LiH
Emerging17papers using it
2022first seen
The 'LiH' dataset/benchmark contains data related to the lithium hydride molecule and is used to evaluate quantum computing methods for estimating ground-state energies and exploring potential energy landscapes in molecular simulations.
Papers using LiH (17)
- Non-Iterative Disentangled Unitary Coupled-Cluster based on Lie-algebraic structureMolecular Quantum TransformerTowards Chemically Accurate and Scalable Quantum Simulations on IQM Quantum Hardware: A Quantum-HPC Hybrid ApproachPath-integral molecular dynamics with actively-trained and universal machine learning force fieldsElectronic Structure Theory with Molecular Point Group Symmetries on Quantum AnnealersAutomated near-term quantum algorithm discovery for molecular ground statesQMCTorch: Molecular Wavefunctions with Neural Components for Energy and Force CalculationsData Efficient Prediction of excited-state properties using Quantum Neural NetworksTowards Efficient Quantum Computing for Quantum Chemistry: Reducing
Circuit Complexity with Transcorrelated and Adaptive Ansatz TechniquesModular Cluster Circuits for the Variational Quantum EigensolverPhysics-Informed Neural Networks for an optimal counterdiabatic quantum computationLeveraging Normalizing Flows for Orbital-Free Density Functional TheoryTransferable Neural Wavefunctions for SolidsAdaptive Basis Sets for Practical Quantum ComputingVariational Denoising for Variational Quantum EigensolverFolded Spectrum VQE : A quantum computing method for the calculation of
molecular excited statesVariational Quantum Imaginary Time Evolution for Matrix Product State
Ansatz with Tests on Transcorrelated Hamiltonians