Do xgboost and random forests in general handle multiple splits of the same numeric feature in a single branch?
Yes, it can handle multiple splits withing the same branch.
A decision tree model can use the same feature as many times as optimally needed.
You can see an example in the sklearn doc.
The petal-length feature is used multiple times in the same branch.