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  2. File:Zernike polynomials3.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Zernike_polynomials3.pdf

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  3. Perfect field - Wikipedia

    en.wikipedia.org/wiki/Perfect_field

    Every imperfect field is necessarily transcendental over its prime subfield (the minimal subfield), because the latter is perfect. An example of an imperfect field is the field F q ( x ) {\displaystyle \mathbf {F} _{q}(x)} , since the Frobenius endomorphism sends x ↦ x p {\displaystyle x\mapsto x^{p}} and therefore is not surjective.

  4. Algebraic function field - Wikipedia

    en.wikipedia.org/wiki/Algebraic_function_field

    The algebraic function fields over k form a category; the morphisms from function field K to L are the ring homomorphisms f : K → L with f(a) = a for all a in k. All these morphisms are injective. If K is a function field over k of n variables, and L is a function field in m variables, and n > m, then there are no morphisms from K to L.

  5. Linearised polynomial - Wikipedia

    en.wikipedia.org/wiki/Linearised_polynomial

    The map x ↦ L(x) is a linear map over any field containing F q.; The set of roots of L is an F q-vector space and is closed under the q-Frobenius map.; Conversely, if U is any F q-linear subspace of some finite field containing F q, then the polynomial that vanishes exactly on U is a linearised polynomial.

  6. Resolvent cubic - Wikipedia

    en.wikipedia.org/wiki/Resolvent_cubic

    We can also assume without loss of generality that it is a reduced polynomial, because P(x) can be expressed as the product of two quadratic polynomials if and only if P(x − a 3 /4) can and this polynomial is a reduced one. Then R 3 (y) = y 3 + 2a 2 y 2 + (a 2 2 − 4a 0)y − a 1 2. There are two cases: If a 1 ≠ 0 then R 3 (0) = −a 1 2 < 0.

  7. Factorization of polynomials over finite fields - Wikipedia

    en.wikipedia.org/wiki/Factorization_of...

    Algorithm: SFF (Square-Free Factorization) Input: A monic polynomial f in F q [x] where q = p m Output: Square-free factorization of f R ← 1 # Make w be the product (without multiplicity) of all factors of f that have # multiplicity not divisible by p c ← gcd(f, f′) w ← f/c # Step 1: Identify all factors in w i ← 1 while w ≠ 1 do y ...

  8. Hilbert's basis theorem - Wikipedia

    en.wikipedia.org/wiki/Hilbert's_basis_theorem

    Hilbert proved the theorem (for the special case of multivariate polynomials over a field) in the course of his proof of finite generation of rings of invariants. [1] The theorem is interpreted in algebraic geometry as follows: every algebraic set is the set of the common zeros of finitely many polynomials.

  9. Hilbert's seventeenth problem - Wikipedia

    en.wikipedia.org/wiki/Hilbert's_seventeenth_problem

    Furthermore, if the polynomial has a degree 2d greater than two, there are significantly many more non-negative polynomials that cannot be expressed as sums of squares. [4] The following table summarizes in which cases every non-negative homogeneous polynomial (or a polynomial of even degree) can be represented as a sum of squares: