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View Code? Open in Web Editor NEWLearning free energy landscapes using artificial neural networks
License: MIT License
Learning free energy landscapes using artificial neural networks
License: MIT License
Dear Hsidky,
ANN method looks having faster convergence to obtain the free energy surface. I have the problem using the ANN combined with the newly developed CVs in the LAMMPS, presented in the following (or in the website SSAGESproject/SSAGES#34). Moreover, how can I use ANN or SSAGES in the CP2K to calculate the free energy? Thank you very much.
The following is the content of a JSON file used in ANN:
{
"walkers" : 1,
"input" : "in.metal",
"CVs": [
{
"qatom": false,
"qvmean": true,
"short_cutoff": 2.6,
"long_cutoff": 3.8,
"q_dimension": 6,
"type": "Q_Steinhardt"
},
{
"short_cutoff": 2.6,
"long_cutoff": 3.8,
"type": "Rpp"
}
],
"methods" : [
{
"type" : "ANN",
"topology" : [30, 20],
"nsweep" : 10000,
"overwrite_output" : false,
"temperature" : 1300,
"grid" : {
"lower" : [0, -1.0],
"upper" : [1.1, 1.1],
"number_points" : [50, 50],
"periodic" : [false, false]
},
"lower_bounds" : [-0.1, -1.1],
"upper_bounds" : [1.2, 1.2],
"lower_bound_restraints" : [0, 0],
"upper_bound_restraints" : [0, 0],
"max_iters" : 10,
"weight" : 15.0 // Is the unit like the lammps one, eV herein? I also use the default value and it does not work.
}
]
}
Using two newly designed CVs, the metadynamics simulations are fine, where the system can traverse the distinguished states I concerned. However, the system only locate at the initial state as I use the ANN method. It means that the bias force is not added to the atoms. As I know, ANN also need add the bias force to the atoms like metadynamics. What is the wrong I meet?
The two CVs should consider the whole atoms as well as its neighbor atoms. In the corresponding XXCV.cpp, I have given the val_ value and its devirative on x (or y, z), grad_[].
The following is a JSON file used in the metadynamics simulations (It works fine):
{
"walkers" : 1,
"input" : "in.metal",
"CVs": [
{
"qatom": false,
"qvmean": true,
"short_cutoff": 2.6,
"long_cutoff": 3.8,
"q_dimension": 6,
"type": "Q_Steinhardt"
},
{
"short_cutoff": 2.6,
"long_cutoff": 3.8,
"type": "Rpp"
}
],
"methods" : [
{
"type" : "Metadynamics",
"widths" : [
0.02, 0.04
],
"height" : 0.103408,
"lower_bounds" : [0, -1.0],
"upper_bounds" : [1.1, 1.1],
"lower_bound_restraints" : [0, 0],
"upper_bound_restraints" : [0, 0],
"hill_frequency" : 500
}
]
}
Thanks! Looking forward to your reply.
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