Thanks for your questions. I was indeed a bit unspecific. I am coding in Python and use this UMAP implementation: https://umap-learn.readthedocs.io/en/latest/api.html UMAP instances have a parameter "random_state" and the documentation says the following: "If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by np.random." I provided an integer, so I am guessing UMAP uses the random number generator of the numpy version in my virtual env. This would be PCG64 (https://numpy.org/doc/2.1/reference/random/generator.html#numpy.random.default_rng). The old random number generator of RandomState instances uses the Mersenne Twister algorithm MT19937 (https://numpy.org/doc/2.1/reference/random/legacy.html#numpy.random.RandomState). From the documentation it is not entirely clear to me what UMAP means by "seed used by the random number generator". But in any case numpy says that "our RNGs are deterministic sequences and can be reproduced by specifying a seed integer to derive its initial state." I looked up the history of changes in my virtual env (just to double check) and I don't see any changes in packages that should influence random number generation like numpy or numba. I had issues with reproducibility in the past, but this was across OS (Linux vs. Mac with the same virtual env) and not on the same computer with the same OS (but different versions of that OS). Thanks a lot for your help!