qml.spin.fermi_hubbard¶
-
fermi_hubbard
(lattice, n_cells, hopping=1.0, coulomb=1.0, boundary_condition=False, neighbour_order=1, mapping='jordan_wigner')[source]¶ Generates the Hamiltonian for the Fermi-Hubbard model on a lattice.
The Hamiltonian is represented as:
\[\hat{H} = -t\sum_{<i,j>, \sigma}(c_{i\sigma}^{\dagger}c_{j\sigma}) + U\sum_{i}n_{i \uparrow} n_{i\downarrow}\]where
t
is the hopping term representing the kinetic energy of electrons,U
is the on-site Coulomb interaction, representing the repulsion between electrons,i,j
represent the indices for neighbouring spins, \(\sigma\) is the spin degree of freedom, and \(n_{i \uparrow}, n_{i \downarrow}\) are number operators for spin-up and spin-down fermions at sitei
. This function assumes there are two fermions with opposite spins on each lattice site.- Parameters
lattice (str) – Shape of the lattice. Input values can be
'chain'
,'square'
,'rectangle'
,'honeycomb'
,'triangle'
, or'kagome'
.n_cells (List[int]) – Number of cells in each direction of the grid.
hopping (float or List[float] or List[math.array(float)]) – Hopping strength between neighbouring sites, it can be a number, a list of length equal to
neighbour_order
or a square matrix of size(num_spins, num_spins)
, wherenum_spins
is the total number of spins. Default value is 1.0.coulomb (float or List[float]) – Coulomb interaction between spins. It can be a constant or a list of length equal to number of spins.
boundary_condition (bool or list[bool]) – Defines boundary conditions for different lattice axes, default is
False
indicating open boundary condition.neighbour_order (int) – Specifies the interaction level for neighbors within the lattice. Default is 1, indicating nearest neighbours.
mapping (str) – Specifies the fermion-to-qubit mapping. Input values can be
'jordan_wigner'
,'parity'
or'bravyi_kitaev'
.
- Returns
Hamiltonian for the Fermi-Hubbard model.
- Return type
Example
>>> n_cells = [2] >>> h = [0.5] >>> u = 1.0 >>> spin_ham = qml.spin.fermi_hubbard("chain", n_cells, hopping=h, coulomb=u) >>> spin_ham ( -0.25 * (Y(0) @ Z(1) @ Y(2)) + -0.25 * (X(0) @ Z(1) @ X(2)) + 0.5 * I(0) + -0.25 * (Y(1) @ Z(2) @ Y(3)) + -0.25 * (X(1) @ Z(2) @ X(3)) + -0.25 * Z(1) + -0.25 * Z(0) + 0.25 * (Z(0) @ Z(1)) + -0.25 * Z(3) + -0.25 * Z(2) + 0.25 * (Z(2) @ Z(3)) )