Quantum Kernel Regression and Variational Quantum Regression for the CCS Prediction of Dissolved Organic Matter: A Comparative Benchmarking Study
- DOI
- 10.1021/jasms.6c00135
- Published
- 2026-09-10
- Container
- Journal of the American Society for Mass Spectrometry
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/jasms.6c00135,
title = {Quantum Kernel Regression
and Variational Quantum
Regression for the CCS Prediction of Dissolved Organic Matter: A Comparative
Benchmarking Study},
author = {Sadollah Ebrahimi and Armand Soldera and Céline Guéguen},
year = {2026},
journal = {Journal of the American
Society for Mass Spectrometry},
doi = {10.1021/jasms.6c00135},
url = {https://doi.org/10.1021/jasms.6c00135}
}RIS
TY - JOUR TI - Quantum Kernel Regression and Variational Quantum Regression for the CCS Prediction of Dissolved Organic Matter: A Comparative Benchmarking Study AU - Sadollah Ebrahimi AU - Armand Soldera AU - Céline Guéguen PY - 2026 JO - Journal of the American Society for Mass Spectrometry DO - 10.1021/jasms.6c00135 UR - https://doi.org/10.1021/jasms.6c00135 ER -
APA
Ebrahimi, S., Soldera, A., & Guéguen, C. (2026). Quantum Kernel Regression and Variational Quantum Regression for the CCS Prediction of Dissolved Organic Matter: A Comparative Benchmarking Study. Journal of the American Society for Mass Spectrometry. https://doi.org/10.1021/jasms.6c00135
Source records
- crossref · retrieved 2026-11-10T11:37:11.259Z