# Derivative with respect to diagonal of diagonal matrix

Suppose I have a diagonal matrix $$\pmb{D}$$ and a symmetric matrix $$\pmb{X}$$ that is not a function of $$\pmb{D}$$, and I wish to find the following derivative: $$\frac{\partial}{\partial \mathrm{diag}(\pmb{D})} \mathrm{vec}\left(\pmb{D}\pmb{X}\pmb{D}\right),$$ in which $$\mathrm{diag}(\pmb{D})$$ represents the diagonal of $$\pmb{D}$$. I know the following derivative: $$\frac{\partial}{\partial \mathrm{vec}(\pmb{D})} \mathrm{vec}\left(\pmb{D}\pmb{X}\pmb{D}\right) = \left(\pmb{D}\pmb{X} \otimes \pmb{I} \right) + \left(\pmb{I} \otimes \pmb{X}\pmb{D}\right)$$ So I guess I can find the answer by multyplying this with $$\frac{\partial \mathrm{vec}\left( \pmb{D} \right)}{\partial \mathrm{diag}(\pmb{D})}$$, which should be some straightforward matrix with zeroes and ones. So my question is, (a) does this matrix have a name and can it easily be determined? and (b) isn't there some simpler way to do this?

Given an arbitrary matrix $$X$$ and a diagonal matrix $$\,A={\rm Diag}(a)$$
the product in question can be expanded as \eqalign{ P &= AXA \cr &= X\odot aa^T \cr {\rm vec}(P) &= {\rm vec}(X)\odot{\rm vec}(aa^T) \cr v_p &= v_x\odot(a\otimes a) \cr &= V_x\,(a\otimes a) \cr } where $$\odot$$ denotes the elementwise/Hadamard product
and $$\otimes$$ denotes the Kronecker product.
The differential and gradient of the vectorized product are \eqalign{ dv_p &= V_x\,(a\otimes da+da\otimes a) \cr &= V_x\,(a\otimes E+E\otimes a)\,da \cr \frac{\partial v_p}{\partial a} &= V_x\,(a\otimes E+E\otimes a) \cr &= {\rm Diag}\Big(v_x\Big)\,\big(a\otimes E+E\otimes a\big) \cr &= \Big(v_xe^T\Big)\odot\big(a\otimes E+E\otimes a\big) \cr &= \Big({\rm vec}(X)\,e^T\Big)\odot\big(a\otimes E+E\otimes a\big) \cr } where $$E$$ is the identity matrix and $$e$$ is the vector of all ones, i.e. $$\,E={\rm Diag}(e)$$
I found a solution, but will not accept this answer yet in case someone has an easier solution. My solution to find $$\frac{\partial \mathrm{vec}\left( \pmb{D} \right)}{\partial \mathrm{diag}(\pmb{D})}$$ was to reconize that for $$n \times n$$ diagonal matrix $$\pmb{D}$$: $$\pmb{D} = \sum_{i=1}^{n} \pmb{E}_i \delta_{ii},$$ with $$\pmb{E}_i$$ being an $$n \times n$$ matrix with a 1 on the $$i$$th diagonal and zeroes otherwise: $$e_{jk} = \begin{cases} 1 & \text{if } j = k = i \\ 0 & \text{otherwise} \end{cases}$$ The derivative can then be derived as: $$\frac{\partial \mathrm{vec}\left( \pmb{D} \right)}{\partial \mathrm{diag}(\pmb{D})} = \begin{bmatrix} \mathrm{vec}(\pmb{E}_1) & \mathrm{vec}(\pmb{E}_2) & \ldots & \mathrm{vec}(\pmb{E}_n) \end{bmatrix}$$ Denoting this result $$\pmb{E}^*$$ I obtain: $$\frac{\partial}{\partial \mathrm{diag}(\pmb{D})} \mathrm{vec}\left(\pmb{D}\pmb{X}\pmb{D}\right) = \left( \left(\pmb{D}\pmb{X} \otimes \pmb{I} \right) + \left(\pmb{I} \otimes \pmb{X}\pmb{D}\right) \right) \pmb{E}^*$$