On-sky tests of the CuReD and HWR fast wavefront reconstruction algorithms with CANARY Article Swipe
Urban Bitenc
,
Alastair Basden
,
Nazim A. Bharmal
,
Tim Morris
,
N. A. Dipper
,
É. Gendron
,
Fabrice Vidal
,
Damien Gratadour
,
Gérard Rousset
,
Richard M. Myers
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stv003
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stv003
CuReD (Cumulative Reconstructor with domain Decomposition) and HWR (Hierarchical Wavefront Reconstructor) are novel wavefront reconstruction algorithms for the Shack–Hartmann wavefront sensor, used in the single-conjugate adaptive optics. For a high-order system they are much faster than the traditional matrix–vector-multiplication method. We have developed three methods for mapping the reconstructed phase into the deformable mirror actuator commands and have tested both reconstructors with the CANARY instrument. We find out that the CuReD reconstructor runs stably only if the feedback loop is operated as a leaky integrator, whereas HWR runs stably with the conventional integrator control. Using the CANARY telescope simulator we find that the Strehl ratio (SR) obtained with CuReD is slightly higher than that of the traditional least-squares estimator (LSE). We demonstrate that this is because the CuReD algorithm has a smoothing effect on the output wavefront. The SR of HWR is slightly lower than that of LSE. We have tested both reconstructors extensively on-sky. They perform well and CuReD achieves a similar SR as LSE. We compare the CANARY results with those from a computer simulation and find good agreement between the two.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/mnras/stv003
- https://academic.oup.com/mnras/article-pdf/448/2/1199/3566282/stv003.pdf
- OA Status
- bronze
- Cited By
- 14
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2069785689
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Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2069785689Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/mnras/stv003Digital Object Identifier
- Title
-
On-sky tests of the CuReD and HWR fast wavefront reconstruction algorithms with CANARYWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-02-10Full publication date if available
- Authors
-
Urban Bitenc, Alastair Basden, Nazim A. Bharmal, Tim Morris, N. A. Dipper, É. Gendron, Fabrice Vidal, Damien Gratadour, Gérard Rousset, Richard M. MyersList of authors in order
- Landing page
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https://doi.org/10.1093/mnras/stv003Publisher landing page
- PDF URL
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https://academic.oup.com/mnras/article-pdf/448/2/1199/3566282/stv003.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/mnras/article-pdf/448/2/1199/3566282/stv003.pdfDirect OA link when available
- Concepts
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Wavefront, Physics, Deformable mirror, Algorithm, Adaptive optics, Integrator, Strehl ratio, Smoothing, Telescope, Estimator, Wavefront sensor, Optics, Phase (matter), Computer science, Mathematics, Computer vision, Voltage, Quantum mechanics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
14Total citation count in OpenAlex
- Citations by year (recent)
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2020: 2, 2019: 2, 2018: 5, 2017: 2, 2016: 2Per-year citation counts (last 5 years)
- References (count)
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22Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.89098779 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |