QUANTUM CHEMISTRY SIMULATIONS: MOLECULES ON QUANTUM COMPUTERS

Quantum chemistry simulations harness hybrid quantum–classical algorithms like AFQMC, VQE and QPE to solve the Schrödinger equation. IonQ recently used a trapped‑ion computer to compute atomic‑level forces with higher accuracy than classical methods【428013860627105†L72-L120】 and is building a 2‑million‑qubit machine by 2030【428013860627105†L72-L120】. Hybrid algorithms reduce qubit counts and energy consumption【579869523161688†L168-L195】, and the MIT Quantum Index Report argues the hardware race now focuses on gate fidelity and error correction【876914668239973†L531-L551】.

Practical applications include drug discovery, materials design, carbon capture and battery innovation. Access remains uneven: wealthy institutions may adopt quantum‑designed drugs earlier, while developing regions face barriers.

Takeaways: researchers should focus on error mitigation and hybrid strategies; developers can contribute to open‑source tools; enterprises should run pilot simulations; policymakers must fund quantum education. Below is a short VQE snippet for H₂ in Qiskit:

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from qiskit import Aer
from qiskit.algorithms import VQE
from qiskit.circuit.library import TwoLocal
from qiskit_nature.drivers import PySCFDriver
from qiskit_nature.problems.second_quantization import ElectronicStructureProblem
from qiskit_nature.converters.second_quantization import QubitConverter
from qiskit_nature.mappers.second_quantization import ParityMapper

driver = PySCFDriver(atom='H .0 .0 0; H .0 .0 0.74', unit='Angstrom', basis='sto3g')
problem = ElectronicStructureProblem(driver)
converter = QubitConverter(mapper=ParityMapper(), two_qubit_reduction=True)
hamiltonian = converter.convert(problem.second_q_ops()[0], num_particles=problem.num_particles)
ansatz = TwoLocal(rotation_blocks=['ry','rz'], entanglement_blocks='cz', reps=2)
vqe = VQE(ansatz, quantum_instance=Aer.get_backend('statevector_simulator'))
energy = vqe.compute_minimum_eigenvalue(hamiltonian).eigenvalue.real

Conclusion: Quantum chemistry simulations are progressing from toy models to practical relevance, but realistic timelines and cross‑disciplinary collaboration are vital.