Isolated molecule with MACE-POLAR-1 model

[qinghualiao]

Hello,

I am trying to train a small MACE-POLAR model, and I got some questions.

1. The data set OMol25 that used for the training MACE-POLAR-1 was obtained at the level wB97M-V/def2-TZVPPD. From what my understanding, the molecules in OMol25 are also isolated molecules. I am wondering how the long-range electrostatic interactions were trained in the model, practically. Only real-space summation was used by setting --kspace_cutoff_factor=0.001? In this case, it is like an advanced local model?
2. If my understanding is correct, what if I use MACE-POLAE-1 under a framework of ML/MM in a periodic boundary condition? How will the long-range electrostatic interactions in the ML region be computed? Or how to carefully deal with it, so that long-range interactions in the ML region won't be double accounted?
3. In the framework of ML/MM, the MACE-POLAR-1 of the ML region can naturally "feel" the MM region, right? The MM region put an external electric field over the ML region?
4. In my case, my molecules are isolated, during training, without --kspace_cutoff_factor=0.001, the training on a H100 crashed every time due to out of memory, but it worked with --kspace_cutoff_factor=0.001. However, even with --kspace_cutoff_factor=0.001, I could not train it with MACE-POLAE-1-M.model as a foundational model, it leads to crash due to out of memory. Is this normal? How can I use it as a foundational model?

I would really appreciate your comments! Thank you!

All the best,
Qinghua

[ilyes319]

Hey @qinghualiao sorry for the delay in my answer,

1. In case of isolated molecules, we used the real space implementation of the electrostatics interaction, and not the ewald. We just compute directly the coulomb energy and potential using erf and sums over the atoms. The details are including in the SI of the paper name: V.5Real Space Electrostatic Energy Computation. In particular, we use a finite different trick for computing the real space dipole dipole coulomb interaction.

2. Using the model in ML/MM is an active area of development for us. One needs to be careful because the model is a polarisable force field such that the MM charges do affect the ML charges in non trivial ways beyond just the final electrostatic energy. One should give the full electrostatic potential of the MM region to MACE and then let it compute the polarisation + the coulomb energy. Atm the biggest restriction for that is we do not have a good pme implementation that would let us scale that to thousands of atoms for biological applications. Once we have that, then it should be possible. One extra details is that the partitioning of the dispersion interactions between the ML and MM region is not necessarily trivial. The model learns a non-local energy that contains some of the dispersion interactions too, such that one will probably have to do some careful calibration in order to understand how to partition the dispersion in the ML and MM region.

3. If you want to train on just isolated atoms, you need to use the real space implementation and not the kspace. If you have no pbc for your isolated molecule (put PBC = false in you extxyz) then it would do the realspace. Note that kspace factor is very small! Here is what we use in polar-1:

            --device=cuda \
            --kspace_cutoff_factor=1.0 \
            --atomic_multipoles_max_l=1 \
            --atomic_multipoles_smearing_width=1.5 \
            --field_norm_factor=1.0 \
            --field_feature_widths="[1.5, 3.0]" \
            --field_feature_norms="[20.0, 20.0, 0.5, 0.5]" \
            --field_feature_max_l=1 \
            --default_dtype="float32" \
            --restart_latest \
            --weight_decay=1e-8 \
            --save_cpu \
            --include_local_electron_energy \
            --include_electrostatic_self_interaction \

Going to float32 might help too.

[Qinghua-Liao]

Hello Ilyes @ilyes319 ,

Thanks very much for your detailed explanation! I later also figured it out, and understand it.
We will be careful with using the MACE-polar model in ML/MM.

I also found the option --kspace_cutoff_factor, for a test, I used 0.001 for it, as a way to turn off kspace, so only real space is account.

You mentioned you used "--kspace_cutoff_factor=1.0" for MACE-polar-1, the training data is from OMol25, which I think are molecules without PBC. So how to set "--kspace_cutoff_factor" to turn off kspace?

Thanks a lot!

All the best,
Qinghua