Modelling Carbon Capture on Metal-Organic Frameworks with Quantum Computing

Despite the recent progress in quantum computational algorithms for chemistry, there is a dearth of quantum computational simulations focused on material science applications, especially for the energy sector, where next generation sorbing materials are urgently needed to battle climate change. To drive their development, quantum computing is applied to the problem of CO2 adsorption in Al-fumarate Metal-Organic Frameworks.

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Quantum Hardware Calculations of Periodic Systems: Hydrogen Chain and Iron Crystals

We focus on the practical aspect of quantum computational calculations of solid-state crystalline materials based on a theory developed in our group by using real quantum hardware with noise mitigation techniques. We select two periodic systems with different levels of complexity for these calculations, the distorted hydrogen chain and the iron crystal in the BCC and FCC phases, and evaluate the ground state energies.

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Generalized Unitary Coupled Cluster Excitations for Multireference Molecular States Optimized by the Variational Quantum Eigensolver

The variational quantum eigensolver (VQE) requires specification of symmetries that describe the system, e.g. spin state and number of electrons. This opens the possibility of using VQE to obtain excited states. In this paper, various unitary coupled cluster (UCC) ansätze applied to excited states are investigated, using quantum circuits to represent single reference and multi-reference wavefunctions.

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From Stochastic Spin Chains to Quantum Kardar-Parisi-Zhang Dynamics

We introduce the asymmetric extension of the Quantum Symmetric Simple Exclusion Process which is a stochastic model of fermions on a lattice hopping with random amplitudes. We analytically show that the time-integrated current of fermions defines a height field which exhibits a quantum non-linear stochastic Kardar-Parisi-Zhang dynamics.

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Evaluating the Noise Resilience of Variational Quantum Algorithms

We simulate the effects of different noise types in state preparation. We find that the inclusion of redundant parameterised gates makes the circuits more noise resilient. We also report a circuit-dependent noise threshold above which the optimisation can converge to states with largely different physical properties from the target state.

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