712 citations · 749 across the 10 of their papers we have counts for
10 papers
Global zero-excitation state preparation through subsystem cooling
Kerstin Beer, Daniel Burgarth
Preparing interacting quantum systems in low-energy or ground states is a fundamental task in quantum simulation and quantum information processing. In realistic settings, dissipat…
Quantum neural networks
Kerstin Beer
This PhD thesis combines two of the most exciting research areas of the last decades: quantum computing and machine learning. We introduce dissipative quantum neural networks (DQNN…
Dissipative quantum generative adversarial networks
Kerstin Beer, Gabriel Müller
Noisy intermediate-scale quantum (NISQ) devices build the first generation of quantum computers. Quantum neural networks (QNNs) gained high interest as one of the few suitable quan…
Training Quantum Neural Networks on NISQ Devices
Kerstin Beer, Daniel List, Gabriel Müller +2
The advent of noisy intermediate-scale quantum (NISQ) devices offers crucial opportunities for the development of quantum algorithms. Here we evaluate the noise tolerance of two qu…
Quantum machine learning of graph-structured data
Kerstin Beer, Megha Khosla, Julius Köhler +1
Graph structures are ubiquitous throughout the natural sciences. Here we consider graph-structured quantum data and describe how to carry out its quantum machine learning via quant…
No Free Lunch for Quantum Machine Learning
Kyle Poland, Kerstin Beer, Tobias J. Osborne
The ultimate limits for the quantum machine learning of quantum data are investigated by obtaining a generalisation of the celebrated No Free Lunch (NFL) theorem. We find a lower b…
Efficient Learning for Deep Quantum Neural Networks
Kerstin Beer, Dmytro Bondarenko, Terry Farrelly +3
Neural networks enjoy widespread success in both research and industry and, with the imminent advent of quantum technology, it is now a crucial challenge to design quantum neural n…
From categories to anyons: a travelogue
Kerstin Beer, Dmytro Bondarenko, Alexander Hahn +8
In this paper we provide an overview of category theory, focussing on applications in physics. The route we follow is motivated by the final goal of understanding anyons and topolo…
Contextuality and bundle diagrams
Kerstin Beer, Tobias J. Osborne
Contextuality describes the nontrivial dependence of measurement outcomes on particular choices of jointly measurable observables. In this work we review and generalize the bundle…
Phase context decomposition of diagonal unitaries for higher-dimensional systems
Kerstin Beer, Friederike Anna Dziemba
We generalize an efficient decomposition method for diagonal operators by Welch et al. to qudit systems. The phase-context aware method focusses on cascaded entanglers whose decomp…