; default setting down.
In the case of the Gosper algorithm, either a downward or a forward antidifference is calculated, i.e., gosper finds \(g_k\) with either \[ a_k=g_k-g_{k-1} \quad \quad \mbox {or}\quad \quad a_k=g_{k+1}-g_{k}, \] respectively.
In the case of the Zeilberger algorithm, either a downward or an upward recurrence equation is returned. Example:
52: zb_direction:=up$
53: sumrecursion(binomial(n,k)^2,k,n);
summ(n + 1)*n + summ(n + 1) - 4*summ(n)*n - 2*summ(n)
54: zb_direction:=down$
zb_order, variable; settings: any nonnegative integer; default setting 5. Gives the maximal order for the recurrence equation that sumrecursion searches for.
zb_factor, switch; default setting on. If off, the factorization of the output usually producing nicer results is suppressed.
zb_proof, switch; default setting off. If on, then several intermediate results are stored in global variables:
gosper_representation, variable; default setting nil.
If a gosper command is issued, and if the Gosper algorithm is applicable, then the variable gosper_representation is set to the list of polynomials (with respect to \(k\)) {p,q,r,f} corresponding to the representation \[ \frac {a_k}{a_{k-1}}=\frac {p_k}{p_{k-1}}\,\frac {q_k}{r_k} \;, \quad \quad \quad g_k=\frac {q_{k+1}}{p_k}\,f_k\,a_k \;, \] see [Gos78]. Examples:
55: on zb_proof;
56: gosper(k*factorial(k),k);
(k + 1)*factorial(k)
57: gosper_representation;
{k,k,1,1}
58: gosper(
1/(k+1)*binomial(2*k,k)/(n-k+1)
*binomial(2*n-2*k,n-k),k);
((2*k - n + 1)*(2*k + 1)
*binomial( - 2*(k - n), - (k - n))
*binomial(2*k,k))/((k + 1)*(n + 2)*(n + 1))
59: gosper_representation;
{1,
(2*k - 1)*(k - n - 2),
(2*k - 2*n - 1)*(k + 1),
- (2*k - n + 1)
------------------}
(n + 2)*(n + 1)
zeilberger_representation, variable; default setting nil.
If a sumrecursion command is issued, and if the Zeilberger algorithm is successful, then the variable zeilberger_representation is set to the final Gosper representation used, see [Koo93].
zb_f, internal operator, do not use.
zb_sigma, internal operator, do not use.
The following messages may occur:
*****
Gosper algorithm: no closed form solution exists
Example input:
gosper(factorial(k),k).
***** Gosper algorithm not applicable
Example input:
gosper(factorial(k/2),k).
The term ratio \(a_k/a_{k-1}\) is not rational.
***** illegal number of arguments
Example input:
gosper(k).
***** Zeilberger algorithm fails. Enlarge zb_order
Example input:
sumrecursion(binomial(n,k)*binomial(6*k,n),k,n)
For this example a setting zb_order:=6 is needed.
***** Zeilberger algorithm not applicable
Example input:
sumrecursion(binomial(n/2,k),k,n)
One of the term ratios \(f(n,k)/f(n-1,k)\) or \(f(n,k)/f(n,k-1)\) is not rational.
***** SOLVE given inconsistent equations
You can ignore this message that occurs with Version 3.5.
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