1 citations · 1 across the 5 of their papers we have counts for
8 papers · 1 filter
Impact of Data Loss in Postprocessing on Training and Inference of Quantum Neural Networks
Soraya V. Panambalom, Edoardo Altamura, Nick Chancellor +1
As quantum hardware scales to larger devices, the classical software layers that interface with it must evolve in step. Postprocessing routines developed and tested primarily in si…
Zeno Blockade Enabling Photonic Quantum Optimization
Mohammad-Ali Miri, Uchenna Chukwu, Nicholas Chancellor
In this work we explore the potential of implementing an optical quantum optimizer using non-linear optics, specifically using sum-frequency generation and/or two photon absorption…
Quantum annealing and condensed matter physics
Viv Kendon, Nicholas Chancellor
Quantum annealing leverages the properties of interacting quantum spin systems to solve computational problems, typically optimisation problems. Current hardware now has capabiliti…
Improving success probability in the LHZ parity embedding by computing with quantum walks
Jemma Bennett, Nicholas Chancellor, Viv Kendon +1
The LHZ parity embedding is one of the front-running methods for implementing difficult-to-engineer long-range interactions in quantum optimisation problems. Continuous-time quantu…
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…
Advantages of multistage quantum walks over QAOA
Lasse Gerblich, Tamanna Dasanjh, Horatio Q. X. Wong +4
Methods to find the solution state for optimization problems encoded into Ising Hamiltonians are a very active area of current research. In this work we compare the quantum approxi…