2.11. Frequently asked questions

This FAQ complements the regular Kwant tutorials and thus does not cover questions that are discussed there. The Kwant paper also digs deeper into Kwant’s structure.

What is a system, and what is a builder?

A Kwant system represents a particular tight-binding model. It contains a graph whose edges and vertices are assigned values, and that corresponds to the Hamiltonian matrix of the model being simulated.

In Kwant the creation of the system is separated from its use in numerical calculations. First an instance of the Builder class is used to construct the model, then the finalize method is called, which produces a so-called low-level System that can be used by Kwant’s solvers.

The interface of builders mimics Python mappings (e.g. dictionaries). The familiar square-bracket syntax allows to set, get and delete items that correspond to elements of the system graph, e.g. syst[key] = value. An item consists of a key and an associated value. Keys are sites and hoppings. Values can be numbers, arrays of numbers, or functions that return numbers or arrays.

Finalizing a builder returns a copy of the system with the graph structure frozen. (This can be equivalently seen as freezing the system geometry or the sparsity structure of the Hamiltonian.) The associated values are taken over verbatim. Note that finalizing does not freeze the Hamiltonian matrix: only its structure is fixed, values that are functions may depend on an arbitrary number of parameters.

In the documentation and in mailing list discussions, the general term “system” can refer either to a Builder or to a low-level System, and the context will determine which specific class is being referred to. The terms “builder” and “low-level system” (or “finalized system”) refer respectively to Builder and System.

What is a site?

Kwant is a tool for working with tight-binding models, which can be viewed as a graph composed of edges and vertices. Sites are Kwant’s labels for the vertices. Sites have two attributes: a family and a tag. The combination of family and tag uniquely defines a site.

For example let us create an empty tight binding system and add two sites:

a = 1
lat = kwant.lattice.square(a)
syst = kwant.Builder()

syst[lat(1, 0)] = 4
syst[lat(1, 1)] = 4

kwant.plot(syst)
../_images/faq_site.png

In the above snippet we added 2 sites: lat(1, 0) and lat(0, 1). Both of these sites belong to the same family, lat, but have different tags: (1, 0) and (0, 1) respectively.

Both sites were given the value 4 which means that the above system corresponds to the Hamiltonian matrix

\[\begin{split}H = \left( \begin{array}{cc} 4 & 0 \\ 0 & 4 \end{array} \right).\end{split}\]

What is a hopping?

A hopping is simply a tuple of two of sites, which defines an edge of the graph that makes up a tight-binding model. Other sequences of sites that are not tuples, for example lists, are not treated as hoppings.

Starting from the example code from What is a site?, we can add a hopping to our system in the following way:

syst[(lat(1, 0), lat(1, 1))] = 1j
../_images/faq_hopping.png

Visually, a hopping is represented as a line that joins two sites.

The Hamiltonian matrix is now

\[\begin{split}H = \left( \begin{array}{cc} 4 & i \\ -i & 4 \end{array} \right).\end{split}\]

Note how adding (site_a, site_b) to a system and assigning it a value v, implicitly adds the hopping (site_b, site_a) with the Hermitian conjugate of v as value.

What is a site family, and what is a tag?

A site family groups related sites together, and a tag serves as a unique identifier for a site within a given family.

In the previous example we saw a family that was suggestively called lat, which had sites whose tags were pairs of integers. In this specific example the site family also happens to be a regular Bravais lattice, and the tags take on the meaning of lattice coordinates for a site on this lattice.

The concept of families and tags is, however, more general. For example, one could implement a mesh that can be locally refined in certain areas, by having a family where sites belong to a quadtree, or an amorphous blob where sites are tagged by letters of the alphabet.

What is a lattice?

Kwant allows to define and use Bravais lattices for dealing with collections of regularly placed sites. They know about things like what sites are neighbors, or what sites belong to a given region of real space. Monatomic lattices have a single site in their basis, while Polyatomic lattices have more than one site in their basis.

Monatomic lattices in Kwant are also site families, with sites that are tagged by tuples of integers: the site’s coordinates in the basis of primitive vectors of the lattice. Polyatomic lattices, however, are not site families, since lattice coordinates are not enough information to uniquely identify a site if there is more than one site in the basis. Polyatomic lattices do, however, have an attribute sublattices that is a list of monatomic lattices that together make up the whole polyatomic lattice.

Let’s create two monatomic lattices (lat_a and lat_b). (1, 0) and (0, 1) will be the primitive vectors and (0, 0) and (0.5, 0.5) the origins of the two lattices:

# Two monatomic lattices
primitive_vectors = [(1, 0), (0, 1)]
lat_a = kwant.lattice.Monatomic(primitive_vectors, offset=(0, 0))
lat_b = kwant.lattice.Monatomic(primitive_vectors, offset=(0.5, 0.5))
# lat1 is equivalent to kwant.lattice.square()

syst = kwant.Builder()

syst[lat_a(0, 0)] = 4
syst[lat_b(0, 0)] = 4

kwant.plot(syst)
../_images/faq_lattice.png

We can also create a Polyatomic lattice with the same primitive vectors and two sites in the basis:

# One polyatomic lattice containing two sublattices
lat = kwant.lattice.Polyatomic([(1, 0), (0, 1)], [(0, 0), (0.5, 0.5)])
sub_a, sub_b = lat.sublattices

The two sublattices sub_a and sub_b are nothing else than Monatomic instances, and are equivalent to lat_a and lat_b that we created previously. The advantage of the second approach is that there is now a Polyatomic object that is aware of both of its sublattices, and we can do things like calculate neighboring sites, even between sublattices, which would not be possible with the two separate Monatomic lattices.

The kwant.lattice module also defines several convenience functions, such as square and honeycomb, for creating lattices of common types, without having to explicitly specify all of the lattice vectors and basis vectors.

When plotting, how to color the different sublattices differently?

In the following example we shall use a kagome lattice, which has three sublattices.

lat = kwant.lattice.kagome()
syst = kwant.Builder()

a, b, c = lat.sublattices  # The kagome lattice has 3 sublattices

As we can see below, we create a new plotting function that assigns a color for each family, and a different size for the hoppings depending on the family of the two sites. Finally we add sites and hoppings to our system and plot it with the new function.

# Plot sites from different families in different colors
def family_color(site):
    if site.family == a:
        return 'red'
    if site.family == b:
        return 'green'
    else:
        return 'blue'

def plot_system(syst):
    kwant.plot(syst, site_lw=0.1, site_color=family_color)

## Add sites and hoppings.
for i in range(4):
    for j in range (4):
        syst[a(i, j)] = 4
        syst[b(i, j)] = 4
        syst[c(i, j)] = 4

syst[lat.neighbors()] = -1

## Plot the system.
plot_system(syst)
../_images/faq_colors.png

How to create many similar hoppings in one go?

This can be achieved with an instance of the class kwant.builder.HoppingKind. In fact, sites and hoppings are not the only possible keys when assigning values to a Builder. There exists a mechanism to expand more general keys into these simple keys.

A HoppingKind, the most comonly used general key, is a way of specifying all hoppings of a particular “kind”, between two site families. For example HoppingKind((1, 0), lat_a, lat_b) represents all hoppings of the form (lat_a(x + (1, 0)), lat_b(x)), where x is a tag (here, a pair of integers).

The following example shows how this can be used:

# Create hopping between neighbors with HoppingKind
a = 1
syst = kwant.Builder()
lat = kwant.lattice.square(a)
syst[ (lat(i, j) for i in range(5) for j in range(5)) ] = 4

syst[kwant.builder.HoppingKind((1, 0), lat)] = -1
kwant.plot(syst)
../_images/faq_direction1.png

Note that HoppingKind only works with site families so you cannot use them directly with Polyatomic lattices; you have to explicitly specify the sublattices when creating a HoppingKind:

# equivalent to syst[kwant.builder.HoppingKind((0, 1), b)] = -1
syst[kwant.builder.HoppingKind((0, 1), b, b)] = -1

Here, we want the hoppings between the sites from sublattice b with a direction of (0,1) in the lattice coordinates.

../_images/faq_direction2.png
syst[kwant.builder.HoppingKind((0, 0), a, b)] = -1
syst[kwant.builder.HoppingKind((0, 0), a, c)] = -1
syst[kwant.builder.HoppingKind((0, 0), c, b)] = -1

Here, we create hoppings between the sites of the same lattice coordinates but from different families.

../_images/faq_direction3.png

How to set the hoppings between adjacent sites?

Polyatomic and Monatomic lattices have a method neighbors that returns a list of HoppingKind instances that connect sites with their (n-nearest) neighors:

# Create hoppings with lat.neighbors()
syst = kwant.Builder()
lat = kwant.lattice.square()
syst[(lat(i, j) for i in range(3) for j in range(3))] = 4

syst[lat.neighbors()] = -1  # Equivalent to lat.neighbors(1)
kwant.plot(syst)

del syst[lat.neighbors()]  # Delete all nearest-neighbor hoppings
syst[lat.neighbors(2)] = -1

kwant.plot(syst)
../_images/faq_adjacent1.png ../_images/faq_adjacent2.png

As we can see in the figure above, lat.neighbors() (on the left) returns the hoppings between the first nearest neighbors and lat.neighbors(2) (on the right) returns the hoppings between the second nearest neighbors.

When using a Polyatomic lattice neighbors() knows about the different sublattices:

# Create the system
lat = kwant.lattice.kagome()
syst = kwant.Builder()
a, b, c = lat.sublattices  # The kagome lattice has 3 sublattices

for i in range(4):
    for j in range (4):
        syst[a(i, j)] = 4  # red
        syst[b(i, j)] = 4  # green
        syst[c(i, j)] = 4  # blue

syst[lat.neighbors()] = -1
../_images/faq_adjacent3.png

However, if we use the neighbors() method of a single sublattice, we will only get the neighbors on that sublattice:

syst[a.neighbors()] = -1
../_images/faq_adjacent4.png

Note in the above that there are only hoppings between the blue sites. This is an artifact of the visualisation: the red and green sites just happen to lie in the path of the hoppings, but are not connected by them.

How to make a hole in a system?

To make a hole in the system, use del syst[site], just like with any other mapping. In the following example we remove all sites inside some “hole” region:

# Define the lattice and the (empty) system
a = 2
lat = kwant.lattice.cubic(a)
syst = kwant.Builder()

L = 10
W = 10
H = 2

# Add sites to the system in a cuboid

syst[(lat(i, j, k) for i in range(L) for j in range(W) for k in range(H))] = 4
kwant.plot(syst)

# Delete sites to create a hole

def in_hole(site):
    x, y, z = site.pos / a - (L/2, W/2, H/2)  # position relative to centre
    return abs(x) < L / 4 and abs(y) < W / 4

for site in filter(in_hole, list(syst.sites())):
    del syst[site]

kwant.plot(syst)
../_images/faq_hole1.png ../_images/faq_hole2.png

del syst[site] also works after hoppings have been added to the system. If a site is deleted, then all the hoppings to/from that site are also deleted.

How to access a system’s sites?

The ways of accessing system sites is slightly different depending on whether we are talking about a Builder or System (see What is a system, and what is a builder? if you do not know the difference).

We can access the sites of a Builder by using its sites method:

# Before finalizing the system

sites = list(builder.sites())  # sites() doe *not* return a list

The sites() method returns an iterator over the system sites, and in the above example we create a list from the contents of this iterator, which contains all the sites. At this stage the ordering of sites is not fixed, so if you add more sites to the Builder and call sites() again, the sites may well be returned in a different order.

After finalization, when we are dealing with a System, the sites themselves are stored in a list, which can be accessed via the sites attribute:

# After finalizing the system
syst = builder.finalized()
sites = syst.sites  # syst.sites is an actual list

The order of sites in a System is fixed, and also defines the ordering of the system Hamiltonian, system wavefunctions etc. (see How does Kwant order components of an individual wavefunction? for details).

System also contains the inverse mapping, id_by_site which gives us the index of a given site within the system:

i = syst.id_by_site[lat(0, 2)]  # we want the id of the site lat(0, 2)

How to use different lattices for the scattering region and a lead?

Let us take the example of a system containing sites from a honeycomb lattice, which we want to connect to leads that contain sites from a square lattice.

First we construct the central system:

# Define the scattering Region
L = 5
W = 5

lat = kwant.lattice.honeycomb()
subA, subB = lat.sublattices

syst = kwant.Builder()
syst[(subA(i, j) for i in range(L) for j in range(W))] = 4
syst[(subB(i, j) for i in range(L) for j in range(W))] = 4
syst[lat.neighbors()] = -1
../_images/faq_different_lattice1.png

and the lead:

# Create a lead
lat_lead = kwant.lattice.square()
sym_lead1 = kwant.TranslationalSymmetry((0, 1))

lead1 = kwant.Builder(sym_lead1)
lead1[(lat_lead(i, 0) for i in range(2, 7))] = 4
lead1[lat_lead.neighbors()] = -1
../_images/faq_different_lattice2.png

We cannot simply use attach_lead to attach this lead to the system with the honeycomb lattice because Kwant does not know how sites from these two lattices should be connected.

We must first add a layer of sites from the square lattice to the system and manually add the hoppings from these sites to the sites from the honeycomb lattice:

syst[(lat_lead(i, 5) for i in range(2, 7))] = 4
syst[lat_lead.neighbors()] = -1

# Manually attach sites from graphene to square lattice
syst[((lat_lead(i+2, 5), subB(i, 4)) for i in range(5))] = -1
../_images/faq_different_lattice3.png

attach_lead() will now be able to attach the lead:

syst.attach_lead(lead1)
../_images/faq_different_lattice4.png

How to cut a finite system out of a system with translational symmetries?

This can be achieved using the fill method to fill a Builder with a Builder with higher symmetry.

When using the fill() method, we need two systems: the template and the target. The template is a Builder with some translational symmetry that will be repeated in the desired shape to create the final system.

For example, say we want to create a simple model on a cubic lattice:

# Create 3d model.
cubic = kwant.lattice.cubic()
sym_3d = kwant.TranslationalSymmetry([1, 0, 0], [0, 1, 0], [0, 0, 1])
model = kwant.Builder(sym_3d)
model[cubic(0, 0, 0)] = 4
model[cubic.neighbors()] = -1

We have now created our “template” Builder which has 3 translational symmetries. Next we will fill a system with no translational symmetries with sites and hoppings from the template inside a cuboid:

# Build scattering region (white).
def cuboid_shape(site):
    x, y, z = abs(site.pos)
    return x < 4 and y < 10 and z < 3

cuboid = kwant.Builder()
cuboid.fill(model, cuboid_shape, (0, 0, 0));
../_images/faq_fill2.png

We can then use the original template to create a lead, which has 1 translational symmetry. We can then use this lead as a template to fill another section of the system with a cylinder of sites and hoppings:

# Build electrode (black).
def electrode_shape(site):
    x, y, z = site.pos - (0, 5, 2)
    return y**2 + z**2 < 2.3**2

electrode = kwant.Builder(kwant.TranslationalSymmetry([1, 0, 0]))
electrode.fill(model, electrode_shape, (0, 5, 2))  # lead

# Scattering region
cuboid.fill(electrode, lambda s: abs(s.pos[0]) < 7, (0, 5, 4))

cuboid.attach_lead(electrode)
../_images/faq_fill3.png

How does Kwant order the propagating modes of a lead?

A very useful feature of kwant is to calculate the transverse wavefunctions of propagating modes in a system with 1 translational symmetry. This can be achieved with the modes method, which returns a pair of objects, the first of which contains the propagating modes of the system in a PropagatingModes object:

lat = kwant.lattice.square()

lead = kwant.Builder(kwant.TranslationalSymmetry((-1, 0)))
lead[(lat(0, i) for i in range(3))] = 4
lead[lat.neighbors()] = -1

flead = lead.finalized()

E = 2.5
prop_modes, _ = flead.modes(energy=E)

PropagatingModes contains the wavefunctions, velocities and momenta of the modes at the requested energy (2.5 in this example). In order to understand the order in which these quantities are returned it is often useful to look at the a section of the band structure for the system in question:

../_images/faq_pm1.png

On the above band structure we have labelled the 4 modes in the order that they appear in the output of modes() at energy 2.5. Note that the modes are sorted in the following way:

  • First all the modes with negative velocity, then all the modes with positive velocity
  • Negative velocity modes are ordered by increasing momentum
  • Positive velocity modes are ordered by decreasing momentum

For more complicated systems and band structures this can lead to some possibly unintuitive orderings:

../_images/faq_pm2.png

How does Kwant order scattering states?

Scattering states calculated using wave_function are returned in the same order as the “incoming” modes of modes. Kwant considers that the translational symmetry of a lead points “towards infinity” (not towards the system) which means that the incoming modes are those that have negative velocities.

This means that for a lead attached on the left of a scattering region (with symmetry vector $(-1, 0)$, for example), the positive $k$ direction (when inspecting the lead’s band structure) actually corresponds to the negative $x$ direction.

How does Kwant order components of an individual wavefunction?

In How to access a system’s sites? we saw that the sites of a finalized system are available as a list through the sites attribute, and that one can look up the index of a site with the id_by_site attribute.

When all the site families present in a system have only 1 degree of freedom per site (i.e. the all the onsites are scalars) then the index into a wavefunction defined over the system is exactly the site index:

lat = kwant.lattice.square(norbs=1)
syst = make_system(lat)
scattering_states = kwant.wave_function(syst, energy=1)
wf = scattering_states(0)[0]  # scattering state from lead 0 incoming in mode 0

idx = syst.id_by_site[lat(0, 0)]  # look up index of site

print('wavefunction on lat(0, 0): ', wf[idx])
wavefunction on lat(0, 0):  (0.12535832151852427-0.3634464249826888j)

We see that the wavefunction on a single site is a single complex number, as expected.

If a site family have more than 1 degree of freedom per site (e.g. spin or particle-hole) then Kwant places degrees of freedom on the same site adjacent to one another. In the case where all site families in the system have the same number of degrees of freedom, we can then simply reshape the wavefunction into a matrix, where the row number indexes the site, and the column number indexes the degree of freedom on that site:

lat = kwant.lattice.square(norbs=2)
syst = make_system(lat)
scattering_states = kwant.wave_function(syst, energy=1)
wf = scattering_states(0)[0]  # scattering state from lead 0 incoming in mode 0

idx = syst.id_by_site[lat(0, 0)]  # look up index of site

# Group consecutive degrees of freedom from 'wf' together; these correspond
# to degrees of freedom on the same site.
wf = wf.reshape(-1, 2)

print('wavefunction on lat(0, 0): ', wf[idx])
wavefunction on lat(0, 0):  [-0.04256406+0.04178877j  0.09634215-0.36738019j]

We see that the wavefunction on a single site is a vector of 2 complex numbers, as we expect.

If there are different site families present in the system that have different numbers of orbitals per site, then the situation becomes much more involved, because we cannot simply “reshape” the wavefunction like we did in the preceding example.