Search: onr:"swepub:oai:research.chalmers.se:d7d562da-eb7e-4841-87cc-cf06b33dc8da" >
Parameter estimatio...
Parameter estimation from quantum-jump data using neural networks
-
- Rinaldi, Enrico (author)
- RIKEN
-
- González Lastre, Manuel (author)
- Universidad Autonoma de Madrid (UAM)
-
- García Herreros, Sergio (author)
- Universidad Autonoma de Madrid (UAM)
-
show more...
-
- Ahmed, Shahnawaz, 1995 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
-
- Khanahmadi, Maryam, 1994 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
-
- Nori, F. (author)
- University of Michigan,RIKEN
-
- Sánchez Munõz, Carlos (author)
- Universidad Autonoma de Madrid (UAM),CSIC - Instituto de Fisica Fundamental (IFF)
-
show less...
-
(creator_code:org_t)
- 2024
- 2024
- English.
-
In: Quantum Science and Technology. - 2058-9565. ; 9:3
- Related links:
-
https://research.cha... (primary) (free)
-
show more...
-
https://research.cha...
-
https://doi.org/10.1...
-
show less...
Abstract
Subject headings
Close
- We present an inference method utilizing artificial neural networks for parameter estimation of a quantum probe monitored through a single continuous measurement. Unlike existing approaches focusing on the diffusive signals generated by continuous weak measurements, our method harnesses quantum correlations in discrete photon-counting data characterized by quantum jumps. We benchmark the precision of this method against Bayesian inference, which is optimal in the sense of information retrieval. By using numerical experiments on a two-level quantum system, we demonstrate that our approach can achieve a similar optimal performance as Bayesian inference, while drastically reducing computational costs. Additionally, the method exhibits robustness against the presence of imperfections in both measurement and training data. This approach offers a promising and computationally efficient tool for quantum parameter estimation with photon-counting data, relevant for applications such as quantum sensing or quantum imaging, as well as robust calibration tasks in laboratory-based settings.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
Keyword
- quantum metrology
- photon counting
- deep learning
- neural networks
- quantum parameter estimation
- quantum jumps
Publication and Content Type
- art (subject category)
- ref (subject category)
Find in a library
To the university's database