# Gradient operator of the log multivariate Gaussian density

I'm trying to analytically find the gradient the log a multivariate Gaussian density, which is given by

$$f(x_{1}, \dots, x_{p}) = f(\vec{x}) = \frac{1}{(2\pi)^{p/2}|\Sigma|^{1/2}} \exp \Bigg(-\frac{1}{2}(\vec{x} - \vec{\mu})^{T}\Sigma^{-1}(\vec{x} - \vec{\mu})\Bigg) \sim \mathcal{N}(\vec{\mu}, \Sigma)$$

where $$\vec{x}, \vec{\mu} \in \mathbb{R}^{p}$$, and $$\Sigma \in \mathbb{R}^{p \times p}$$.

I want to find the analytical expression for $$\nabla f$$, where $$\nabla$$ is the gradient operator defined as

$$\nabla f(\vec{x}) = \Bigg[ \frac{\partial f(\vec{x})}{\partial x_{1}}, \dots, \frac{\partial f(\vec{x})}{\partial x_{p}} \Bigg]$$

My vector calculus is very rusty and not sure how to take partial derivatives with respect to $$x_{1}, \dots, x_{p}$$.

Any help is much appreciated!

Hint:

The relevant part is $$\exp\left(\frac12 \sum_{i,j=1}^p (\Sigma^{-1})_{ij}(x_i-\mu_i)(x_j-\mu_j)\right)$$

so its $$k$$-th partial derivative is

$$\exp\left(\frac12 \sum_{i,j=1}^p (\Sigma^{-1})_{ij}(x_i-\mu_i)(x_j-\mu_j)\right) \cdot \frac\partial{\partial x_k}\left(\frac12 \sum_{i,j=1}^p (\Sigma^{-1})_{ij}(x_i-\mu_i)(x_j-\mu_j)\right) \\= \exp\left(\frac12 \sum_{i,j=1}^p (\Sigma^{-1})_{ij}(x_i-\mu_i)(x_j-\mu_j)\right)\cdot \frac12 \left(\sum_{i,j=1}^p (\Sigma^{-1})_{ij}\delta_{ik}(x_j-\mu_j) + \sum_{i,j=1}^p (\Sigma^{-1})_{ij}\delta_{jk}(x_i-\mu_i)\right)$$ Since $$\Sigma^{-1}$$ is symmetric, the two sums are equal so the final result is $$\exp\left(\frac12 \sum_{i,j=1}^p (\Sigma^{-1})_{ij}(x_i-\mu_i)(x_j-\mu_j)\right) \cdot\left(\sum_{i=1}^p (\Sigma^{-1})_{ik}(x_i-\mu_i)\right)$$