Cleaning up the README:

[ondrejkrejci]

I think that at least this part, should be put either to wiki or readthedocs to free the page a little bit.

ppafm simulation models and implementations

Since 2014 ppafm developed into the toolbox of various methodologies adjusted for a particular use case.

1. CPU version: - Original implementation using Python & C/C++.
   It can simulate a typical AFM experiment (3D stack of AFM images) in a matter of a few minutes.
   It is the base version for the development of new features and methodology.
   All available simulation models are implemented in this version, including:
   1. Point charge electrostatics + Lennard-Jones: Original fully classical implementation allows the user to set up calculation without any ab initio input by specifying atomic positions, types and (optionally) charges.
   2. Hartree-potential electrostatics + Lennard-Jones: Electrostatics is considerably improved by using Hartree potential from DFT calculation and using the Quadrupole model for CO-tip.
      We found this crucial to properly simulate polar molecules (e.g. H2O clusters, carboxylic acids, PTCDA) which exhibit strong electrostatic distortions of AFM images.
   3. Hartree-potential electrostatics + Density overlap: Further accuracy improvement is achieved when Pauli repulsion between electron shells of atoms is modelled by the overlap between electron density of tip and sample.
      This repulsive term replaces the repulsive part of Lennard-Jones while the attractive part (C6) remains.
      This modification considerably improves especially the simulation of molecules with electron pairs (-NH-, -OH, =O group), triple bonds and other strongly concentrated electrons.
2. GPU version: - Version specially designed for the generation of training data for machine learning.
   Implementation using pyOpenCL can parallelize the evaluation of forcefield and relaxation of probe-particle positions over hundreds or thousands of stream processors of the graphical accelerator.
   The further speed-up is achieved by using hardware-accelerated trilinear interpolation of 3D textures available in most GPUs.
   This allows simulating 10-100 AFM experiments per second on consumer-grade desktop GPU.
   GPU version is designed to work in collaboration with machine-learning software for AFM (https://github.com/SINGROUP/ASD-AFM) and use various generators of molecular geometry.
3. GUI @ GPU - The speed of GPU implementation enables interactive GUI where AFM images of molecules can be updated on the fly (<<0.1s) on a common laptop computer, while the user is editing molecular geometry or parameters of the tip.
   This provides an invaluable tool, especially for experimentalists trying to identify and interpret the structure and configuration of molecules in experiments on the fly while running the experiment.

Other branches

• master_backup is the old master branch that was recently significantly updated and named main.
  For users who miss the old master branch, we provided a backup copy.
  However, this version is very old and its use is discouraged.
• PhotonMap implements the latest developments concerning sub-molecular scanning probes combined with Raman spectroscopy (TERS) and fluorescent spectroscopy (LSTM).
• complex_tip is a modification of the Probe-Particle Model with 2 particles that allows a better fit to experimental results at the cost of additional fitting parameters.

[ondrejkrejci]

@ProkopHapala - we do not want to delete the information, just think that there is a different place for it. Do you agree? Thank you!

[ProkopHapala]

I don't have strong opinion on that. It is matter of taste. Since we wrote this in the paper, I don't feel much need to have it there anymore. Feel free to modify it.

Maybe it would make sense to put Fig.2 from the paper (https://ars.els-cdn.com/content/image/1-s2.0-S0010465524002649-gr002.jpg) on the frontpage as quick advertisement ?