Polynomial solutions of P-recursive equations
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In mathematics a
P-recursive equation In mathematics a P-recursive equation is a linear equation of sequences where the coefficient sequences can be represented as polynomials. P-recursive equations are linear recurrence equations (or linear recurrence relations or linear difference ...
can be solved for polynomial solutions. Sergei A. Abramov in 1989 and
Marko Petkovšek Marko Petkovšek is a Slovenian mathematician, born: 1955, working mainly in symbolic computation. He is a professor of discrete and computational mathematics at the University of Ljubljana. He completed his Ph.D. at Carnegie Mellon University u ...
in 1992 described an
algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, problems or to perform a computation. Algorithms are used as specificat ...
which finds all
polynomial In mathematics, a polynomial is an expression consisting of indeterminates (also called variables) and coefficients, that involves only the operations of addition, subtraction, multiplication, and positive-integer powers of variables. An exa ...
solutions of those recurrence equations with polynomial coefficients. The algorithm computes a ''degree bound'' for the solution in a first step. In a second step an
ansatz In physics and mathematics, an ansatz (; , meaning: "initial placement of a tool at a work piece", plural Ansätze ; ) is an educated guess or an additional assumption made to help solve a problem, and which may later be verified to be part of the ...
for a polynomial of this degree is used and the unknown coefficients are computed by a
system of linear equations In mathematics, a system of linear equations (or linear system) is a collection of one or more linear equations involving the same variable (math), variables. For example, :\begin 3x+2y-z=1\\ 2x-2y+4z=-2\\ -x+\fracy-z=0 \end is a system of three ...
. This article describes this algorithm. In 1995 Abramov, Bronstein and Petkovšek showed that the polynomial case can be solved more efficiently by considering
power series In mathematics, a power series (in one variable) is an infinite series of the form \sum_^\infty a_n \left(x - c\right)^n = a_0 + a_1 (x - c) + a_2 (x - c)^2 + \dots where ''an'' represents the coefficient of the ''n''th term and ''c'' is a const ...
solution of the recurrence equation in a specific power basis (i.e. not the ordinary basis (x^n)_). Other algorithms which compute
rational Rationality is the quality of being guided by or based on reasons. In this regard, a person acts rationally if they have a good reason for what they do or a belief is rational if it is based on strong evidence. This quality can apply to an abili ...
or hypergeometric solutions of a linear recurrence equation with polynomial coefficients also use algorithms which compute polynomial solutions.


Degree bound

Let \mathbb be a
field Field may refer to: Expanses of open ground * Field (agriculture), an area of land used for agricultural purposes * Airfield, an aerodrome that lacks the infrastructure of an airport * Battlefield * Lawn, an area of mowed grass * Meadow, a grass ...
of characteristic zero and \sum_^r p_k(n) \, y (n+k) = f(n) a
recurrence equation In mathematics, a recurrence relation is an equation according to which the nth term of a sequence of numbers is equal to some combination of the previous terms. Often, only k previous terms of the sequence appear in the equation, for a parameter ...
of order r with polynomial coefficients p_k \in \mathbb /math>, polynomial right-hand side f \in \mathbb /math> and unknown polynomial sequence y(n) \in \mathbb /math>. Furthermore \deg (p) denotes the degree of a polynomial p \in \mathbb /math> (with \deg (0) = - \infty for the zero polynomial) and \text(p) denotes the leading coefficient of the polynomial. Moreover let\begin q_i &= \sum_^r \binom p_k, & b &= \max_(\deg (q_i)-i), \\ \alpha(n) &= \sum_ \text (q_i) n^, & d_\alpha &= \max \ \cup \ \endfor i=0,\dots,r where n^ = n (n-1) \cdots (n-i+1) denotes the
falling factorial In mathematics, the falling factorial (sometimes called the descending factorial, falling sequential product, or lower factorial) is defined as the polynomial :\begin (x)_n = x^\underline &= \overbrace^ \\ &= \prod_^n(x-k+1) = \prod_^(x-k) \,. \e ...
and \N the set of nonnegative integers. Then \deg (y) \leq \max \. This is called a degree bound for the polynomial solution y. This bound was shown by Abramov and Petkovšek.


Algorithm

The algorithm consists of two steps. In a first step the ''degree bound'' is computed. In a second step an ''ansatz'' with a polynomial y of that degree with arbitrary coefficients in \mathbb is made and plugged into the recurrence equation. Then the different powers are compared and a system of linear equations for the coefficients of y is set up and solved. This is called the ''method undetermined coefficients''. The algorithm returns the general polynomial solution of a recurrence equation. algorithm polynomial_solutions is input: Linear recurrence equation \sum_^r p_k(n) \, y (n+k) = f(n), p_k, f \in \mathbb p_0, p_r \neq 0. output: The general polynomial solution y if there are any solutions, otherwise false. for i=0,\dots,r do q_i = \sum_^r \binom p_k repeat b=\max_ (\deg (q_i) - i) \alpha(n) = \sum_ \text (q_i) n^ d_\alpha = \max \ \cup \ d = \max \ y(n) = \sum_^d y_j n^j with unknown coefficients y_j \in \mathbb for j=0,\dots,d Compare coefficients of polynomials \sum_^r p_k(n) \, y (n+k) and f(n) to get possible values for y_j, j=0,\dots,d if there are possible values for y_j then return general solution y else return false end if


Example

Applying the formula for the degree bound on the recurrence equation(n^2-2) \, y (n) + (-n^2+2n) \, y (n+1)=2n,over \Q yields \deg (y) \leq 2. Hence one can use an ansatz with a quadratic polynomial y(n) =y_2 n^2 + y_1 n + y_0 with y_0, y_1, y_2 \in \Q. Plugging this ansatz into the original recurrence equation leads to2n = (n^2-2) \, y(n) + (-n^2+2n) \, y (n+1) = (y_1 + y_2) \, n^2 + (2 y_0 + 2 y_2 ) \, n - 2 y_0.This is equivalent to the following system of linear equations\begin \begin 0 & 1 & 1 \\ 2 & 0 & 2 \\ -2 & 0 & 0 \end \begin y_0 \\ y_1 \\ y_2 \end = \begin 0 \\ 2 \\ 0 \end \end{align}with the solution y_0 = 0, y_1 = -1, y_2 = 1. Therefore the only polynomial solution is y (n) = n^2-n.


References

Polynomials