Hamiltonian#

Central to quantum chemical calculations for molecules is the fermionic two-body Hamiltonian in second quantized form.

TODO: spinfree, nonrelativistic, without external fields, without nuclear-repulsion energy

\[\hat{H} = \sum_{pq} h_{pq} a^\dagger_p a_q + \frac12 \sum_{pqrs} g_{pqrs} a^\dagger_p a^\dagger_r a_s a_q \]

The integrals \(h_{pq}\) and \(g_{pqrs}\) are one- and two-electron integrals in atomic units. For spinorbitals \(\phi_j\) that make up the basis, the integrals are [1]:

\[h_{pq} = \int \phi^*_p(\mathbf{x}_1)\left( -\frac12 \nabla^2 - \sum_A \frac{Z_A}{r_{A}} \right) \phi_q(\mathbf{x}_1) d\mathbf{x}_1\]

\[g_{pqrs} = \int \int \phi^*_p(\mathbf{x}_1)\phi^*_r(\mathbf{x}_2) \frac{1}{r_{12}} \phi_s(\mathbf{x}_2)\phi_q(\mathbf{x}_1) dx_1 dx_2\]

These integral quantities are obtained from the PySCF driver program, and can be accessed via the Molecule class. Qibochem then uses these integrals and OpenFermion to construct the second quantized fermionic Hamiltonian for the molecular system in terms of creation and annihilation operators, with coefficients from these integral quantities.

Example#

from qibochem.driver.molecule import Molecule
mol = Molecule([('H', (0.0, 0.0, 0.0)), ('H', (0.0, 0.0, 0.74804))])
mol.run_pyscf()
mol_ferm_ham = mol.hamiltonian("ferm") # or mol.hamiltonian("f")
print(mol_ferm_ham.terms)

Output:

{(): 0.7074183344740923, ((0, 1), (0, 0)): -1.248461959132892, ((1, 1), (1, 0)): -1.248461959132892, ((2, 1), (2, 0)): -0.48007161818330846, ((3, 1), (3, 0)): -0.48007161818330846, ((0, 1), (0, 1), (0, 0), (0, 0)): 0.3366109237586995, ((0, 1), (0, 1), (2, 0), (2, 0)): 0.09083064962340165, ((0, 1), (1, 1), (1, 0), (0, 0)): 0.3366109237586995, ((0, 1), (1, 1), (3, 0), (2, 0)): 0.09083064962340165, ((0, 1), (2, 1), (0, 0), (2, 0)): 0.09083064962340165, ((0, 1), (2, 1), (2, 0), (0, 0)): 0.33115823068165495, ((0, 1), (3, 1), (1, 0), (2, 0)): 0.09083064962340165, ((0, 1), (3, 1), (3, 0), (0, 0)): 0.33115823068165495, ((1, 1), (0, 1), (0, 0), (1, 0)): 0.3366109237586995, ((1, 1), (0, 1), (2, 0), (3, 0)): 0.09083064962340165, ((1, 1), (1, 1), (1, 0), (1, 0)): 0.3366109237586995, ((1, 1), (1, 1), (3, 0), (3, 0)): 0.09083064962340165, ((1, 1), (2, 1), (0, 0), (3, 0)): 0.09083064962340165, ((1, 1), (2, 1), (2, 0), (1, 0)): 0.33115823068165495, ((1, 1), (3, 1), (1, 0), (3, 0)): 0.09083064962340165, ((1, 1), (3, 1), (3, 0), (1, 0)): 0.33115823068165495, ((2, 1), (0, 1), (0, 0), (2, 0)): 0.3311582306816552, ((2, 1), (0, 1), (2, 0), (0, 0)): 0.09083064962340165, ((2, 1), (1, 1), (1, 0), (2, 0)): 0.3311582306816552, ((2, 1), (1, 1), (3, 0), (0, 0)): 0.09083064962340165, ((2, 1), (2, 1), (0, 0), (0, 0)): 0.09083064962340165, ((2, 1), (2, 1), (2, 0), (2, 0)): 0.348087115228365, ((2, 1), (3, 1), (1, 0), (0, 0)): 0.09083064962340165, ((2, 1), (3, 1), (3, 0), (2, 0)): 0.348087115228365, ((3, 1), (0, 1), (0, 0), (3, 0)): 0.3311582306816552, ((3, 1), (0, 1), (2, 0), (1, 0)): 0.09083064962340165, ((3, 1), (1, 1), (1, 0), (3, 0)): 0.3311582306816552, ((3, 1), (1, 1), (3, 0), (1, 0)): 0.09083064962340165, ((3, 1), (2, 1), (0, 0), (1, 0)): 0.09083064962340165, ((3, 1), (2, 1), (2, 0), (3, 0)): 0.348087115228365, ((3, 1), (3, 1), (1, 0), (1, 0)): 0.09083064962340165, ((3, 1), (3, 1), (3, 0), (3, 0)): 0.348087115228365}

Additional information about the data structure of the second quantized fermionic Hamiltonian can be found here.

Fermion to Qubit mapping#

The fermionic Hamiltonian can then be mapped into qubit Hamiltonians in OpenFermion form.

mol_qubit_ham = mol.hamiltonian("qubit") # or mol.hamiltonian("q")
mol_sym_ham = mol.hamiltonian("sym")     # or mol.hamiltonian("s")

Supported mapping schemes are the Jordan-Wigner and Bravyi-Kitaev schemes, as implemented in OpenFermion.

Example#

The mapping scheme can be specified using the keyword ferm_qubit_map as follows:

mol_qubit_ham = mol.hamiltonian("qubit", ferm_qubit_map="jw")
print(mol_qubit_ham.terms)

Output:

{(): -0.10728041160866736, ((0, 'Z'),): 0.17018261181714206, ((1, 'Z'),): 0.17018261181714206, ((2, 'Z'),): -0.21975065439248248, ((3, 'Z'),): -0.21975065439248248, ((0, 'Z'), (1, 'Z')): 0.16830546187934975, ((0, 'Z'), (2, 'Z')): 0.1201637905291267, ((0, 'Z'), (3, 'Z')): 0.16557911534082753, ((1, 'Z'), (2, 'Z')): 0.16557911534082753, ((1, 'Z'), (3, 'Z')): 0.1201637905291267, ((2, 'Z'), (3, 'Z')): 0.1740435576141825, ((0, 'X'), (1, 'X'), (2, 'Y'), (3, 'Y')): -0.045415324811700825, ((0, 'X'), (1, 'Y'), (2, 'Y'), (3, 'X')): 0.045415324811700825, ((0, 'Y'), (1, 'X'), (2, 'X'), (3, 'Y')): 0.045415324811700825, ((0, 'Y'), (1, 'Y'), (2, 'X'), (3, 'X')): -0.045415324811700825}

Additional information about the data structure of the qubit Hamiltonian can be found here.

Symbolic Hamiltonian#

To carry out quantum simulations of the electronic structure in molecules using methods such as VQE and time evolution using Qibo, the Hamiltonian has to be defined either in the full matrix form, or a more efficient term representation using sympy form:

mol_sym_ham = mol.hamiltonian("sym")     # or mol.hamiltonian("s")
print(mol_sym_ham.form)

-0.107280411608667 - 0.0454153248117008*X0*X1*Y2*Y3 + 0.0454153248117008*X0*Y1*Y2*X3 + 0.0454153248117008*Y0*X1*X2*Y3 - 0.0454153248117008*Y0*Y1*X2*X3 + 0.170182611817142*Z0 + 0.16830546187935*Z0*Z1 + 0.120163790529127*Z0*Z2 + 0.165579115340828*Z0*Z3 + 0.170182611817142*Z1 + 0.165579115340828*Z1*Z2 + 0.120163790529127*Z1*Z3 - 0.219750654392482*Z2 + 0.174043557614182*Z2*Z3 - 0.219750654392482*Z3

By default, the symbolic Hamiltonian is returned, i.e. if no arguments are given for mol.hamiltonian().

References