Make the v3 topic modeling workflow backend-agnostic and add tomotopy support

[sldyns]

Summary

This PR refactors the current pycistopic_v3 topic-modeling workflow so that v3 artifacts are backend-agnostic instead of being tied to Mallet-specific readers and filenames, and adds a tomotopy LDA backend that writes the same artifact bundle.

What changed

• add a shared topic-model abstraction in topic_models.py
• add TopicModelFilenames to centralize the v3 artifact layout
• add backend resolution from the saved parameters file via load_topic_model_backend
• add LDATomotopy to train directly from the binary accessibility matrix and write the standard v3 outputs
• refactor LDAMallet to implement the same backend interface and emit the same artifact bundle
• update the topic_modeling CLI to use a shared run entry point with --backend {mallet,tomotopy}
• keep corpus creation as a Mallet-specific step, while allowing tomotopy to run directly from the matrix plus barcode/region inputs
• update create_anndata, model-stat calculation, plotting, and topic binarization to load outputs through the backend abstraction instead of assuming Mallet-only artifacts
• update log-likelihood/stat handling so backend-specific hyperparameters are interpreted correctly, including learned alpha values from tomotopy
• add tomotopy>=0.14.0 as a dependency