Publication:
Numerical Study of Dynamic Adaptive Phase Correction of Radiation Turbulent Distortions and Estimation of their Frequency Bandwidth with a Shack–Hartmann Wavefront Sensor

dc.contributor.authorBogachev, V. A.
dc.contributor.authorShnyagin, R. A.
dc.contributor.authorVolkov, M. V.
dc.contributor.authorStarikov, F. A.
dc.date.accessioned2024-12-25T14:35:49Z
dc.date.available2024-12-25T14:35:49Z
dc.date.issued2022
dc.description.abstract© 2022, Pleiades Publishing, Ltd.Abstract: The effect of limited operation speed of an adaptive optics system with a Shack–Hartmann wavefront sensor (WFS) on the efficiency of correction of dynamic laser beam phase distortions due to atmospheric turbulence is numerically studied. We suggest estimating the frequency bandwidth of significant turbulent distortions with a WFS, which is convenient from a practical point of view.
dc.format.extentС. 250-257
dc.identifier.citationNumerical Study of Dynamic Adaptive Phase Correction of Radiation Turbulent Distortions and Estimation of their Frequency Bandwidth with a Shack–Hartmann Wavefront Sensor / Bogachev, V.A. [et al.] // Atmospheric and Oceanic Optics. - 2022. - 35. - № 3. - P. 250-257. - 10.1134/S1024856022030174
dc.identifier.doi10.1134/S1024856022030174
dc.identifier.urihttps://www.doi.org/10.1134/S1024856022030174
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85132347337&origin=resultslist
dc.identifier.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000812522100010
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/28006
dc.relation.ispartofAtmospheric and Oceanic Optics
dc.titleNumerical Study of Dynamic Adaptive Phase Correction of Radiation Turbulent Distortions and Estimation of their Frequency Bandwidth with a Shack–Hartmann Wavefront Sensor
dc.typeArticle
dspace.entity.typePublication
oaire.citation.issue3
oaire.citation.volume35
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relation.isOrgUnitOfPublication.latestForDiscovery3d683db7-9a7b-4e1e-8011-ff80d8ac7d34
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