# How to think of gradient of a vector?

I have this introductory problem:

$$\nabla_x \boldsymbol{a}^T \boldsymbol{x} = \boldsymbol{a}$$

$$\boldsymbol{a}$$ and $$\boldsymbol{x}$$ are vectors.

There are several things that were confusing to me in this exercise. First, I had trouble understanding the notation $$\nabla_x$$ i.e. what is gradient with superscript $$x$$ supposed to mean but according to this answer it is a vector of variables with respect to which you calculate the partial derivatives. Second thing is the presence of the right hand side of the equation - at first I thought it's like solving an unknown in e.g. $$5+4x=16$$. But now I'm convinced the RHS is just the answer I'm supposed to get by evaluating LHS.

I still don't how I should think about the question asking me to calculate gradient of what evaluates to be a vector - according to the Gradient wikipedia page you calculate gradient of a function, not a vector like here. Does it have some special meaning?

Edit: I just realized the matrix resulting from $$\boldsymbol{a}^T \boldsymbol{x}$$ is a 1x1 matrix, so if I treat it as just an expression it makes more sense.

• Intuitively, the meaning of the gradient vector at any point $x$ is that it points in the direction in the input space that the function will grow fastest from the point $x$. Commented Mar 7, 2019 at 13:38

Let $$\boldsymbol a=(a,b,c)$$, so that $$\boldsymbol a^T\boldsymbol x=ax+by+cz$$.
$$\nabla_{\boldsymbol x}(\boldsymbol a^T\boldsymbol x)=\left(\frac{\partial}{\partial x}(ax+by+cz),\frac{\partial}{\partial y}(ax+by+cz),\frac{\partial}{\partial z}(ax+by+cz)\right)=(a,b,c).$$
The locus of points such that $$ax+by+cz=d$$ where $$d$$ is some constant (i.e. an iso-surface), is a plane. The gradient is a vector normal to this plane. More generally, the gradient of a scalar function is a vector orthogonal to the iso-surfaces.