  Uniform sampling from the set $\mathcal{G}(\mathbf{d})$ of graphs with a
given degree-sequence $\mathbf{d} = (d_1, \dots, d_n) \in \mathbb N^n$ is a
classical problem in the study of random graphs. We consider an analogue for
temporal graphs in which the edges are labeled with integer timestamps. The
input to this generation problem is a tuple $\mathbf{D} = (\mathbf{d}, T) \in
\mathbb N^n \times \mathbb N_{>0}$ and the task is to output a uniform random
sample from the set $\mathcal{G}(\mathbf{D})$ of temporal graphs with
degree-sequence $\mathbf{d}$ and timestamps in the interval $[1, T]$. By
allowing repeated edges with distinct timestamps, $\mathcal{G}(\mathbf{D})$ can
be non-empty even if $\mathcal{G}(\mathbf{d})$ is, and as a consequence,
existing algorithms are difficult to apply.
  We describe an algorithm for this generation problem which runs in expected
time $O(M)$ if $\Delta^{2+\epsilon} = O(M)$ for some constant $\epsilon > 0$
and $T - \Delta = \Omega(T)$ where $M = \sum_i d_i$ and $\Delta = \max_i d_i$.
Our algorithm applies the switching method of McKay and Wormald $[1]$ to
temporal graphs: we first generate a random temporal multigraph and then remove
self-loops and duplicated edges with switching operations which rewire the
edges in a degree-preserving manner.
