Polynomial decomposition

{{Short description|Factorization under function composition}}

In mathematics, a polynomial decomposition expresses a polynomial f as the functional composition g \circ h of polynomials g and h, where g and h have degree greater than 1; it is an algebraic functional decomposition. Algorithms are known for decomposing univariate polynomials in polynomial time.

Polynomials which are decomposable in this way are composite polynomials; those which are not are indecomposable polynomials or sometimes prime polynomialsJ.F. Ritt, "Prime and Composite Polynomials", Transactions of the American Mathematical Society 23:1:51–66 (January, 1922) {{doi|10.2307/1988911}} {{JSTOR|1988911}} (not to be confused with irreducible polynomials, which cannot be factored into products of polynomials). The degree of a composite polynomial is always a composite number, the product of the degrees of the composed polynomials.

The rest of this article discusses only univariate polynomials; algorithms also exist for multivariate polynomials of arbitrary degree.Jean-Charles Faugère, Ludovic Perret, "An efficient algorithm for decomposing multivariate polynomials and its applications to cryptography", Journal of Symbolic Computation, 44:1676-1689 (2009), {{doi|10.1016/j.jsc.2008.02.005}}

Examples

In the simplest case, one of the polynomials is a monomial. For example,

:f = x^6 - 3 x^3 + 1

decomposes into

:g = x^2 - 3 x + 1 \text{ and } h = x^3

since

:f(x) = (g \circ h)(x) = g(h(x)) = g(x^3) = (x^3)^2 - 3 (x^3) + 1,

using the ring operator symbol to denote function composition.

Less trivially,

:

\begin{align}

& x^6-6 x^5+21 x^4-44 x^3+68 x^2-64 x+41 \\

= {} & (x^3+9 x^2+32 x+41) \circ (x^2-2 x).

\end{align}

Uniqueness

A polynomial may have distinct decompositions into indecomposable polynomials where f = g_1 \circ g_2 \circ \cdots \circ g_m = h_1 \circ h_2 \circ \cdots\circ h_n where g_i \neq h_i for some i. The restriction in the definition to polynomials of degree greater than one excludes the infinitely many decompositions possible with linear polynomials.

Joseph Ritt proved that m = n, and the degrees of the components are the same, but possibly in different order; this is Ritt's polynomial decomposition theorem.Capi Corrales-Rodrigáñez, "A note on Ritt's theorem on decomposition of polynomials", Journal of Pure and Applied Algebra 68:3:293–296 (6 December 1990) {{doi|10.1016/0022-4049(90)90086-W}} For example, x^2 \circ x^3 = x^3 \circ x^2.

Applications

A polynomial decomposition may enable more efficient evaluation of a polynomial. For example,

:

\begin{align}

& x^8 + 4 x^7 + 10 x^6 + 16 x^5 + 19 x^4 + 16 x^3 + 10 x^2 + 4 x - 1 \\

= {} & \left(x^2 - 2\right) \circ \left(x^2\right) \circ \left(x^2 + x + 1\right)

\end{align}

can be calculated with 3 multiplications and 3 additions using the decomposition, while Horner's method would require 7 multiplications and 8 additions.

A polynomial decomposition enables calculation of symbolic roots using radicals, even for some irreducible polynomials. This technique is used in many computer algebra systems.The examples below were calculated using Maxima. For example, using the decomposition

:

\begin{align}

& x^6 - 6 x^5 + 15 x^4 - 20 x^3 + 15 x^2 - 6 x - 1 \\

= {} & \left(x^3 - 2\right) \circ \left(x^2 - 2 x + 1\right),

\end{align}

the roots of this irreducible polynomial can be calculated asWhere each ± is taken independently.

:1 \pm 2^{1/6}, 1 \pm \frac{\sqrt{-1 \pm \sqrt{3}i}}{2^{1/3}}.

Even in the case of quartic polynomials, where there is an explicit formula for the roots, solving using the decomposition often gives a simpler form. For example, the decomposition

:

\begin{align}

& x^4 - 8 x^3 + 18 x^2 - 8 x + 2 \\

= {} & (x^2 + 1) \circ (x^2 - 4 x + 1)

\end{align}

gives the roots

: 2 \pm \sqrt{3 \pm i}

but straightforward application of the quartic formula gives equivalent results but in a form that is difficult to simplify and difficult to understand; one of the four roots is:

: 2-{ \frac{\sqrt{{{ 9 \left(\frac{8 \sqrt{10} i}{3^{3/2}} + 72\right)^{2/3} + 36 \left(\frac{8 \sqrt{10} i}{3^{3/2}} + 72\right)^{1/3} + 156} \over {\left({\frac{8 \sqrt{10} i}{3^{3/2}}} + 72\right)^{1/3}}}}} 6}-{{\sqrt{-\left(\frac{8 \sqrt{10} i}{3^{3/2}} + 72\right)^{1/3}-{{52}\over{3 \left(\frac{8 \sqrt{10} i}{3^{3/2}} +72\right)^{1/3}}} + 8}}\over 2} .

Algorithms

The first algorithm for polynomial decomposition was published in 1985,{{cite journal |author=David R. Barton, Richard Zippel |title=Polynomial Decomposition Algorithms |journal=Journal of Symbolic Computation |volume=1 |pages=159–168 |year=1985|issue=2 |doi=10.1016/S0747-7171(85)80012-2 }} though it had been discovered in 1976,Richard Zippel, [http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.3154 Functional Decomposition], 1996. and implemented in the Macsyma/Maxima computer algebra system.See the [https://maxima.sourceforge.io/docs/manual/maxima_76.html#index-polydecomp polydecomp function]. That algorithm takes exponential time in worst case, but works independently of the characteristic of the underlying field.

A 1989 algorithm runs in polynomial time but with restrictions on the characteristic.{{cite journal |author=Kozen |first1=Dexter |author-link1=Dexter Kozen |last2=Landau |first2=Susan |author-link2=Susan Landau |year=1989 |title=Polynomial Decomposition Algorithms |journal=Journal of Symbolic Computation |volume=7 |issue=5 |pages=445–456|doi=10.1016/S0747-7171(89)80027-6 |citeseerx=10.1.1.416.6491 }}

A 2014 algorithm calculates a decomposition in polynomial time and without restrictions on the characteristic.{{cite journal |author=Raoul Blankertz |title=A polynomial time algorithm for computing all minimal decompositions of a polynomial |journal=ACM Communications in Computer Algebra |volume=48 |pages=1 |issue=187 |year=2014 |url=http://www.sigsam.org/bulletin/articles/187/Polynomial_time_decomposition_pp13-23.pdf}} {{webarchive|url=https://web.archive.org/web/20150924101735/http://www.sigsam.org/bulletin/articles/187/Polynomial_time_decomposition_pp13-23.pdf |date=2015-09-24 }}

Notes

{{reflist|colwidth=30em}}

References

  • {{cite book |author=Joel S. Cohen |chapter=Chapter 5. Polynomial Decomposition |title=Computer Algebra and Symbolic Computation: Mathematical Methods |year=2003 |isbn=1-56881-159-4}}

Category:Polynomials

Category:Computer algebra