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Adam Callison
Researcher at Imperial College London
Publications - 9
Citations - 122
Adam Callison is an academic researcher from Imperial College London. The author has contributed to research in topics: Quantum walk & Hamiltonian (quantum mechanics). The author has an hindex of 5, co-authored 5 publications receiving 55 citations.
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Finding spin glass ground states using quantum walks
TL;DR: This work investigates the performance of continuous-time quantum walks as a tool for finding spin glass ground states, a problem that serves as a useful model for realistic optimization problems and uncover significant ways in which solving spin glass problems differs from applying quantum walks to the search problem.
Journal ArticleDOI
An energetic perspective on rapid quenches in quantum annealing
TL;DR: In this paper, the energy expectation value of different elements of the Hamiltonian was analyzed, and it was shown that monotonic quenches, where the strength of the problem Hamiltonian is consistently increased relative to fluctuation (driver) terms, will yield a better result on average than random guessing.
Journal ArticleDOI
Two quantum Ising algorithms for the shortest-vector problem
TL;DR: Two quantum algorithms are proposed to solve the shortest-vector problem, which could play an important role in designing new cryptosystems for the postquantum era.
Peer ReviewDOI
Hybrid quantum-classical algorithms in the noisy intermediate-scale quantum era and beyond
TL;DR: It is argued that the evolution of quantum computing is unlikely to be different: hybrid algorithms are likely to stay well past the NISQ era and even into full fault-tolerance, with the quantum processors augmenting the already powerful classical processors which exist by performing specialized tasks.
Journal ArticleDOI
Energetic Perspective on Rapid Quenches in Quantum Annealing
Adam Callison,Max Festenstein,Max Festenstein,Jie Chen,Laurentiu Nita,Viv Kendon,Nicholas Chancellor +6 more
TL;DR: It is found that a technique referred to as "pre-annealing" can significantly improve the performance of quantum walks and provide efficient heuristic estimates for Hamiltonian parameters, a key requirement for practical application of quantum annealing.