most citedKernel Alignment for Quantum Support Vector Machines Using Genetic Algorithms

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

quant-ph20262 cited

Kernel Alignment for Quantum Support Vector Machines Using Genetic Algorithms

Floyd M. Creevey, Jamie A. Heredge, Martin E. Sevior +1

The data encoding circuits used in quantum support vector machine (QSVM) kernels play a crucial role in their classification accuracy. However, manually designing these circuits po…

quant-ph2025

Fully convolutional 3D neural network decoders for surface codes with syndrome circuit noise

Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman

Artificial Neural Networks (ANNs) are a promising approach to the decoding problem of Quantum Error Correction (QEC), but have observed consistent difficulty when generalising perf…

quant-ph2025

What can unitary sequences tell us about multi-time physics?

Gregory A. L. White, Felix A. Pollock, Lloyd C. L. Hollenberg +2

Multi-time quantum processes are endowed with the same richness as multipartite states, including temporal entanglement and exotic causal structures. However, experimentally probin…

quant-ph2025

Quantum autoencoders using mixed reference states

Hailan Ma, Gary J. Mooney, Ian R. Petersen +2

One of the fundamental tasks in quantum information theory is quantum data compression, which can be realized via quantum autoencoders that first compress quantum states to low-dim…

physics.app-ph2025

Machine learning assisted tracking of magnetic objects using quantum diamond magnetometry

Fernando Meneses, Christopher T. -K. Lew, Anand Sivamalai +5

Remote magnetic sensing can be used to monitor the position of objects in real-time, enabling ground transport monitoring, underground infrastructure mapping and hazardous detectio…