Cover Image

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

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Jones, Benjamin D. M., Mineh, Lana, Montanaro, Ashley
Format:	Preprint
Published:	2024
Subjects:	Quantum Physics Machine Learning Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A supplemental investigation of non-linearity in quantum generative models with respect to simulatability and optimization
by: Gili, Kaitlin, et al.
Published: (2023)

Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms
by: Srimahajariyapong, Kasidit, et al.
Published: (2025)

Modeling stochastic eye tracking data: A comparison of quantum generative adversarial networks and Markov models
by: Bhandari, Shailendra, et al.
Published: (2024)

Non-binary artificial neuron with phase variation implemented on a quantum computer
by: de Borba, Jhordan Silveira, et al.
Published: (2024)

Experimental verification of the quantum nature of a neural network
by: Patrascu, Andrei T.
Published: (2022)

Method for noise-induced regularization in quantum neural networks
by: Kuzmin, Viacheslav, et al.
Published: (2024)

Quantum evolutionary algorithm for TSP combinatorial optimisation problem
by: Ma, Yijiang, et al.
Published: (2024)

Role of scrambling and noise in temporal information processing with quantum systems
by: Xiong, Weijie, et al.
Published: (2025)

Superposed parameterised quantum circuits
by: Patapovich, Viktoria, et al.
Published: (2025)

Zero-shot Quantum Neural Architecture Search
by: Dao, Tung, et al.
Published: (2026)

Representation Theorem for Matrix Product States
by: Guo, Erdong, et al.
Published: (2021)

Hybrid-Quantum Neural Architecture Search for The Proximal Policy Optimization Algorithm
by: Zada, Moustafa
Published: (2025)

DeQompile: quantum circuit decompilation using genetic programming for explainable quantum architecture search
by: Xie, Shubing, et al.
Published: (2025)

Evolving generalist controllers to handle a wide range of morphological variations
by: Triebold, Corinna, et al.
Published: (2023)

Speeding-up Evolutionary Algorithms to solve Black-Box Optimization Problems
by: Echevarrieta, Judith, et al.
Published: (2023)

EQNN: Enhanced Quantum Neural Network
by: Chen, Abel C. H.
Published: (2024)

Data re-uploading in Quantum Machine Learning for time series: application to traffic forecasting
by: Schetakis, Nikolaos, et al.
Published: (2025)

CTRQNets & LQNets: Continuous Time Recurrent and Liquid Quantum Neural Networks
by: Mayorga, Alejandro Antonio, et al.
Published: (2024)

Exploring Biological Neuronal Correlations with Quantum Generative Models
by: Hernandes, Vinicius, et al.
Published: (2024)

Neural Architecture Search for Quantum Autoencoders
by: Agha, Hibah, et al.
Published: (2025)

Optimizing quantum circuits with evolutionary algorithms for stable Boolean gates, elementary cellular automata, and highly entangled quantum states
by: Bhandari, Shailendra, et al.
Published: (2024)

Experimental differentiation and extremization with analog quantum circuits
by: Philip, Evan, et al.
Published: (2025)

Quantum memristors for neuromorphic quantum machine learning
by: Lamata, Lucas
Published: (2024)

Benchmarking Swarm Optimization Algorithms for Parameter Initialization in the Quantum Approximate Optimization Algorithm
by: Bhat, Shashank Sanjay, et al.
Published: (2025)

A practical applicable quantum-classical hybrid ant colony algorithm for the NISQ era
by: Qiu, Qian, et al.
Published: (2024)

Quantum-limited stochastic optical neural networks operating at a few quanta per activation
by: Ma, Shi-Yuan, et al.
Published: (2023)

Evolving a multi-population evolutionary-QAOA on distributed QPUs
by: Schiavello, Francesca, et al.
Published: (2024)

Comparison of Reservoir Computing topologies using the Recurrent Kernel approach
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)

Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model
by: Renau, Quentin, et al.
Published: (2025)

Epidemic Modeling using Hybrid of Time-varying SIRD, Particle Swarm Optimization, and Deep Learning
by: Kumar, Naresh, et al.
Published: (2024)

Benchmarking local Hebbian learning rules for memory storage and prototype extraction
by: Lansner, Anders, et al.
Published: (2026)

Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes
by: Yazdani, Danial, et al.
Published: (2024)

Active Learning in Symbolic Regression with Physical Constraints
by: Medina, Jorge, et al.
Published: (2023)

Prediction, Generation of WWTPs microbiome community structures and Clustering of WWTPs various feature attributes using DE-BP model, SiTime-GAN model and DPNG-EPMC ensemble clustering algorithm with modulation of microbial ecosystem health
by: Dai, Mingzhi, et al.
Published: (2025)

Generalization Ability of Feature-based Performance Prediction Models: A Statistical Analysis across Benchmarks
by: Nikolikj, Ana, et al.
Published: (2024)

Towards graph neural networks for provably solving convex optimization problems
by: Qian, Chendi, et al.
Published: (2025)

Continual learning with the neural tangent ensemble
by: Benjamin, Ari S., et al.
Published: (2024)

A Review of 315 Benchmark and Test Functions for Machine Learning Optimization Algorithms and Metaheuristics with Mathematical and Visual Descriptions
by: Naser, M. Z., et al.
Published: (2024)

Efficient lattice field theory simulation using adaptive normalizing flow on a resistive memory-based neural differential equation solver
by: Xu, Meng, et al.
Published: (2025)

Spiking Brain Compression: Post-Training Second-order Compression for Spiking Neural Networks
by: Shi, Lianfeng, et al.
Published: (2025)