ITP: amp -- atomistic machine-learning potentials
retitle 790803 amp -- atomistic machine-learning potentials
owner 790803 ginggs@debian.org
thanks
Upstream have relaunched Neural as Amp.
* Package name : amp
Version : 0.3
Upstream Author : Andrew Peterson, Alireza Khorshidi
* URL : https://bitbucket.org/andrewpeterson/amp
* License : GPL-3.0+
Programming Lang: Python
Description : Atomistic Machine-learning Potentials
Amp is an open-source package designed to easily bring machine-learning
to atomistic calculations. This allows one to predict (or really,
interpolate) calculations on the potential energy surface, by first
building up a regression representation of a “train set” of atomic
images. Amp calculator works by first learning from any other calculator
(usually quantum mechanical calculations) that can provide energy and
forces as a function of atomic coordinates. In theory, these predictions
can take place with arbitrary accuracy approaching that of the original
calculator.
.
Amp is designed to integrate closely with the Atomic Simulation
Environment (ASE). As such, the interface is in pure python, although
several compute-heavy parts of the underlying codes also have fortran
versions to accelerate the calculations. The close integration with ASE
means that any calculator that works with ASE - including EMT, GPAW,
DACAPO, VASP, NWChem, and Gaussian - can easily be used as the parent
method.
I intend maintaining this package as part of the DebiChem team.
I found there was a packaged named amp in Debian circa 2000; the Audio
MPEG Player in non-free, but I don't believe this is a problem.
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