qat.fermion.hamiltonians.SpinHamiltonian

class qat.fermion.hamiltonians.SpinHamiltonian(nqbits: int, terms: List[Term], constant_coeff: float = 0.0)

Implementation of a spin Hamiltonian.

Parameters:

nqbits (int) – the total number of qubits
terms (List[Term]) – the list of terms
constant_coeff (float) – constant term

nbqbits

the total number of qubits

Type:: int

terms

the list of terms

Type:: List[Term]

constant_coeff

constant term

Type:: float

matrix

the corresponding matrix (None by default, can be set by calling get_matrix method)

Type:: np.ndarray

Example

from qat.core import Term
from qat.fermion import SpinHamiltonian

hamiltonian = SpinHamiltonian(2, [Term(0.3, "X", [0]), Term(-0.4, "ZY", [0, 1])])

print(f"H = {hamiltonian}")
print(f"H matrix: {hamiltonian.get_matrix()}")

H = 0.3 * (X|[0]) +
-0.4 * (ZY|[0, 1])
H matrix: [[0. +0.j  0. +0.4j 0.3+0.j  0. +0.j ]
 [0. -0.4j 0. +0.j  0. +0.j  0.3+0.j ]
 [0.3+0.j  0. +0.j  0. +0.j  0. -0.4j]
 [0. +0.j  0.3+0.j  0. +0.4j 0. +0.j ]]

copy()

Deepcopy the current class.

Returns:: Copy of the SpinHamiltonian.
Return type:: SpinHamiltonian

dag() → SpinHamiltonian

Compute the conjugate transpose of the Hamiltonian.

Returns:: Conjugate transpose of the SpinHamiltonian operator
Return type:: SpinHamiltonian

get_matrix(sparse: bool = False) → ndarray

This function returns the matrix corresponding to \(H\) in the computational basis.

Parameters:

sparse (Optional[bool]) – Whether to return in sparse representation.
False. (Defaults to)

Returns:

The matrix of the SpinHamiltonian.

Return type:

np.ndarray

Warning

This method should not be used if the SpinHamiltonian is too large.