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IBM Quantum Platform

Scale SQD chemistry workflows with Dice solver

This guide shows how to use the Dice solver as an alternative SCI solver to diagonalize larger Fermionic problems beyond what the default PySCF solver can support. For information on how to install and use qiskit-addon-dice-solver, visit the documentation. For more details on the SQD code used in this example, see the chemistry Hamiltonian tutorial.

import numpy as np
import pyscf
import pyscf.cc
import pyscf.mcscf
from qiskit_addon_dice_solver import solve_sci_batch
from qiskit_addon_sqd.counts import generate_bit_array_uniform
from qiskit_addon_sqd.fermion import diagonalize_fermionic_hamiltonian

# Specify molecule properties
num_orbitals = 16
num_elec_a = num_elec_b = 5
spin_sq = 0

# Build N2 molecule
mol = pyscf.gto.Mole()
mol.build(
    atom=[["N", (0, 0, 0)], ["N", (1.0, 0, 0)]],
    basis="6-31g",
    symmetry="Dooh",
)

# Define active space
n_frozen = 2
active_space = range(n_frozen, mol.nao_nr())

# Get molecular integrals
scf = pyscf.scf.RHF(mol).run()
num_orbitals = len(active_space)
n_electrons = int(sum(scf.mo_occ[active_space]))
num_elec_a = (n_electrons + mol.spin) // 2
num_elec_b = (n_electrons - mol.spin) // 2
cas = pyscf.mcscf.CASCI(scf, num_orbitals, (num_elec_a, num_elec_b))
mo = cas.sort_mo(active_space, base=0)
hcore, nuclear_repulsion_energy = cas.get_h1cas(mo)
eri = pyscf.ao2mo.restore(1, cas.get_h2cas(mo), num_orbitals)

# Compute exact energy
exact_energy = cas.run().e_tot

# Create a seed to control randomness throughout this workflow
rng = np.random.default_rng(24)


# Generate random samples
bit_array = generate_bit_array_uniform(
    10_000, num_orbitals * 2, rand_seed=rng
)

# Run SQD
result = diagonalize_fermionic_hamiltonian(
    hcore,
    eri,
    bit_array,
    samples_per_batch=300,
    norb=num_orbitals,
    nelec=(num_elec_a, num_elec_b),
    num_batches=5,
    max_iterations=5,
    sci_solver=solve_sci_batch,
    symmetrize_spin=True,
    seed=rng,
)

Output:

converged SCF energy = -108.835236570774
CASCI E = -109.046671778080  E(CI) = -32.8155692383187  S^2 = 0.0000000
print(f"Exact energy: {exact_energy}")
print(f"Estimated energy: {result.energy + nuclear_repulsion_energy}")

Output:

Exact energy: -109.04667177808028
Estimated energy: -109.03402667558743
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