5 papers
A Hybrid Quantum Neural Network to Analyse Big Experimental Powder X-ray Diffraction Data
H. Dong, S. D. M. Jacques, M. Q. Hlatshwayo +4
Quantitative analysis of experimental powder X-ray diffraction data remains challenging when evaluating complex multiphase materials and noisy measurements. We introduce a hybrid q…
Spectral Gap Informed Ramp QAOA
Kieran McDowall, Konstantinos Georgopoulos, Petros Wallden
A challenge with the Quantum Approximate Optimisation Algorithm (QAOA), and variational algorithms in general, is finding good variational parameters, a task which in itself can be…
Resource-efficient Quantum Algorithms for Selected Hamiltonian Subspace Diagonalization
Vincent Graves, Manqoba Q. Hlatshwayo, Theodoros Kapourniotis +1
Quantum algorithms for selecting a subspace of Hamiltonians to diagonalize have emerged as a promising alternative to variational algorithms in the NISQ era. So far, such algorithm…
Cross-Platform Benchmarking of Near-Term Quantum Optimisation Algorithms
Kieran McDowall, Theodoros Kapourniotis, Christopher Oliver +2
Quantum computers show potential for achieving computational advantage over classical computers, with many candidate applications in combinatorial optimisation. We present an appli…
A Review and Collection of Metrics and Benchmarks for Quantum Computers: definitions, methodologies and software
Deep Lall, Abhishek Agarwal, Weixi Zhang +15
Quantum computers have the potential to provide an advantage over classical computers in a number of areas. Numerous metrics to benchmark the performance of quantum computers, rang…