Optimizing fingerprinting experiments for parameter identification: Application to spin systems
| Autor: | Michael Tesch, Quentin Ansel, Steffen J. Glaser, Dominique Sugny |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Physics
Quantum Physics Dynamical systems theory Process (computing) Physical system FOS: Physical sciences 02 engineering and technology 021001 nanoscience & nanotechnology Optimal control 01 natural sciences Identification (information) Nuclear magnetic resonance 0103 physical sciences Curve fitting Limit (mathematics) Relaxation (approximation) 010306 general physics 0210 nano-technology Quantum Physics (quant-ph) Algorithm |
| DOI: | 10.48550/arxiv.1711.07658 |
| Popis: | We introduce the Optimal Fingerprinting Process which is aimed at accurately identifying the parameters which characterize the dynamics of a physical system. A database is first built from the time evolution of an ensemble of dynamical systems driven by a specific field, which is designed by optimal control theory to maximize the efficiency of the recognition process. Curve fitting is then applied to enhance the precision of the identification. As an illustrative example, we consider the estimation of the relaxation parameters of a spin- 1/2 particle. The experimental results are in good accordance with the theoretical computations. We show on this example a physical limit of the estimation process. Comment: 21 pages, 8 figures |
| Databáze: | OpenAIRE |
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