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  2. Cubic equation - Wikipedia

    en.wikipedia.org/wiki/Cubic_equation

    For solving the cubic equation x 3 + m 2 x = n where n > 0, Omar Khayyám constructed the parabola y = x 2 /m, the circle that has as a diameter the line segment [0, n/m 2] on the positive x-axis, and a vertical line through the point where the circle and the parabola intersect above the x-axis.

  3. Lill's method - Wikipedia

    en.wikipedia.org/wiki/Lill's_method

    Find roots of 3x 3 + 2x 2 − 7x + 2. In 1936, Margherita Piazzola Beloch showed how Lill's method could be adapted to solve cubic equations using paper folding. [6] If simultaneous folds are allowed, then any n th-degree equation with a real root can be solved using n − 2 simultaneous folds. [7]

  4. Solution in radicals - Wikipedia

    en.wikipedia.org/wiki/Solution_in_radicals

    A solution in radicals or algebraic solution is an expression of a solution of a polynomial equation that is algebraic, that is, relies only on addition, subtraction, multiplication, division, raising to integer powers, and extraction of n th roots (square roots, cube roots, etc.). A well-known example is the quadratic formula

  5. Nested radical - Wikipedia

    en.wikipedia.org/wiki/Nested_radical

    If we solve this equation, we find that x = 2. More generally, we find that + + + + is the positive real root of the equation x 3x − n = 0 for all n > 0. For n = 1, this root is the plastic ratio ρ, approximately equal to 1.3247.

  6. Equation solving - Wikipedia

    en.wikipedia.org/wiki/Equation_solving

    An example of using Newton–Raphson method to solve numerically the equation f(x) = 0. In mathematics, to solve an equation is to find its solutions, which are the values (numbers, functions, sets, etc.) that fulfill the condition stated by the equation, consisting generally of two expressions related by an equals sign.

  7. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    This is the case, for example, if f(x) = x 3 − 2x + 2. For this function, it is even the case that Newton's iteration as initialized sufficiently close to 0 or 1 will asymptotically oscillate between these values. For example, Newton's method as initialized at 0.99 yields iterates 0.99, −0.06317, 1.00628, 0.03651, 1.00196, 0.01162, 1.00020 ...

  8. Laguerre's method - Wikipedia

    en.wikipedia.org/wiki/Laguerre's_method

    If x is a simple root of the polynomial , then Laguerre's method converges cubically whenever the initial guess, , is close enough to the root . On the other hand, when x 1 {\displaystyle \ x_{1}\ } is a multiple root convergence is merely linear, with the penalty of calculating values for the polynomial and its first and second derivatives at ...

  9. Cubic function - Wikipedia

    en.wikipedia.org/wiki/Cubic_function

    The roots, stationary points, inflection point and concavity of a cubic polynomial x 3 − 6x 2 + 9x − 4 (solid black curve) and its first (dashed red) and second (dotted orange) derivatives. The critical points of a cubic function are its stationary points , that is the points where the slope of the function is zero. [ 2 ]

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