552 citations · 1.4k across the 32 of their papers we have counts for
33 papers
Learning the Complexity of Weakly Noisy Quantum States
Yusen Wu, Bujiao Wu, Yanqi Song +2
Quantifying the complexity of quantum states is a longstanding key problem in various subfields of science, ranging from quantum computing to the black-hole theory. The lower bound…
Orbital Expansion Variational Quantum Eigensolver: Enabling Efficient Simulation of Molecules with Shallow Quantum Circuit
Yusen Wu, Zigeng Huang, Jinzhao Sun +3
In the noisy-intermediate-scale-quantum era, Variational Quantum Eigensolver (VQE) is a promising method to study ground state properties in quantum chemistry, materials science, a…
Quantum Optimisation for Continuous Multivariable Functions by a Structured Search
Edric Matwiejew, Jason Pye, Jingbo B. Wang
Solving optimisation problems is a promising near-term application of quantum computers. Quantum variational algorithms leverage quantum superposition and entanglement to optimise…
Quantum Phase Recognition via Quantum Kernel Methods
Yusen Wu, Bujiao Wu, Jingbo Wang +1
The application of quantum computation to accelerate machine learning algorithms is one of the most promising areas of research in quantum algorithms. In this paper, we explore the…
Quantum optimisation via maximally amplified states
Tavis Bennett, Jingbo B. Wang
This paper presents the Maximum Amplification Optimisation Algorithm (MAOA), a novel quantum algorithm designed for combinatorial optimisation in the restricted circuit depth conte…
QuOp_MPI: a framework for parallel simulation of quantum variational algorithms
Edric Matwiejew, Jingbo B. Wang
QuOp_MPI is a Python package designed for parallel simulation of quantum variational algorithms. It presents an object-orientated approach to quantum variational algorithm design a…