H-2
Emerging21papers using it
2024first seen
The 'H-2' dataset contains the potential energy surface of the hydrogen molecule (H\(_2\)) across 100 bond lengths and is used to evaluate the performance of the Variational Quantum Eigensolver (VQE) algorithm in computing ground state energies.
Papers using H-2 (21)
- Fast and Noise-aware Machine Learning Variational Quantum Eigensolver
OptimiserImpact of gate-voltage noise on silicon spin-qubit variational quantum eigensolversExperimental Realization of the Markov Chain Monte Carlo Algorithm on a Quantum ComputerVelocity Verlet-based optimization for variational quantum eigensolversClassical Regularization in Variational Quantum EigensolversQuantum-Inspired Ising Machines for Quantum Chemistry CalculationsSize-Consistent Quantum Chemistry on Quantum ComputersQuantum Computing Approach to Atomic and Molecular Three-Body SystemsQuantum Generative Adversarial Autoencoders: Learning latent representations for quantum data generationEstimating shots and variance on noisy quantum circuitsSimulating electronic structure on bosonic quantum computersSubspace-Search Quantum Imaginary Time Evolution for Excited State ComputationsLow Depth Virtual Distillation of Quantum Circuits by Deterministic Circuit DecompositionMolecular groundstate determination via short pulses on superconducting qubitsMinimal evolution times for fast, pulse-based state preparation in silicon spin qubitsA Study on Quantum Car-Parrinello Molecular Dynamics with Classical
Shadows for Resource Efficient Molecular SimulationHardware-efficient variational quantum algorithm in trapped-ion quantum
computerDigital-analog quantum genetic algorithm using Rydberg-atom arraysVariational Quantum Imaginary Time Evolution for Matrix Product State
Ansatz with Tests on Transcorrelated HamiltoniansToward a Quantum Computing Formulation of the Electron Nuclear Dynamics
Method via Fukutome Unitary RepresentationQuantum annealer accelerates the variational quantum eigensolver in a
triple-hybrid algorithm