ghutchis

The BOSS tool from Turku / Aalto goes for that approach. A few of their papers discuss pushing the acquistion function to explore more over time.

We split into two potential tasks:

• finding the global minima quickly (e.g., crucial for some of my group’s oligomer / foldamer work)
• adding the ensemble by exploring the low-energy PES from step 1.

In particular, we want to make sure Task 1 scales well to larger molecules. Right now, it’s hard to be sure you have a good minima for oligomers / polymers (e.g., CREST seems to struggle to find a helix with alanine oligomers).

Our previous Bayesian optimization work struggled with more torsions (e.g., it did great up to about 8 dihedrals) and we’re now tackling 35+ fairly well.

I can’t (yet) guarantee we get the full ensemble - because we wanted to make sure we got the right minima first.

Here’s my proposal about a simple visibility syntax:

"Solvent": {
  "type": "stringList",
  "values": ["Water", "Acetonitrile", "Benzene", "..."],
  "visibleWhen": { "key": "Solvation Model", "notEquals": "None" }
},
"UV States": {
  "type": "integer",
  "enabledWhen": { "key": "Calculation Type", "in": ["TD-DFT", "EOM-CCSD"] }
}

• Two properties: visibleWhen, enabledWhen
• Operators: equals, notEquals, in, notIn, greaterThan, lessThan. (isChecked is just equals: true.)

I think that handles a large number of cases (e.g., hiding or disabling parts of an input generator)