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  2. Lill's method - Wikipedia

    en.wikipedia.org/wiki/Lill's_method

    Finding roots of 3x 2 + 5x − 2. Lill's method can be used with Thales's theorem to find the real roots of a quadratic polynomial. In this example with 3x 2 + 5x − 2, the polynomial's line segments are first drawn in black, as above. A circle is drawn with the straight line segment joining the start and end points forming a diameter.

  3. Coefficient - Wikipedia

    en.wikipedia.org/wiki/Coefficient

    The leading entry (sometimes leading coefficient [citation needed]) of a row in a matrix is the first nonzero entry in that row. So, for example, in the matrix ( 1 2 0 6 0 2 9 4 0 0 0 4 0 0 0 0 ) , {\displaystyle {\begin{pmatrix}1&2&0&6\\0&2&9&4\\0&0&0&4\\0&0&0&0\end{pmatrix}},} the leading coefficient of the first row is 1; that of the second ...

  4. Factor theorem - Wikipedia

    en.wikipedia.org/wiki/Factor_theorem

    Deduce the candidate of zero of the polynomial from its leading coefficient and constant term . (See Rational Root Theorem .) Use the factor theorem to conclude that ( x − a ) {\displaystyle (x-a)} is a factor of f ( x ) {\displaystyle f(x)} .

  5. Gröbner basis - Wikipedia

    en.wikipedia.org/wiki/Gröbner_basis

    The first (greatest) term of a polynomial p for this ordering and the corresponding monomial and coefficient are respectively called the leading term, leading monomial and leading coefficient and denoted, in this article, lt(p), lm(p) and lc(p). Most polynomial operations related to Gröbner bases involve the leading terms.

  6. Row echelon form - Wikipedia

    en.wikipedia.org/wiki/Row_echelon_form

    The leading entry (that is, the left-most nonzero entry) of every nonzero row, called the pivot, is on the right of the leading entry of every row above. [ 2 ] Some texts add the condition that the leading coefficient must be 1 [ 3 ] while others require this only in reduced row echelon form .

  7. Factorization of polynomials - Wikipedia

    en.wikipedia.org/wiki/Factorization_of_polynomials

    A simplified version of the LLL factorization algorithm is as follows: calculate a complex (or p-adic) root α of the polynomial () to high precision, then use the Lenstra–Lenstra–Lovász lattice basis reduction algorithm to find an approximate linear relation between 1, α, α 2, α 3, . . . with integer coefficients, which might be an ...

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