Maxima 5.43.0 Manual: zeilberger-pkg

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## 90 zeilberger

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### 90.1 Introduction to zeilberger

`zeilberger` is a implementation of Zeilberger’s algorithm for definite hypergeometric summation, and also Gosper’s algorithm for indefinite hypergeometric summation.

`zeilberger` makes use of the "filtering" optimization method developed by Axel Riese.

`zeilberger` was developed by Fabrizio Caruso.

`load ("zeilberger")` loads this package.

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#### 90.1.1 The indefinite summation problem

`zeilberger` implements Gosper’s algorithm for indefinite hypergeometric summation. Given a hypergeometric term F_k in k we want to find its hypergeometric anti-difference, that is, a hypergeometric term f_k such that

F_k = f_(k+1) - f_k.

#### 90.1.2 The definite summation problem

`zeilberger` implements Zeilberger’s algorithm for definite hypergeometric summation. Given a proper hypergeometric term (in n and k) F_(n,k) and a positive integer d we want to find a d-th order linear recurrence with polynomial coefficients (in n) for F_(n,k) and a rational function R in n and k such that

a_0 F_(n,k) + ... + a_d F_(n+d),k = Delta_k(R(n,k) F_(n,k)),

where Delta_k is the k-forward difference operator, i.e., Delta_k(t_k) := t_(k+1) - t_k.

#### 90.1.3 Verbosity levels

There are also verbose versions of the commands which are called by adding one of the following prefixes:

`Summary`

  Just a summary at the end is shown

`Verbose`

  Some information in the intermidiate steps

`VeryVerbose`

  More information

`Extra`

  Even more information including information on the linear system in Zeilberger’s algorithm

For example:
`GosperVerbose`, `parGosperVeryVerbose`, `ZeilbergerExtra`, `AntiDifferenceSummary`.

Previous: Introduction to zeilberger, Up: zeilberger-pkg [Contents][Index]

### 90.2 Functions and Variables for zeilberger

Function: AntiDifference (F_k, k)

  Returns the hypergeometric anti-difference of F_k, if it exists.
  Otherwise `AntiDifference` returns `no_hyp_antidifference`.

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  Categories: Package zeilberger

Function: Gosper (F_k, k)

  Returns the rational certificate R(k) for F_k, that is, a rational function such that F_k = R(k+1) F_(k+1) - R(k) F_k, if it exists. Otherwise, `Gosper` returns `no_hyp_sol`.

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Function: GosperSum (F_k, k, a, b)

  Returns the summmation of F_k from k = a to k = b if F_k has a hypergeometric anti-difference. Otherwise, `GosperSum` returns `nongosper_summable`.

  Examples:

      (%i1) load ("zeilberger")$

      (%i2) GosperSum ((-1)^k*k / (4*k^2 - 1), k, 1, n);
      Dependent equations eliminated:  (1)
                                 3       n + 1
                            (n + -) (- 1)
                                 2               1
      (%o2)               - ------------------ - -
                                        2        4
                            2 (4 (n + 1)  - 1)

      (%i3) GosperSum (1 / (4*k^2 - 1), k, 1, n);
                                      3
                                - n - -
                                      2       1
      (%o3)                  -------------- + -
                                      2       2
                             4 (n + 1)  - 1

      (%i4) GosperSum (x^k, k, 1, n);
                                n + 1
                               x          x
      (%o4)                    ------ - -----
                               x - 1    x - 1

      (%i5) GosperSum ((-1)^k*a! / (k!*(a - k)!), k, 1, n);
                                      n + 1
                      a! (n + 1) (- 1)              a!
      (%o5)       - ------------------------- - ----------
                    a (- n + a - 1)! (n + 1)!   a (a - 1)!

      (%i6) GosperSum (k*k!, k, 1, n);
      Dependent equations eliminated:  (1)
      (%o6)                     (n + 1)! - 1

      (%i7) GosperSum ((k + 1)*k! / (k + 1)!, k, 1, n);
                        (n + 1) (n + 2) (n + 1)!
      (%o7)             ------------------------ - 1
                                (n + 2)!

      (%i8) GosperSum (1 / ((a - k)!*k!), k, 1, n);
      (%o8)                  NON_GOSPER_SUMMABLE

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Function: parGosper (F_(n,k), k, n, d)

  Attempts to find a d-th order recurrence for F_(n,k).

  The algorithm yields a sequence [s_1, s_2, ..., s_m] of solutions. Each solution has the form

  [R(n, k), [a_0, a_1, ..., a_d]].

  `parGosper` returns `[]` if it fails to find a recurrence.

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Function: Zeilberger (F_(n,k), k, n)

  Attempts to compute the indefinite hypergeometric summation of F_(n,k).

  `Zeilberger` first invokes `Gosper`, and if that fails to find a solution, then invokes `parGosper` with order 1, 2, 3, ..., up to `MAX_ORD`. If Zeilberger finds a solution before reaching `MAX_ORD`, it stops and returns the solution.

  The algorithms yields a sequence [s_1, s_2, ..., s_m] of solutions. Each solution has the form

  [R(n,k), [a_0, a_1, ..., a_d]].

  `Zeilberger` returns `[]` if it fails to find a solution.

  `Zeilberger` invokes `Gosper` only if `Gosper_in_Zeilberger` is `true`.

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### 90.3 General global variables

Global variable: MAX_ORD

  Default value: 5

  `MAX_ORD` is the maximum recurrence order attempted by `Zeilberger`.

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Global variable: simplified_output

  Default value: `false`

  When `simplified_output` is `true`, functions in the `zeilberger` package attempt further simplification of the solution.

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Global variable: linear_solver

  Default value: `linsolve`

  `linear_solver` names the solver which is used to solve the system of equations in Zeilberger’s algorithm.

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Global variable: warnings

  Default value: `true`

  When `warnings` is `true`, functions in the `zeilberger` package print warning messages during execution.

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Global variable: Gosper_in_Zeilberger

  Default value: `true`

  When `Gosper_in_Zeilberger` is `true`, the `Zeilberger` function calls `Gosper` before calling `parGosper`. Otherwise, `Zeilberger` goes immediately to `parGosper`.

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Global variable: trivial_solutions

  Default value: `true`

  When `trivial_solutions` is `true`, `Zeilberger` returns solutions which have certificate equal to zero, or all coefficients equal to zero.

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### 90.4 Variables related to the modular test

Global variable: mod_test

  Default value: `false`

  When `mod_test` is `true`, `parGosper` executes a modular test for discarding systems with no solutions.

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Global variable: modular_linear_solver

  Default value: `linsolve`

  `modular_linear_solver` names the linear solver used by the modular test in `parGosper`.

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Global variable: ev_point

  Default value: `big_primes[10]`

  `ev_point` is the value at which the variable n is evaluated when executing the modular test in `parGosper`.

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Global variable: mod_big_prime

  Default value: `big_primes[1]`

  `mod_big_prime` is the modulus used by the modular test in `parGosper`.

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Global variable: mod_threshold

  Default value: 4

  `mod_threshold` is the greatest order for which the modular test in `parGosper` is attempted.

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  Categories: Package zeilberger

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