3 papers
quant-ph2025
Quantum Circuits, Feature Maps, and Expanded Pseudo-Entropy: Analysis of Encoding Real-World Data into a Quantum Computer
Andrew Vlasic, Payal Solanki, Anh Pham
This manuscript introduces a computationally efficient method to calculate the nonlinearity of a quantum feature map, as well as a method for determining whether a quantum feature…
quant-ph2025
Empirical Power of Quantum Encoding Methods for Binary Classification
Gennaro De Luca, Andrew Vlasic, Michael Vitz +1
Quantum machine learning is one of the many potential applications of quantum computing, each of which is hoped to provide some novel computational advantage. However, quantum mach…
quant-ph2024
Towards structure-preserving quantum encodings
Arthur J. Parzygnat, Tai-Danae Bradley, Andrew Vlasic +1
Harnessing the potential computational advantage of quantum computers for machine learning tasks relies on the uploading of classical data onto quantum computers through what are c…