@misc{10481/90778,
year = {2023},
month = {12},
url = {https://hdl.handle.net/10481/90778},
abstract = {Quantum machine learning (QML) is a discipline that holds the promise of
revolutionizing data processing and problem-solving. However, dissipation
and noise arising from the coupling with the environment are commonly
perceived as major obstacles to its practical exploitation, as they impact the
coherence and performance of the utilized quantum devices. Significant
efforts have been dedicated to mitigating and controlling their negative effects
on these devices. This perspective takes a different approach, aiming to
harness the potential of noise and dissipation instead of combating them.
Surprisingly, it is shown that these seemingly detrimental factors can provide
substantial advantages in the operation of QML algorithms under certain
circumstances. Exploring and understanding the implications of adapting
QML algorithms to open quantum systems opens up pathways for devising
strategies that effectively leverage noise and dissipation. The recent works
analyzed in this perspective represent only initial steps toward uncovering
other potential hidden benefits that dissipation and noise may offer. As
exploration in this field continues, significant discoveries are anticipated that
could reshape the future of quantum computing.},
organization = {Ministry of Economic
Affairs and Digital Transformation of the Spanish Government through the QUANTUM ENIA project call—Quantum Spain project},
organization = {European Union through the Recovery, Transformation, and Resilience
Plan - NextGenerationEU within the framework of the “Digital Spain
2026 Agenda”},
organization = {Junta de Andalucía,
under projects P20-00617 and US-1380840 (ERDF)},
organization = {Spanish Ministry of Science, Innovation, and Universities under grants
Nos. PID2019-104002GB-C21 and PID2019-104002GB- C22},
organization = {Grant PID2022-136228NB-C22 funded by MCIN/AEI/
10.13039/501100011033 and by “ERDF- A way of making Europe.”},
publisher = {Wiley-VCH GmbH},
title = {Benefits of Open Quantum Systems for Quantum Machine Learning},
doi = {10.1002/qute.202300247},
author = {Olivera Atencio, María Laura and Lamata, Lucas and Casado Pascual, Jesús},
}