Dear All,

On Fri, Nov 20, 2015 at 5:17 AM, Graham Inggs <> wrote:
> retitle 790803 amp -- atomistic machine-learning potentials
> owner 790803
> thanks
> Upstream have relaunched Neural as Amp.
> * Package name    : amp
>   Version         : 0.3
>   Upstream Author : Andrew Peterson, Alireza Khorshidi
> * URL             :
> * 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.

I am interested in participating in the packaging of amp. I recently
joined Prof. Peterson's group as postdoctoral research associate at
Brown, and thus I will be involved in amp (use/development). I would
be glad if you let me know how I can help you with.

Muammar El Khatib.
Linux user: 403107.
GPG Key = 71246E4A. |
 : :' :
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