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The symmetry may be broken if the function fails to have differentiable partial derivatives, which is possible if Clairaut's theorem is not satisfied (the second partial derivatives are not continuous). The function f(x, y), as shown in equation , does not have symmetric second derivatives at its origin.
Because the exterior derivative d has the property that d 2 = 0, it can be used as the differential (coboundary) to define de Rham cohomology on a manifold. The k -th de Rham cohomology (group) is the vector space of closed k -forms modulo the exact k -forms; as noted in the previous section, the Poincaré lemma states that these vector spaces ...
The second symmetric derivative is defined as [6] [2]: 1 (+) + (). If the (usual) second derivative exists, then the second symmetric derivative exists and is equal to it. [ 6 ] The second symmetric derivative may exist, however, even when the (ordinary) second derivative does not.
The second derivative of a function f can be used to determine the concavity of the graph of f. [2] A function whose second derivative is positive is said to be concave up (also referred to as convex), meaning that the tangent line near the point where it touches the function will lie below the graph of the function.
For example, consider the ordinary differential equation ′ = + The Euler method for solving this equation uses the finite difference quotient (+) ′ to approximate the differential equation by first substituting it for u'(x) then applying a little algebra (multiplying both sides by h, and then adding u(x) to both sides) to get (+) + (() +).
Mathieu's differential equations appear in a wide range of contexts in engineering, physics, and applied mathematics. Many of these applications fall into one of two general categories: 1) the analysis of partial differential equations in elliptic geometries, and 2) dynamical problems which involve forces that are periodic in either space or time.
Thus, the second partial derivative test indicates that f(x, y) has saddle points at (0, −1) and (1, −1) and has a local maximum at (,) since = <. At the remaining critical point (0, 0) the second derivative test is insufficient, and one must use higher order tests or other tools to determine the behavior of the function at this point.
The solver can also be used in a multi-host parallel mode on platforms that support MPI. Elmer's parallelisation capability is one of the strongest sides of this solver. Elmer's parallelisation capability is one of the strongest sides of this solver.