 Orthogonal-mixture Metropolis proposal

For a proposal $Y=AX+Z$, with isotropic $Z\sim N(0,I)$ and an independent random orthogonal matrix $A$, invariance of the distribution of $A$ under transpose makes the proposal distribution symmetric. Indeed $|y-Ax|=|x-A^{T}y|$, and averaging the isotropic Gaussian density over an inversion-invariant law yields $q(x,y)=q(y,x)$. The Metropolis–Hastings algorithm therefore accepts with the target density ratio alone.