Search results
Results From The WOW.Com Content Network
In the case of two nested square roots, the following theorem completely solves the problem of denesting. [2]If a and c are rational numbers and c is not the square of a rational number, there are two rational numbers x and y such that + = if and only if is the square of a rational number d.
An illustration of Newton's method. In numerical analysis, the Newton–Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.
Two root systems (E 1, Φ 1) and (E 2, Φ 2) are called isomorphic if there is an invertible linear transformation E 1 → E 2 which sends Φ 1 to Φ 2 such that for each pair of roots, the number , is preserved. [7] The root lattice of a root system Φ is the Z-submodule of E generated by Φ.
The unique primitive square root of unity is ; the primitive fourth roots of unity are and . The n th roots of unity allow expressing all n th roots of a complex number z as the n products of a given n th roots of z with a n th root of unity.
In the finite-dimensional case, i.e. when T is a square matrix (Nilpotent matrix) with complex entries, σ(T) = {0} if and only if T is similar to a matrix whose only nonzero entries are on the superdiagonal [2] (this fact is used to prove the existence of Jordan canonical form). In turn this is equivalent to T n = 0 for some n. Therefore, for ...
In statistical mechanics, the mean squared displacement (MSD, also mean square displacement, average squared displacement, or mean square fluctuation) is a measure of the deviation of the position of a particle with respect to a reference position over time.
It is obtained by taking the ratio of the covariance of the two variables in question of our numerical dataset, normalized to the square root of their variances. Mathematically, one simply divides the covariance of the two variables by the product of their standard deviations .
For an approximately normal data set, the values within one standard deviation of the mean account for about 68% of the set; while within two standard deviations account for about 95%; and within three standard deviations account for about 99.7%.