  We consider one-dimensional discrete-time random walks (RWs) in the presence
of finite size traps of length $\ell$ over which the RWs can jump. We study the
survival probability of such RWs when the traps are periodically distributed
and separated by a distance $L$. We obtain exact results for the mean
first-passage time and the survival probability in the special case of a
double-sided exponential jump distribution. While such RWs typically survive
longer than if they could not leap over traps, their survival probability still
decreases exponentially with the number of steps. The decay rate of the
survival probability depends in a non-trivial way on the trap length $\ell$ and
exhibits an interesting regime when $\ell\rightarrow 0$ as it tends to the
ratio $\ell/L$, which is reminiscent of strongly chaotic deterministic systems.
We generalize our model to continuous-time RWs, where we introduce a power-law
distributed waiting time before each jump. In this case, we find that the
survival probability decays algebraically with an exponent that is independent
of the trap length. Finally, we derive the diffusive limit of our model and
show that, depending on the chosen scaling, we obtain either diffusion with
uniform absorption, or diffusion with periodically distributed point absorbers.
