This article explains the user-visible changes in Kwant 0.2. Kwant 0.2 was released on 29 November 2012.

This has been the main focus of this release. Through optimization a level of performance has been reached that we consider satisfactory: runs of Kwant for mid-sized (100x100 say) systems now typically spend most time in highly optimized libraries and not anymore in Python-implemented code. For large, truly performance-critical systems almost all time is now spent in optimized libraries.

An important optimization has been replacing NumPy for most uses within Kwant by tinyarray. tinyarray provides a subset of NumPy’s functionality in a way that is highly optimized for small arrays such as the tags of sites in Kwant.

The code for sparse matrix solvers has been reorganized and a new solver has
been added next to *kwant.solvers.sparse*: `kwant.solvers.mumps`

. The new
solver uses the MUMPS software package and
is much (typically several times) faster than the UMFPACK-based old solver.
In addition, MUMPS uses considerably less memory for a given system while at
the same time it is able to take advantage of more than 2 GiB of RAM.

`plotter`

module¶`plotter`

has been rewritten using matplotlib, which allows
plot post-processing, basic 3D plotting and many other features. Due to the
possibility to easily modify a matplotlib plot after it has been generated,
function `plot`

has much fewer input parameters, and is less
flexible than its previous implementation. Its interface is also much more
similar to that of matplotlib. For the detailed interface and input
description check `plot`

documentation.

The behavior of `plot`

with low level systems has changed.
Arguments of plot which are functions are given site numbers in place of
`Site`

objects when plotting a low level system. This
provides an easy way to make the appearance of lines and symbols depend on
computation results.

A new function `map`

was implemented. It allows to show a map of
spatial dependence of a function of a system site (e.g. density of states)
without showing the sites themselves.

`TranslationalSymmetry`

is used differently¶When constructing an instance of `TranslationalSymmetry`

a sole
parameter used to be expected: A sequence of sequences of 1d real space
vectors. Now `TranslationalSymmetry`

can take an arbitrary number of
parameters, each of them a 1d real space vector. This reduced the number of
parantheses necessary in the common case where there is just a single parameter

Example of old usage:

```
sym = kwant.TranslationalSymmetry([(-1, 0)])
```

New usage:

```
sym = kwant.TranslationalSymmetry((-1, 0))
```

The functionality that used to be provided by the method `energies`

of
`kwant.system.InfiniteSystem`

has been moved to the `kwant.physics`

package.
See the documentation of `kwant.physics.Bands`

and
Beyond transport: Band structure and closed systems.

The new function of sparse solvers `ldos`

allows the calculation of the local density of states.

(Kwant 0.3 update: `wave_func`

has been renamed to
`wave_function`

.)

The new function of sparse solvers `wave_func`

allows the calculation of the
wave function in the scattering region due to any mode of any lead.

The function *solve* of sparse solvers now
always returns a single instance of `BlockResult`

. The
latter has been generalized to include more information for leads defined as
infinite systems.