Statistical-mechanical approaches to the problem of atmospheric compensation in adaptive optics

Y. Saika; H. Nishimori

doi:10.1063/1.2204551

Statistical-mechanical approaches to the problem of atmospheric compensation in adaptive optics

Y. Saika, H. Nishimori

INF - Applied Information Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We formulate the problem of atmospheric compensation appearing in adaptive optics using the statistical-mechanical technology developed for information science. Our method uses the equilibrium statistical mechanics of the Q-Ising model corresponding to the maximizer of the posterior marginal estimate in the language of probabilistic information processing. Then, using the Monte Carlo simulation for a typical wave-front in adaptive optics clarifies that this method works well if we appropriately select the model of the true prior according to the sensitivity of measurement.

Original language	English
Title of host publication	FLOW DYNAMICS
Subtitle of host publication	The Second International Conference on Flow Dynamics
Pages	516-519
Number of pages	4
DOIs	https://doi.org/10.1063/1.2204551
Publication status	Published - 2006 May 5
Event	FLOW DYNAMICS: The Second International Conference on Flow Dynamics - Sendai, Japan Duration: 2005 Nov 16 → 2005 Nov 18

Publication series

Name	AIP Conference Proceedings
Volume	832
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Other

Other	FLOW DYNAMICS: The Second International Conference on Flow Dynamics
Country	Japan
City	Sendai
Period	05/11/16 → 05/11/18

ASJC Scopus subject areas

Physics and Astronomy(all)

Access to Document

10.1063/1.2204551

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Saika, Y & Nishimori, H 2006, Statistical-mechanical approaches to the problem of atmospheric compensation in adaptive optics. in FLOW DYNAMICS: The Second International Conference on Flow Dynamics. AIP Conference Proceedings, vol. 832, pp. 516-519, FLOW DYNAMICS: The Second International Conference on Flow Dynamics, Sendai, Japan, 05/11/16. https://doi.org/10.1063/1.2204551

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