Modeling Li-ion Adsorption on Pyridine Molecule with Quantum Computers

Despite recent progress in quantum computational algorithms, such as the variational quantum algorithm (VQE) for chemistry, there is still a shortage of quantum computational simulations focused on larger molecules and strong interactions. We present the simulations of noncovalent dative interaction between Li-ion and pyridine molecule using an Hartree-Fock-based embedding approach. We apply quantum computation to investigate Li-ion adsorption on a pyridine molecule, varying the Li-ion adsorption sites to obtain the potential energy surface (PES). The Pyridine-Li⁺ complex contains 44 paired electrons, and fully describing this system on quantum computers would require approximately 75 qubits. Currently, this problem cannot be fully addressed using available classical simulators of quantum circuits or the existing noisy intermediate-scale quantum (NISQ) devices, which are limited to only a few tens of qubits. To overcome this limitation, we adopt a projection-based embedding strategy, where only a crucial subset of the molecular system is described using a high-accuracy quantum computational method, while the rest is approximated with a more efficient classical approach, providing a lower level but computationally inexpensive representation of the electronic structure. Various error mitigation techniques, including readout error mitigation (REOM) and zero-noise extrapolation (ZNE), are employed to mitigate circuit errors during execution. Additionally, we use dynamical decoupling for error suppression. We demonstrate that this quantum computing approach can produce results with an acceptable level of accuracy using a small number of quantum resources. This complex is significant in various applications such as hydrogen storage catalysis and battery technologies, where Li⁺ interactions play a critical role. Our framework provides a pathway for scaling up quantum computations to large molecular systems, accelerating the development of sustainable and renewable energy systems.