135 citations · 263 across the 8 of their papers we have counts for
4 papers · 1 filter
Improved maximum-likelihood quantum amplitude estimation
Adam Callison, Dan E. Browne
Quantum amplitude estimation is a key subroutine in a number of powerful quantum algorithms, including quantum-enhanced Monte Carlo simulation and quantum machine learning. Maximum…
Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond
Adam Callison, Nicholas Chancellor
Hybrid quantum-classical algorithms are central to much of the current research in quantum computing, particularly when considering the noisy intermediate-scale quantum (NISQ) era,…
Comparing the hardness of MAX 2-SAT problem instances for quantum and classical algorithms
Puya Mirkarimi, Adam Callison, Lewis Light +2
An algorithm for a particular problem may find some instances of the problem easier and others harder to solve, even for a fixed input size. We numerically analyse the relative har…
Using copies to improve precision in continuous-time quantum computing
Jemma Bennett, Adam Callison, Tom O'Leary +3
In the quantum optimisation setting, we build on a scheme introduced by Young et al [PRA 88, 062314, 2013], where physical qubits in multiple copies of a problem encoded into an Is…