I'm interested in finding the Legendre transform of the following function $$ f(x) = - \log(\langle a,x\rangle) $$ where $a$ and $x$ are both $n$-dimensional (column) vectors. The values of $x$ and $a$ are such that the inner product is always positive
I wish to find the Legendre transform of $f(x)$. My attempt is below $$ \langle p,x\rangle - f(x) = \langle p,x\rangle + \log(\langle a,x\rangle) $$ The gradient is given as $$ \frac{d}{dx} = p + \frac{a}{\langle a,x\rangle} $$ And the hessian is $$ \frac{d^2}{dxdx^{T}} = -\frac{aa^{T}}{\langle a,x\rangle^2} $$ (I think). This hessian is negative, which means the fixed point we find is a maximum - all good so far.
From here I would be like to be able to write something like the following $$ f^{\ast}(p) = -\log(\langle a,x^{\ast}\rangle) $$ where $x^{\ast} = g(p)$, which I find by inverting that first derivative (when it is at a minimum). However, I don't know how to do this. $$ \frac{a}{p} = a^{T}x $$ The thinking here is to somehow invert $a$, but in general one can't invert vectors in matrix multiplication, since inverses only exist for square matrices. What, then, should I do to attack this problem?
The other classic way to solve this problems is to invert the gradient of the function, i.e., to find the following function $$ (\frac{d}{dx}f)^{-1}(p) $$ but since this gradient ($\nabla f$) is again a vector (of partial derivatives), I am again stuck on how to proceed