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Electronic Structure Calculations using Quantum Computing

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arxiv 2305.07902 v1 pith:36M6JPXH submitted 2023-05-13 quant-ph

classification quant-ph
keywords quantumalgorithmelectronicstructurecomputationalmethodscalculationscomplex
verification ladder T0 review T1 audit T2 compute T3 formal
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The computation of electronic structure properties at the quantum level is a crucial aspect of modern physics research. However, conventional methods can be computationally demanding for larger, more complex systems. To address this issue, we present a hybrid Classical-Quantum computational procedure that uses the Variational Quantum Eigensolver (VQE) algorithm. By mapping the quantum system to a set of qubits and utilising a quantum circuit to prepare the ground state wavefunction, our algorithm offers a streamlined process requiring fewer computational resources than classical methods. Our algorithm demonstrated similar accuracy in rigorous comparisons with conventional electronic structure methods, such as Density Functional Theory and Hartree-Fock Theory, on a range of molecules while utilising significantly fewer resources. These results indicate the potential of the algorithm to expedite the development of new materials and technologies. This work paves the way for overcoming the computational challenges of electronic structure calculations. It demonstrates the transformative impact of quantum computing on advancing our understanding of complex quantum systems.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region

    quant-ph 2024-11 reject novelty 3.0 of 10

    On a 32-point water quality dataset from Durban, a quantum support vector classifier reached 75% accuracy while a quantum neural network consistently failed to train.

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