3 citations · 3 across the 5 of their papers we have counts for
5 papers · 1 filter
Cavity-Enhanced Collective Quantum Processing with Polarization-Encoded Qubits
Kamil Wereszczyński, Józef Cyran, Adam Brzezowski +4
We introduce a cavity-enhanced optical architecture for collective quantum processing in which logical qubits are encoded in the polarization subspace of recirculating intracavity…
FRQI Pairs method for image classification using Quantum Recurrent Neural Network
Rafał Potempa, Michał Kordasz, Sundas Naqeeb Khan +4
This study aims to introduce the FRQI Pairs method to a wider audience, a novel approach to image classification using Quantum Recurrent Neural Networks (QRNN) with Flexible Repres…
GEQIE Framework for Rapid Quantum Image Encoding
Rafał Potempa, Michał Kordasz, Józef P. Cyran +2
This work presents a Python framework named after the General Equation of Quantum Image Encoding (GEQIE). The framework creates the image-encoding state using a unitary gate, which…
Deep learning as a tool for quantum error reduction in quantum image processing
Krzysztof Werner, Kamil Wereszczyński, Rafał Potempa +1
Despite the limited availability and quantum volume of quantum computers, quantum image representation is a widely researched area. Currently developed methods use quantum entangle…
Cosine series quantum sampling method with applications in signal and image processing
Kamil Wereszczyński, Agnieszka Michalczuk, Damian Pęszor +3
A novel family of Cosine series Quantum Sampling (QCoSamp) operators appropriate for quantum computing is described. The development of quantum algorithms, analogous to classical a…