 ### fix a few more typos

parent f106f961
 ... ... @@ -53,6 +53,8 @@ The remainder of this section demonstrates how to realize the discretized Hamiltonian in Kwant and how to perform transmission calculations. For simplicity, we choose to work in such units that :math:t = a = 1. .. _tutorial_quantum_wire: Transport through a quantum wire ................................ ... ... @@ -416,16 +418,16 @@ And one main function. Finally, we use the following standard Python construct [#]_ to execute main if the program is used as a script (i.e. executed as python tutorial1b.py): python quantum_wire_revisited.py): .. literalinclude:: quantum_wire_revisited.py :start-after: #HIDDEN_BEGIN_ypbj :end-before: #HIDDEN_END_ypbj If the example, however, is imported inside Python using import tutorial1b, main is not executed automatically. Instead, you can execute it manually using tutorial1b.main(). On the other hand, you also have access to the other functions, make_system and If the example, however, is imported inside Python using import quantum_wire_revisted as qw, main is not executed automatically. Instead, you can execute it manually using qw.main(). On the other hand, you also have access to the other functions, make_system and plot_conductance, and can thus play with the parameters. The result of the example should be identical to the previous one. ... ...
 ... ... @@ -136,9 +136,9 @@ case of a position-dependent potential: H = \frac{\hbar^2}{2 m} (\partial_x^2+\partial_y^2) + V(x, y) The position-dependent potential enters in the onsite energies. One possibility would be to again set the onsite matrix elements of each lattice point individually (as in tutorial1a.py). However, The position-dependent potential enters in the onsite energies. One possibility would be to again set the onsite matrix elements of each lattice point individually (as in :ref:tutorial_quantum_wire). However, changing the potential then implies the need to build up the system again. Instead, we use a python *function* to define the onsite energies. We ... ...
 ... ... @@ -27,11 +27,11 @@ invariant system needed for band structure calculations. In the previous examples ~kwant.builder.Builder instances like the one created above were attached as leads to the Builder instance of the scattering region and the latter was finalized. The thus created system contained implicitly finalized versions of the attached leads. But now we are working with a single lead and there is no scattering region. So we have to finalized the Builder of our sole lead explicitly. contained implicitly finalized versions of the attached leads. However, now we are working with a single lead and there is no scattering region. Hence, we have to finalize the Builder of our sole lead explicitly. That finalized lead is then passed to ~kwant.plotter.bands. This function That finalized lead is then passed to ~kwant.plotter.bands. This function calculates energies of various bands at a range of momenta and plots the calculated energies. It is really a convenience function, and if one needs to do something more profound with the dispersion relation these energies may be ... ... @@ -65,7 +65,7 @@ In this example, we compute the wave functions of a closed circular quantum dot and its spectrum as a function of magnetic field (Fock-Darwin spectrum). To compute the eigenenergies and eigenstates, we will make use of the sparse linear algebra functionality of scipy _, which linear algebra functionality of SciPy _, which interfaces the ARPACK package: .. literalinclude:: closed_system.py ... ...
 ... ... @@ -84,8 +84,9 @@ The leads are defined almost as before: Note the method ~kwant.lattice.Polyatomic.vec used in calculating the parameter for ~kwant.lattice.TranslationalSymmetry. The latter expects a real-space symmetry vector, but for many lattices symmetry vectors are more easily expressed in the natural coordinate system of the lattice. The vec method of lattices maps a lattice vector to a real-space vector. easily expressed in the natural coordinate system of the lattice. The ~kwant.attices.Polyatomic.vec-method is thus used to map a lattice vector to a real-space vector. Observe also that the translational vectors graphene.vec((-1, 0)) and graphene.vec((0, 1)) are *not* orthogonal any more as they would have been ... ... @@ -108,10 +109,7 @@ in the following piece of code: :end-before: #HIDDEN_END_zydk Here we use in contrast to the previous example a sparse matrix and the sparse linear algebra functionality of SciPy (this requires SciPy version >= 0.9.0; since the remaining part of the example does not depend on this eigenenergy calculation, a try-block simply skips this calculation if a lower SciPy version is installed.) the sparse linear algebra functionality of SciPy. The code for computing the band structure and the conductance is identical to the previous examples, and needs not be further explained here. ... ...
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment