[step:Verify that the Metropolis-adjusted transition kernel is well defined]
Since $\pi: \mathbb{R}^d \to (0,\infty)$ is $C^1$ and strictly positive, the function $\log \pi: \mathbb{R}^d \to \mathbb{R}$ is $C^1$, and its gradient $\nabla\log\pi: \mathbb{R}^d \to \mathbb{R}^d$ is continuous. Hence $q_h: \mathbb{R}^d \times \mathbb{R}^d \to (0,\infty)$ is continuous, so it is Borel measurable.
For fixed $x \in \mathbb{R}^d$, the map $q_h(x,\cdot): \mathbb{R}^d \to (0,\infty)$ is the Gaussian density with mean $x+\frac{h}{2}\nabla\log\pi(x)$ and covariance matrix $hI_d$. Therefore
\begin{align*}
\int_{\mathbb{R}^d} q_h(x,y)\,d\mathcal{L}^d(y) = 1.
\end{align*}
The ratio
\begin{align*}
(x,y) \mapsto \frac{\pi(y)q_h(y,x)}{\pi(x)q_h(x,y)}
\end{align*}
is positive and continuous, so $\alpha$ is Borel measurable and satisfies $0 < \alpha(x,y) \leq 1$ for all $x,y \in \mathbb{R}^d$.
The rejection probability $r: \mathbb{R}^d \to [0,1]$ is defined in the theorem statement by
\begin{align*}
r(x) := 1-\int_{\mathbb{R}^d}q_h(x,z)\alpha(x,z)\,d\mathcal{L}^d(z).
\end{align*}
Since $0 \leq \alpha(x,z) \leq 1$ and $q_h(x,\cdot)$ integrates to $1$, we have $0 \leq r(x) \leq 1$. The function $r$ is Borel measurable by the standard parameterized-integral measurability lemma for nonnegative Borel functions, proved by first checking indicators of Borel rectangles and then using the [monotone class theorem](/theorems/4925) together with Tonelli's theorem.
Thus, for every $x \in \mathbb{R}^d$, the formula
\begin{align*}
K(x,A) = \int_A q_h(x,y)\alpha(x,y)\,d\mathcal{L}^d(y) + r(x)\delta_x(A)
\end{align*}
defines a probability measure on the Borel subsets of $\mathbb{R}^d$. Conversely, for every Borel set $A \subset \mathbb{R}^d$, the map $x \mapsto \int_A q_h(x,y)\alpha(x,y)\,d\mathcal{L}^d(y)$ is Borel measurable by the same monotone-class and Tonelli parameterized-integral argument, and $x \mapsto \delta_x(A)=\mathbb{1}_A(x)$ is Borel measurable, where $\mathbb{1}_A: \mathbb{R}^d \to \{0,1\}$ denotes the indicator function of $A$. Hence $x \mapsto K(x,A)$ is Borel measurable, so $K$ is a Markov transition kernel.
[/step]