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  2. Cross product - Wikipedia

    en.wikipedia.org/wiki/Cross_product

    The cross product with respect to a right-handed coordinate system. In mathematics, the cross product or vector product (occasionally directed area product, to emphasize its geometric significance) is a binary operation on two vectors in a three-dimensional oriented Euclidean vector space (named here ), and is denoted by the symbol .

  3. Pauli matrices - Wikipedia

    en.wikipedia.org/wiki/Pauli_matrices

    The fact that the Pauli matrices, along with the identity matrix I, form an orthogonal basis for the Hilbert space of all 2 × 2 complex matrices , over , means that we can express any 2 × 2 complex matrix M as = + where c is a complex number, and a is a 3-component, complex vector.

  4. Rotation formalisms in three dimensions - Wikipedia

    en.wikipedia.org/wiki/Rotation_formalisms_in...

    These statements comprise a total of 6 conditions (the cross product contains 3), leaving the rotation matrix with just 3 degrees of freedom, as required. Two successive rotations represented by matrices A 1 and A 2 are easily combined as elements of a group, A total = A 2 A 1 {\displaystyle \mathbf {A} _{\text{total}}=\mathbf {A} _{2}\mathbf ...

  5. Triple product - Wikipedia

    en.wikipedia.org/wiki/Triple_product

    In geometry and algebra, the triple product is a product of three 3-dimensional vectors, usually Euclidean vectors.The name "triple product" is used for two different products, the scalar-valued scalar triple product and, less often, the vector-valued vector triple product.

  6. Rotation matrix - Wikipedia

    en.wikipedia.org/wiki/Rotation_matrix

    corresponds to a rotation of approximately −74° around the axis (− ⁠ 1 / 2 ⁠,1,1) in three-dimensional space. The 3 × 3 permutation matrix = [] is a rotation matrix, as is the matrix of any even permutation, and rotates through 120° about the axis x = y = z. The 3 × 3 matrix

  7. Exterior algebra - Wikipedia

    en.wikipedia.org/wiki/Exterior_algebra

    where {e 1 ∧ e 2, e 3 ∧ e 1, e 2 ∧ e 3} is the basis for the three-dimensional space ⋀ 2 (R 3). The coefficients above are the same as those in the usual definition of the cross product of vectors in three dimensions, the only difference being that the exterior product is not an ordinary vector, but instead is a bivector. Bringing in a ...

  8. Spinors in three dimensions - Wikipedia

    en.wikipedia.org/wiki/Spinors_in_three_dimensions

    Given a unit vector in 3 dimensions, for example (a, b, c), one takes a dot product with the Pauli spin matrices to obtain a spin matrix for spin in the direction of the unit vector. The eigenvectors of that spin matrix are the spinors for spin-1/2 oriented in the direction given by the vector. Example: u = (0.8, -0.6, 0) is a unit vector ...

  9. Dyadics - Wikipedia

    en.wikipedia.org/wiki/Dyadics

    Also, the dot, cross, and dyadic products can all be expressed in matrix form. Dyadic expressions may closely resemble the matrix equivalents. The dot product of a dyadic with a vector gives another vector, and taking the dot product of this result gives a scalar derived from the dyadic.