Numerical simulations for the SAXO+ upgrade: Performance analysis of the adaptive optics system Article Swipe
Charles Goulas
,
Raphaël Galicher
,
Fabrice Vidal
,
Johan Mazoyer
,
Florian Ferreira
,
Arnaud Sevin
,
A. Boccaletti
,
É. Gendron
,
Clémentine Béchet
,
Michel Tallon
,
M. Langlois
,
Caroline Kulcsár
,
Henri‐François Raynaud
,
Nicolas Galland
,
Laura Schreiber
,
Isaac Bernardino Dinis
,
F. Wildi
,
G. Chauvin
,
J. Milli
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.17644
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.17644
SPHERE, operating at the VLT since 2014, is currently one of the high-contrast instruments with a higher performance. Its adaptive optics system, known as SAXO, will be upgraded to SAXO+, which features the addition of a second stage of adaptive optics. This stage will use a near-infrared pyramid wavefront sensor to record images of fainter exoplanets around redder stars. In this work, we compare the performance of SAXO and SAXO+. We look for the optimal values of the key system parameters of SAXO+ for various science cases and turbulence conditions. We performed numerical simulations using COMPASS, an end-to-end adaptive optics simulation tool. We simulated perfect coronagraph images of an on-axis point source, and we minimized the residual starlight intensity between 3 and 5 $λ/D$ as a performance criterion. The explored parameter space includes science cases, turbulence conditions, and key system parameters. In every science case and turbulence condition, SAXO+ reduces the residual starlight intensity inside the correction zone of the second stage by a factor of ten compared to SAXO. The optimal first stage gain is lower for SAXO+ than for SAXO alone. We quantified the gain in performance of SAXO+ when changing the second stage frequency from 2 kHz to 3 kHz, and we conclude that 2 kHz may be sufficient for most realistic conditions. We give the optimal first stage gain as well as the first and second stage frequencies for every seeing, coherence time, and science case. Finally, we find that a 2 ${λ_{\mathrm{WFS}}}/D$ pyramid modulation radius is a good trade-off between performance and robustness against varying turbulence conditions. This study shows that the future SAXO+ system will outperform the current SAXO system in all studied cases.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2406.17644
- https://arxiv.org/pdf/2406.17644
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400065175
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400065175Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2406.17644Digital Object Identifier
- Title
-
Numerical simulations for the SAXO+ upgrade: Performance analysis of the adaptive optics systemWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-06-25Full publication date if available
- Authors
-
Charles Goulas, Raphaël Galicher, Fabrice Vidal, Johan Mazoyer, Florian Ferreira, Arnaud Sevin, A. Boccaletti, É. Gendron, Clémentine Béchet, Michel Tallon, M. Langlois, Caroline Kulcsár, Henri‐François Raynaud, Nicolas Galland, Laura Schreiber, Isaac Bernardino Dinis, F. Wildi, G. Chauvin, J. MilliList of authors in order
- Landing page
-
https://arxiv.org/abs/2406.17644Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2406.17644Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2406.17644Direct OA link when available
- Concepts
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Upgrade, Computer science, Numerical analysis, Optics, Geology, Physics, Mathematics, Operating system, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.as | 23, 124, 223, 225 |
| abstract_inverted_index.at | 2 |
| abstract_inverted_index.be | 26, 210 |
| abstract_inverted_index.by | 162 |
| abstract_inverted_index.in | 187, 276 |
| abstract_inverted_index.is | 7, 175, 250 |
| abstract_inverted_index.of | 10, 34, 38, 53, 66, 76, 81, 107, 158, 165, 189 |
| abstract_inverted_index.to | 28, 50, 168, 200 |
| abstract_inverted_index.we | 62, 113, 204, 241 |
| abstract_inverted_index.Its | 18 |
| abstract_inverted_index.The | 128, 170 |
| abstract_inverted_index.VLT | 4 |
| abstract_inverted_index.all | 277 |
| abstract_inverted_index.and | 68, 87, 112, 121, 137, 145, 203, 228, 237, 256 |
| abstract_inverted_index.for | 72, 83, 177, 180, 212, 232 |
| abstract_inverted_index.kHz | 199, 208 |
| abstract_inverted_index.key | 78, 138 |
| abstract_inverted_index.may | 209 |
| abstract_inverted_index.one | 9 |
| abstract_inverted_index.ten | 166 |
| abstract_inverted_index.the | 3, 11, 32, 64, 73, 77, 115, 150, 155, 159, 185, 193, 218, 226, 266, 272 |
| abstract_inverted_index.use | 44 |
| abstract_inverted_index.SAXO | 67, 181, 274 |
| abstract_inverted_index.This | 41, 262 |
| abstract_inverted_index.case | 144 |
| abstract_inverted_index.find | 242 |
| abstract_inverted_index.from | 197 |
| abstract_inverted_index.gain | 174, 186, 222 |
| abstract_inverted_index.give | 217 |
| abstract_inverted_index.good | 252 |
| abstract_inverted_index.kHz, | 202 |
| abstract_inverted_index.look | 71 |
| abstract_inverted_index.most | 213 |
| abstract_inverted_index.than | 179 |
| abstract_inverted_index.that | 206, 243, 265 |
| abstract_inverted_index.this | 60 |
| abstract_inverted_index.well | 224 |
| abstract_inverted_index.when | 191 |
| abstract_inverted_index.will | 25, 43, 270 |
| abstract_inverted_index.with | 14 |
| abstract_inverted_index.zone | 157 |
| abstract_inverted_index.2014, | 6 |
| abstract_inverted_index.SAXO+ | 82, 148, 178, 190, 268 |
| abstract_inverted_index.SAXO, | 24 |
| abstract_inverted_index.SAXO. | 169 |
| abstract_inverted_index.case. | 239 |
| abstract_inverted_index.cases | 86 |
| abstract_inverted_index.every | 142, 233 |
| abstract_inverted_index.first | 172, 220, 227 |
| abstract_inverted_index.known | 22 |
| abstract_inverted_index.lower | 176 |
| abstract_inverted_index.point | 110 |
| abstract_inverted_index.shows | 264 |
| abstract_inverted_index.since | 5 |
| abstract_inverted_index.space | 131 |
| abstract_inverted_index.stage | 37, 42, 161, 173, 195, 221, 230 |
| abstract_inverted_index.study | 263 |
| abstract_inverted_index.time, | 236 |
| abstract_inverted_index.tool. | 101 |
| abstract_inverted_index.using | 94 |
| abstract_inverted_index.which | 30 |
| abstract_inverted_index.work, | 61 |
| abstract_inverted_index.$λ/D$ | 123 |
| abstract_inverted_index.SAXO+, | 29 |
| abstract_inverted_index.SAXO+. | 69 |
| abstract_inverted_index.alone. | 182 |
| abstract_inverted_index.around | 56 |
| abstract_inverted_index.cases, | 134 |
| abstract_inverted_index.cases. | 279 |
| abstract_inverted_index.factor | 164 |
| abstract_inverted_index.future | 267 |
| abstract_inverted_index.higher | 16 |
| abstract_inverted_index.images | 52, 106 |
| abstract_inverted_index.inside | 154 |
| abstract_inverted_index.optics | 20, 99 |
| abstract_inverted_index.radius | 249 |
| abstract_inverted_index.record | 51 |
| abstract_inverted_index.redder | 57 |
| abstract_inverted_index.second | 36, 160, 194, 229 |
| abstract_inverted_index.sensor | 49 |
| abstract_inverted_index.stars. | 58 |
| abstract_inverted_index.system | 79, 139, 269, 275 |
| abstract_inverted_index.values | 75 |
| abstract_inverted_index.SPHERE, | 0 |
| abstract_inverted_index.against | 258 |
| abstract_inverted_index.between | 119, 254 |
| abstract_inverted_index.compare | 63 |
| abstract_inverted_index.current | 273 |
| abstract_inverted_index.fainter | 54 |
| abstract_inverted_index.on-axis | 109 |
| abstract_inverted_index.optics. | 40 |
| abstract_inverted_index.optimal | 74, 171, 219 |
| abstract_inverted_index.perfect | 104 |
| abstract_inverted_index.pyramid | 47, 247 |
| abstract_inverted_index.reduces | 149 |
| abstract_inverted_index.science | 85, 133, 143, 238 |
| abstract_inverted_index.seeing, | 234 |
| abstract_inverted_index.source, | 111 |
| abstract_inverted_index.studied | 278 |
| abstract_inverted_index.system, | 21 |
| abstract_inverted_index.various | 84 |
| abstract_inverted_index.varying | 259 |
| abstract_inverted_index.COMPASS, | 95 |
| abstract_inverted_index.Finally, | 240 |
| abstract_inverted_index.adaptive | 19, 39, 98 |
| abstract_inverted_index.addition | 33 |
| abstract_inverted_index.changing | 192 |
| abstract_inverted_index.compared | 167 |
| abstract_inverted_index.conclude | 205 |
| abstract_inverted_index.explored | 129 |
| abstract_inverted_index.features | 31 |
| abstract_inverted_index.includes | 132 |
| abstract_inverted_index.residual | 116, 151 |
| abstract_inverted_index.upgraded | 27 |
| abstract_inverted_index.coherence | 235 |
| abstract_inverted_index.currently | 8 |
| abstract_inverted_index.frequency | 196 |
| abstract_inverted_index.intensity | 118, 153 |
| abstract_inverted_index.minimized | 114 |
| abstract_inverted_index.numerical | 92 |
| abstract_inverted_index.operating | 1 |
| abstract_inverted_index.parameter | 130 |
| abstract_inverted_index.performed | 91 |
| abstract_inverted_index.realistic | 214 |
| abstract_inverted_index.simulated | 103 |
| abstract_inverted_index.starlight | 117, 152 |
| abstract_inverted_index.trade-off | 253 |
| abstract_inverted_index.wavefront | 48 |
| abstract_inverted_index.condition, | 147 |
| abstract_inverted_index.correction | 156 |
| abstract_inverted_index.criterion. | 127 |
| abstract_inverted_index.end-to-end | 97 |
| abstract_inverted_index.exoplanets | 55 |
| abstract_inverted_index.modulation | 248 |
| abstract_inverted_index.outperform | 271 |
| abstract_inverted_index.parameters | 80 |
| abstract_inverted_index.quantified | 184 |
| abstract_inverted_index.robustness | 257 |
| abstract_inverted_index.simulation | 100 |
| abstract_inverted_index.sufficient | 211 |
| abstract_inverted_index.turbulence | 88, 135, 146, 260 |
| abstract_inverted_index.conditions, | 136 |
| abstract_inverted_index.conditions. | 89, 215, 261 |
| abstract_inverted_index.coronagraph | 105 |
| abstract_inverted_index.frequencies | 231 |
| abstract_inverted_index.instruments | 13 |
| abstract_inverted_index.parameters. | 140 |
| abstract_inverted_index.performance | 65, 126, 188, 255 |
| abstract_inverted_index.simulations | 93 |
| abstract_inverted_index.performance. | 17 |
| abstract_inverted_index.high-contrast | 12 |
| abstract_inverted_index.near-infrared | 46 |
| abstract_inverted_index.${λ_{\mathrm{WFS}}}/D$ | 246 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 19 |
| citation_normalized_percentile.value | 0.63487662 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |