**Edit:** I simplified the example to a canonical case for clarity.

Given an integral $\int_{\Omega}{g(\mathbf{x})}$ with a well-posed integrand $g(\mathbf{x})$ defined on some multidimensional space $\Omega$, one can integrate it successfully with a Markov Chain Monte Carlo method, in particular using Metropolis-Hastings method. Detailed balance and ergodicity are achieved with any well-posed (samplable) integrand. Transition kernel $K(\dot{},\dot{})$ is Harris recurrent and its transition probability is known for every pair $(\mathbf{x},\mathbf{y})$. The value of the desired integral is always finite, even in presence of delta distributions in the integrand. This is given.

In the case of interest, the integrand is of a form $f(\mathbf{x})=\delta_{\mathbf{x}_0}(\mathbf{x})\dot{} g(\mathbf{x}) + h(\mathbf{x})$ and consists of a delta distribution at some unknown location $\mathbf{x}_0\in \Omega$ and some regular (well-posed) non-zero functions $g(\mathbf{x})$ and $h(\mathbf{x})$. This delta distribution cannot be sampled explicitly or using numerical optimization (given). This makes such an integrand unsamplable with random walk. 

I mollify (approximate to the identity) this delta distribution using some [mollifier][1] (normalized smooth function $\phi_\epsilon(\mathbf{x})=\epsilon^{-1}\phi\left(\frac{\mathbf{x}}{\epsilon}\right)$ with some bandwidth $\epsilon$). This leads to a tempered integrand $f_\epsilon(\mathbf{x})=\phi_\epsilon(\mathbf{x}-\mathbf{x}_0)\dot{} g(\mathbf{x})+h(\mathbf{x})$. During the integration, at every step $n$, I gradually shrink the parameter $\epsilon_n$ to zero in order to achieve $f_{\epsilon_n} \to f$ as $n \to \infty$ in spirit of serial tempering and simulated annealing. 

One cannot use parallel or serial tempering here, as the probability of the proposal to descend from a tempered mixture to the original integrand $f$ at the exact location $\mathbf{x}_0$ of the delta distribution is zero.

Thus I have two rather similar questions: 

 1. Would the integral converge to the proper value $g(\mathbf{x_0})+\int_{\Omega}{h(\mathbf{x})}$ with such scheme? 
 2. What are the conditions for the asymptotic decrease rate of the sequence $\epsilon_n$ that guarantees the consistency of the MCMC integration? In other words, the rate that allows the integral to converge before parts of the integrand $f_{\epsilon_n}$ become unsamplable?


  [1]: http://en.wikipedia.org/wiki/Mollifier