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  2. Symmetry in quantum mechanics - Wikipedia

    en.wikipedia.org/wiki/Symmetry_in_quantum_mechanics

    In quantum electrodynamics, the local symmetry group is U(1) and is abelian. In quantum chromodynamics, the local symmetry group is SU(3) and is non-abelian. The electromagnetic interaction is mediated by photons, which have no electric charge. The electromagnetic tensor has an electromagnetic four-potential field possessing gauge symmetry.

  3. Fermi–Dirac statistics - Wikipedia

    en.wikipedia.org/wiki/Fermi–Dirac_statistics

    In the case of a spectral gap, such as for electrons in a semiconductor, the point of symmetry μ is typically called the Fermi level or—for electrons—the electrochemical potential, and will be located in the middle of the gap. [13] [14]

  4. Cubic function - Wikipedia

    en.wikipedia.org/wiki/Cubic_function

    The points P 1, P 2, and P 3 (in blue) are collinear and belong to the graph of x 3 + ⁠ 3 / 2 ⁠ x 2 − ⁠ 5 / 2 ⁠ x + ⁠ 5 / 4 ⁠. The points T 1, T 2, and T 3 (in red) are the intersections of the (dotted) tangent lines to the graph at these points with the graph itself. They are collinear too.

  5. Gradient - Wikipedia

    en.wikipedia.org/wiki/Gradient

    The gradient of H at a point is a plane vector pointing in the direction of the steepest slope or grade at that point. The steepness of the slope at that point is given by the magnitude of the gradient vector. The gradient can also be used to measure how a scalar field changes in other directions, rather than just the direction of greatest ...

  6. Gradient theorem - Wikipedia

    en.wikipedia.org/wiki/Gradient_theorem

    The gradient theorem states that if the vector field F is the gradient of some scalar-valued function (i.e., if F is conservative), then F is a path-independent vector field (i.e., the integral of F over some piecewise-differentiable curve is dependent only on end points). This theorem has a powerful converse:

  7. Hessian matrix - Wikipedia

    en.wikipedia.org/wiki/Hessian_matrix

    Refining this property allows us to test whether a critical point is a local maximum, local minimum, or a saddle point, as follows: If the Hessian is positive-definite at x , {\displaystyle x,} then f {\displaystyle f} attains an isolated local minimum at x . {\displaystyle x.}

  8. Gradient pattern analysis - Wikipedia

    en.wikipedia.org/wiki/Gradient_pattern_analysis

    Gradient pattern analysis (GPA) [1] is a geometric computing method for characterizing geometrical bilateral symmetry breaking of an ensemble of symmetric vectors regularly distributed in a square lattice. Usually, the lattice of vectors represent the first-order gradient of a scalar field, here an M x M square amplitude matrix.

  9. Conical intersection - Wikipedia

    en.wikipedia.org/wiki/Conical_intersection

    An accidental same-symmetry conical intersection is an intersection between two electronic states that carry the same point group symmetry. While this type of intersection was traditionally more difficult to locate, a number of efficient searching algorithms and methods to compute non-adiabatic couplings have emerged in the past decade.