Is there a method in Gensim to find the most relevant topics between two corpuses?
There's no one method for doing this in Gensim. But once you've trained a topic-model (such as LDA) on the combined corpus of all documents, you could do things like:

compare any two documents, by comparing their topics
tally top-N topics for all documents in one of the original corpuses, and then top-N topics for all documents the 2nd original corpus, then contrast those counts
treat the original two corpuses as two giant composite documents, calculate the topics of those two synthetic documents, and compare their topics
I am trying to better understand how two groups of documents relate to one another through topic modeling. I have performed similarity scoring on them and would like to try and peer deeper into how these documents relate through topic modeling. Rather than just observing the most relevant topics for each document using LDA, is there a method where I could have a model trained on both documents combined as a single corpus and visualize what topics have the most relevance to both documents combined?
I tried just running LDA on a combined corpus but it returned topics that were clearly divided in relevance between the two different underlying documents of origin. Instead, I want to see what smaller topics the two documents overlap with the most.