Hello,
Sorry if this is not the correct place for this question, but I'm working on implementing Vendi Sampling on LAMMPS (and hopefully GROMACS too), from a prototype Python implementation.
The basic idea is that in a multi-replica simulation, the atomic positions in the replicas are inspected, evaluated for "diversity" (w.r.t centered/rotated reference positions), and go through an algorithm that gives us a scalar value called the "Vendi Score", the collective potential energy of the ensemble.
I'm trying to understand how to approach this from a development perspective. My understanding so far on reading on LAMMPS and the Colvars module is, that a suitable plan for development might be:
Implement a new analysis method (say vendi_sampling), a class that is a child of colvarbias, much along the lines of metadynamics, with file-based communication between replicas, and something that outputs energy in its calc_energy method. (calc_forces cannot, and need not return anything meaningful since we do not have derivatives of energy w.r.t. the atomic positions).
The resulting colvar configuration might look something like this:
colvarsTrajFrequency 5
colvar {
name atom_positions
cartesian {
name xyz
atoms {
name ala
atomNumbersRange 1-22
centerToReference on
rotateToReference on
refPositionsFile alanine-dipeptide-implicit.xyz
}
}
}
vendi_sampling {
name vendi
colvars atom_positions
multipleReplicas on
replicaUpdateFrequency 1
replicasRegistry vendi-replicas.txt
outputEnergy on
}
Use this colvar configuration as a fix in LAMMPS and use the fix_modify command to run the simulation. The documentation on fix_modify states:
The fix_modify energy option is supported by this fix to add the energy change from the biasing force added by Colvars to the global potential energy of the system as part of thermodynamic output
So this might look something like:
fix myfix all colvars my.colvars
fix_modify myfix energy yes
minimize 0.001 0.001 1000 1000
I'm a software engineer with no background in MD before this, so I'm wondering if someone can review this general plan and see if makes sense? Or perhaps there's a simpler way?
Hello, Sorry if this is not the correct place for this question, but I'm working on implementing Vendi Sampling on LAMMPS (and hopefully GROMACS too), from a prototype Python implementation.
The basic idea is that in a multi-replica simulation, the atomic positions in the replicas are inspected, evaluated for "diversity" (w.r.t centered/rotated reference positions), and go through an algorithm that gives us a scalar value called the "Vendi Score", the collective potential energy of the ensemble.
I'm trying to understand how to approach this from a development perspective. My understanding so far on reading on LAMMPS and the Colvars module is, that a suitable plan for development might be:
vendi_sampling), a class that is a child ofcolvarbias, much along the lines ofmetadynamics, with file-based communication between replicas, and something that outputs energy in itscalc_energymethod. (calc_forcescannot, and need not return anything meaningful since we do not have derivatives of energy w.r.t. the atomic positions).The resulting colvar configuration might look something like this:
fix_modifycommand to run the simulation. The documentation onfix_modifystates:So this might look something like:
I'm a software engineer with no background in MD before this, so I'm wondering if someone can review this general plan and see if makes sense? Or perhaps there's a simpler way?