Examples

Everything related to constructing examples that motivate and teach how to use our package. This includes:

• coming up with new interesting physical systems
• cleaning up the existing ones

and likely more.

docs/source/mf_notes.md

 # Algorithm overview
 
-## Interacting problems
+## Derivation of the mean-field Hamiltonian
+
+### Interacting problems
 
 In physics, one often encounters problems where a system of multiple particles interact with each other.
 In this package, we consider a general electronic system with density-density interparticle interaction:
 
 :::{math}
 :label: hamiltonian
-\hat{H} = \hat{H_0} + \hat{V} = \sum_{ij} h_{ij} c^\dagger_{i} c_{j} + \frac{1}{2} \sum_{ij} v_{ij} c_i^\dagger c_j^\dagger c_j c_i
+\hat{H} = \hat{H^0} + \hat{V} = \sum_{ij} h_{ij} c^\dagger_{i} c_{j} + \frac{1}{2} \sum_{ij} v_{ij} c_i^\dagger c_j^\dagger c_j c_i
 :::
 
 where $c_i^\dagger$ and $c_i$ are creation and annihilation operators respectively for fermion in state $i$.
-The first term $\hat{H}_0$ is the non-interacting Hamiltonian which by itself is straightforward to solve in a single-particle basis by direct diagonalizations made easy through packages such as `kwant`.
+The first term $\hat{H^0}$ is the non-interacting Hamiltonian which by itself is straightforward to solve in a single-particle basis by direct diagonalizations made easy through packages such as `kwant`.
 The second term $\hat{V}$ is density-density interaction term between two particles, for example Coulomb interaction.
 In order to solve the interacting problem exactly, one needs to diagonalize the full Hamiltonian $\hat{H}$ in the many-particle basis which grows exponentially with the number of particles.
 Such a task is often infeasible for large systems and one needs to resort to approximations.
 
-## Mean-field Hamiltonian
+### Mean-field approximaton
 
 The first-order perturbative approximation to the interacting Hamiltonian is the Hartree-Fock approximation also known as the mean-field approximation.
 The mean-field approximates the quartic term $\hat{V}$ in {eq}`hamiltonian` as a sum of bilinear terms weighted by the expectation values the remaining operators:
-
-$$
+:::{math}
+:label: mf_approx
 \hat{V} \approx \hat{V}^{\text{MF}} \equiv \sum_{ij} v_{ij} \left[
 \braket{c_i^\dagger c_i} c_j^\dagger c_j - \braket{c_i^\dagger c_j} c_j^\dagger c_i \right]
-$$
-
+:::
 we neglect the superconducting pairing and constant offset terms.
-The expectation value terms  $\langle c_i^\dagger c_j \rangle$ are due to the ground-state density matrix:
-
-$$
-\rho_{ij} \equiv \langle c_i^\dagger c_j \rangle,
-$$
-
-and therefore act as an effective field acting on the system.
+The expectation value terms  $\langle c_i^\dagger c_j \rangle$ are due to the ground-state density matrix and therefore act as an effective field acting on the system.
+The ground-state density matrix reads:
+:::{math}
+:label: density
+\rho_{ij} \equiv \braket{c_i^\dagger c_j } = \text{Tr}\left(e^{-\beta \left(\hat{H^0} + \hat{V}^{\text{MF}} - \mu \hat{N} \right)} c_i^\dagger c_j\right),
+:::
+where $\beta = 1/ (k_B T)$ is the inverse temperature, $\mu$ is the chemical potential, and $\hat{N} = \sum_i c_i^\dagger c_i$ is the number operator.
 
-<!-- :::{admonition} Derivation of the mean-field Hamiltonian with Wicks theorem
+:::{admonition} Derivation of the mean-field Hamiltonian with Wicks theorem
 :class: dropdown info
 ```{include} mf_details.md
 ```
-::: -->
+:::
 
-### Tight-binding grid
+### Finite tight-binding grid
 
-To simplify the mean-field Hamiltonian, we assume a normalised orthogonal tight-binding grid defined by the single-particle basis states:
+To simplify the mean-field Hamiltonian, we assume a finite, normalised orthogonal tight-binding grid defined by the single-particle basis states:
 
 $$
 \ket{n} = c^\dagger_n\ket{\text{vac}}
 $$
 
 where $\ket{\text{vac}}$ is the vacuum state.
-We project our mean-field interaction onto the tight-binding grid:
+We project our mean-field interaction in {eq}`mf_approx` onto the tight-binding grid:
+
+:::{math}
+:label: mf_finite
+V^\text{MF}_{nm} = \braket{n | \hat{V}^{\text{MF}} | m} =  \sum_{i} \rho_{ii} v_{in} \delta_{nm} - \rho_{mn} v_{mn},
+:::
+where $\delta_{nm}$ is the Kronecker delta function.
+
+### Infinite tight-binding grid
+
+In the limit of a translationally invariant system, the index $n$ that labels the basis states partitions into two independent variables: the unit cell internal degrees of freedom (spin, orbital, sublattice, etc.) and the position of the unit cell $R_n$:
 
 $$
-V^\text{MF}_{nm} = \langle n | \hat{V}^{\text{MF}} | m \rangle =  \sum_{i} \rho_{ii} v_{in} \delta_{nm} - \rho_{mn} v_{mn},
+n \to n, R_n.
 $$
-where $\delta_{nm}$ is the Kronecker delta function.
+
+Because of the translationaly invariance, the physical properties of the system are independent of the absolute unit cell position $R_n$ and rather depend on the relative position between the two unit cells $R_{nm} = R_n - R_m$:
+
+$$
+\rho_{mn} \to \rho_{mn}(R_{mn}).
+$$
+
+That allows us to re-write the mean-field interaction in {eq}`mf_finite` as:
+
+:::{math}
+:label: mf_infinite
+V^\text{MF}_{nm} (R) =  \sum_{i} \rho_{ii} (0) v_{in} (0) \delta_{nm} \delta(R) - \rho_{mn}(R) v_{mn}(R),
+:::
+
+where now indices $i, n, m$ label the internal degrees of freedom of the unit cell and $R$ is the relative position between the two unit cells in terms of the lattice vectors.
+
+## Numerical solution of the mean-field Hamiltonian
+
+In order to calculate the mean-field interaction in {eq}`mf_infinite`, we require the ground-state density matrix $\rho_{mn}(R)$.
+However, the density matrix in {eq}`density` is a functional of the mean-field interaction $\hat{V}^{\text{MF}}$ itself.
+Therefore,