Comparative study of adaptive variational quantum eigensolvers for multi-orbital impurity models
@article{Mukherjee2022ComparativeSO, title={Comparative study of adaptive variational quantum eigensolvers for multi-orbital impurity models}, author={Anirban Mukherjee and Noah F. Berthusen and Jo{\~a}o C. Getelina and Peter P. Orth and Yongxin Yao}, journal={Communications Physics}, year={2022}, volume={6}, pages={1-15} }
Hybrid quantum-classical embedding methods for correlated materials simulations provide a path towards potential quantum advantage. However, the required quantum resources arising from the multi-band nature of d and f electron materials remain largely unexplored. Here we compare the performance of different variational quantum eigensolvers in ground state preparation for interacting multi-orbital embedding impurity models, which is the computationally most demanding step in quantum embedding…
One Citation
References
SHOWING 1-10 OF 98 REFERENCES
Gutzwiller hybrid quantum-classical computing approach for correlated materials
- Physics
- 2020
Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational…
The theory of variational hybrid quantum-classical algorithms
- Computer Science
- 2015
This work develops a variational adiabatic ansatz and explores unitary coupled cluster where it is shown how the use of modern derivative free optimization techniques can offer dramatic computational savings of up to three orders of magnitude over previously used optimization techniques.
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
- PhysicsNature
- 2017
The experimental optimization of Hamiltonian problems with up to six qubits and more than one hundred Pauli terms is demonstrated, determining the ground-state energy for molecules of increasing size, up to BeH2.
Benchmarking Adaptive Variational Quantum Eigensolvers
- PhysicsFrontiers in Chemistry
- 2020
Using numerical simulation, it is found both methods provide good estimates of the energy and ground state, but only ADAPT-VQE proves to be robust to particularities in optimization methods, and gradient-based optimization is overall more economical and delivers superior performance than analogous simulations carried out with gradient-free optimizers.
Measurement reduction in variational quantum algorithms
- Physics
- 2020
Variational quantum algorithms are promising applications of noisy intermediate-scale quantum (NISQ) computers. These algorithms consist of a number of separate prepare-and-measure experiments that…
Exploring entanglement and optimization within the Hamiltonian Variational Ansatz
- PhysicsArXiv
- 2020
This paper focuses on a special family of quantum circuits called the Hamiltonian Variational Ansatz (HVA), which takes inspiration from the quantum approximation optimization algorithm and adiabatic quantum computation and exhibits favorable structural properties and numerically observes that the optimization landscape of HVA becomes almost trap free when the ansatz is over-parameterized.
Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz
- Computer ScienceQuantum Science and Technology
- 2018
The application of VQE to the simulation of molecular energies using the unitary coupled cluster (UCC) ansatz is studied and an analytical method to compute the energy gradient is proposed that reduces the sampling cost for gradient estimation by several orders of magnitude compared to numerical gradients.
Efficient variational simulation of non-trivial quantum states
- PhysicsSciPost Physics
- 2019
We provide an efficient and general route for preparing non-trivial
quantum states that are not adiabatically connected to unentangled
product states. Our approach is a hybrid quantum-classical…
The Variational Quantum Eigensolver: A review of methods and best practices
- Computer SciencePhysics Reports
- 2022
Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers
- Computer Science
- 2019
This work presents a measurement strategy based on a low-rank factorization of the two-electron integral tensor that provides a cubic reduction in term groupings over prior state-of-the-art and enables measurement times three orders of magnitude smaller than those suggested by commonly referenced bounds for the largest systems.