Meri Leeworthy

Gradient functions

The gradient function and vector fields are closely related concepts in vector calculus, with the gradient being a specific type of vector field.

Gradient Function

The gradient of a scalar function $f(x, y, z)$ is a vector field that points in the direction of the greatest rate of increase of the function. The gradient of $f$ is denoted by $\nabla f$ and is defined as:

$$ \nabla f = \left( \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y}, \frac{\partial f}{\partial z} \right) $$

Relation to Vector Fields

Example

Consider a scalar function $f(x, y) = x^2 + y^2$. The gradient of $f$ is:

$$ \nabla f = \left( \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y} \right) = \left( 2x, 2y \right) $$

The vector field $\mathbf{F}(x, y) = (2x, 2y)$ is the gradient of $f(x, y)$, and therefore, $\mathbf{F}$ is a conservative vector field with $f$ as its potential function.

Physical Interpretation

Summary

I live and work on the land of the Wurundjeri people of the Kulin Nation. I pay respect to their elders past and present and acknowledge that sovereignty was never ceded. Always was, always will be Aboriginal land.

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