6 papers
DreamQAS: Learning a Decision-Useful World Model for VQE-Efficient Quantum Architecture Search
Jiayang Niu, Yan Wang, Jie Li +4
Reinforcement-learning-based quantum architecture search (RL-QAS) repeatedly optimizes a variational quantum eigensolver (VQE) after extending a circuit, although circuit construct…
HamQASBench: A Hamiltonian-Informed Diagnostic Benchmark for Evaluating Quantum Architecture Search
Jiayang Niu, Akib Karim, Yan Wang +5
Quantum Architecture Search (QAS) automates the design of parameterized quantum circuits for variational quantum algorithms, yet existing benchmarks organize instances by molecular…
Quantum Jacobi-Davidson Method
Shaobo Zhang, Akib Karim, Harry M. Quiney +1
Computing electronic structures of quantum systems is a key task underpinning many applications in photonics, solid-state physics, and quantum technologies. This task is typically…
Hybrid Action Reinforcement Learning for Quantum Architecture Search
Jiayang Niu, Yan Wang, Jie Li +4
Reinforcement learning-based Quantum Architecture Search (QAS) offers a promising avenue for automating the design of variational quantum circuits, but existing methods typically d…
Symmetry-Checking in Band Structure Calculations on a Noisy Quantum Computer
Shaobo Zhang, Akib Karim, Harry M. Quiney +1
Band crossings in electronic band structures play an important role in determining the electronic, topological, and transport properties in solid-state systems, making them central…
Fast and Noise-aware Machine Learning Variational Quantum Eigensolver Optimiser
Akib Karim, Shaobo Zhang, Muhammad Usman
The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm for preparing ground states in the current era of noisy devices. The classical component of the al…