Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver | Paper Citation Record

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Noisy intermediate-scale quantum algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Variational quantum algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Observing ground-state properties of the Fermi-Hubbard model using a scalable algorithm on a quantum computer

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Quantum Threat Timeline Report 2022

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Progress towards practical quantum variational algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Strategies for solving the Fermi-Hubbard model on near-term quantum com- puters

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Efficient quantum measurement of Pauli operators in the presence of finite sampling error

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Algorithms for optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Essentials of Metaheuristics

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Numerical optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver An overview of gradient descent optimization algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Sequential minimal optimization for quantum- classical hybrid algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver A Jacobi Diagonalization and Anderson Acceleration Algorithm For Variational Quantum Algorithm Parameter Optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Convergence of a block coordinate descent method for nondifferentiable minimiza- tion

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Structure optimization for pa- rameterized quantum circuits

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Quantum analytic descent

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Quantum natural gradient

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Using models to improve optimizers for variational quantum algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver

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This paper cites The variational quantum eigensolver: a review of methods and best practices.

Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver The variational quantum eigensolver: a review of methods and best practices

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver VQE method: a short survey and recent developments

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Variational ansatz-based quantum simulation of imaginary time evolution

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Classical optimizers for noisy intermediate-scale quantum devices

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This paper cites https://scikit-quant.readthedocs.io/en/latest/.

Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver https://scikit-quant.readthedocs.io/en/latest/

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Performance comparison of optimization methods on variational quantum algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Optimizing quantum heuristics with meta-learning

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Robust and efficient algorithms for high-dimensional black-box quantum optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Performance of hybrid quantum-classical variational heuristics for combi- natorial optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Practical optimization for hybrid quantum-classical algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Avoiding local minima in varia- tional quantum eigensolvers with the natural gradient optimizer

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Learning to learn with quantum neural networks via classical neural networks

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Classical Benchmarks for Variational Quantum Eigensolver Simulations of the Hubbard Model

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver General parameter-shift rules for quantum gradients

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Estimating the gradient and higher- order derivatives on quantum hardware

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Optuna: A Next-generation Hyperparameter Optimization Framework

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver An overview of the simultaneous perturbation method for efficient optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Implementation of the simultaneous perturbation algorithm for stochastic optimiza- tion

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver DEAP: Evolutionary Algorithms Made Easy

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Completely derandomized self-adaptation in evolu- tion strategies

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver The CMA Evolution Strategy: A Tutorial

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Implementing the Nelder-Mead simplex algorithm with adaptive parameters

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver A simplex method for function minimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver A direct search optimization method that models the objective and constraint func- tions by linear interpolation

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver A view of algorithms for optimization without derivatives

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver On the natural gradient for variational quantum eigensolver

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Natural gradient works efficiently in learning

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver New insights and perspectives on the natural gradient method

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Low-depth gradient measurements can improve conver- gence in variational hybrid quantum-classical algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver On the momentum term in gradient descent learning algorithms

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver ADADELTA: An Adaptive Learning Rate Method

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Adaptive subgradient methods for online learning and stochastic optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Adam: A Method for Stochastic Optimization

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Benchmarking a wide range of optimisers for solving the Fermi-Hubbard model using the variational quantum eigensolver Unresolved cited work

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