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valid for any vector fields X and Y and any tensor field T.. Considering vector fields as infinitesimal generators of flows (i.e. one-dimensional groups of diffeomorphisms) on M, the Lie derivative is the differential of the representation of the diffeomorphism group on tensor fields, analogous to Lie algebra representations as infinitesimal representations associated to group representation ...
It can be thought of as the rate of change of the function in the -direction.. Sometimes, for = (,, …), the partial derivative of with respect to is denoted as . Since a partial derivative generally has the same arguments as the original function, its functional dependence is sometimes explicitly signified by the notation, such as in:
In mathematics, matrix calculus is a specialized notation for doing multivariable calculus, especially over spaces of matrices.It collects the various partial derivatives of a single function with respect to many variables, and/or of a multivariate function with respect to a single variable, into vectors and matrices that can be treated as single entities.
Suppose that a function represents the position of an object at the time. The first derivative of that function is the velocity of an object with respect to time, the second derivative of the function is the acceleration of an object with respect to time, [29] and the third derivative is the jerk. [36]
Let x(t) and y(t) be the coordinates of the points of the curve expressed as functions of a variable t: = (), = (). The first derivative implied by these parametric equations is = / / = ˙ ˙ (), where the notation ˙ denotes the derivative of x with respect to t.
The directional derivative of a scalar function f with respect to a vector v at a point (e.g., position) x may be denoted by any of the following: = ′ = = () = = = (). It therefore generalizes the notion of a partial derivative , in which the rate of change is taken along one of the curvilinear coordinate curves , all other coordinates being ...
the partial differential of y with respect to any one of the variables x 1 is the principal part of the change in y resulting from a change dx 1 in that one variable. The partial differential is therefore involving the partial derivative of y with respect to x 1.
The partial derivative of f with respect to x does not give the true rate of change of f with respect to changing x because changing x necessarily changes y. However, the chain rule for the total derivative takes such dependencies into account. Write () = (, ()). Then, the chain rule says