activity
20182026
most citedEfficient Learning for Deep Quantum Neural Networks

712 citations · 842 across the 7 of their papers we have counts for

collaborators

7 papers

quant-ph2026

Testing measurement-based computational phases of quantum matter on a quantum processor

Ryohei Weil, Dmytro Bondarenko, Arnab Adhikary +1

Many symmetry protected or symmetry enriched phases of quantum matter have the property that every ground state in a given such phase endows measurement based quantum computation w…

quant-ph2024★ 3 cited

Measurement-based quantum machine learning

Luis Mantilla Calderón, Robert Raussendorf, Polina Feldmann +1

Quantum machine learning (QML) leverages quantum computing for classical inference, furnishes the processing of quantum data with machine-learning methods, and provides quantum alg…

quant-ph2023★ 3 cited

Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networks

Dmytro Bondarenko, Robert Salzmann, Viktoria-S. Schmiesing

Recurrent neural networks play an important role in both research and industry. With the advent of quantum machine learning, the quantisation of recurrent neural networks has becom…

quant-ph2021★ 1 cited

Constructing k-local parent Lindbladians for matrix product density operators

Dmytro Bondarenko

Matrix product density operators (MPDOs) are an important class of states with interesting properties. Consequently, it is important to understand how to prepare these states exper…

quant-ph2019★ 123 cited

Quantum autoencoders to denoise quantum data

Dmytro Bondarenko, Polina Feldmann

Entangled states are an important resource for quantum computation, communication, metrology, and the simulation of many-body systems. However, noise limits the experimental prepar…

quant-ph2019★ 712 cited

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…

quant-ph2018

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…