Hello,

I have a dataset with clear discrete heterogeneity giving three populations of particles. They are all the same complex, some complete, some with missing subunits, and were all easily sorted by heterogeneous refinement.

They all reached ~2 Å using particle images at the original pixel size (0.65 Å/pix), and given that there is still some margin until hitting the Nyquist limit, I tried to use RBMC. I made sure to run “Remove duplicates” on each particle set with default options, to avoid the error caused by duplicates in RBMC. Then I connected my three sets of particles to a single RBMC job but still got the “matrix is singular” error caused by duplicates, although not right away but at a much late stage (I think at the motion correction stage? not sure, and now I deleted this job so I can’t check).

My guess is that these duplicates are particles contributing to more than one reconstruction (with different weights), and I could probably fix it either by running the “Remove duplicates” jobs with stricter settings or by re-running heterogeneous refinement with “hard classification” on. I did not try this. Instead, I set up independent RBMC jobs for all three sets of particles (it was before the weekend, so I didn’t mind for that to take a long time).

Now I am a bit puzzled because two of the three sets of particles gave the same hyperparameters, but the third one differs:

```
Using hyperparameters:
Spatial prior strength: 4.6001e-03
Spatial correlation distance: 500
Acceleration prior strength: 6.4435e-02
Using hyperparameters:
Spatial prior strength: 5.4788e-03
Spatial correlation distance: 500
Acceleration prior strength: 1.4751e-02
Using hyperparameters:
Spatial prior strength: 4.6001e-03
Spatial correlation distance: 500
Acceleration prior strength: 6.4435e-02
```

With particles from the same set of micrographs, I would expect the search to converge to the same hyperparameters even with different subsets of particles and micrographs.

I will let the jobs complete and run homogeneous refinements on the outputs to see what happens. If anything looks suspicious, my first instinct would be to re-run RBMC on the middle set with hyperparameters from the two other sets.

So, my questions are:

- Is it suspicious to get different hyperparameters for one of the three sets of particles in this dataset?
- If so, what is the most reasonable thing to do about it?

Thank you!