Adaptive Optics Systems VI 2018
DOI: 10.1117/12.2314407
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High Contrast Imaging for Python (HCIPy): an open-source adaptive optics and coronagraph simulator

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Cited by 100 publications
(65 citation statements)
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“…of this method is available in the open-source package HCIPy (Por et al 2018). We show some examples in Figure 5.…”
Section: Parameter Study For One-sided Dark Zonesmentioning
confidence: 99%
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“…of this method is available in the open-source package HCIPy (Por et al 2018). We show some examples in Figure 5.…”
Section: Parameter Study For One-sided Dark Zonesmentioning
confidence: 99%
“…This research made use of HCIPy, an open-source object-oriented framework written in Python for performing end-to-end simulations of high-contrast imaging instruments (Por et al 2018). Additionally we used the numerical library NumPy (Walt et al 2011) and visualizations were made using the library Matplotlib (Hunter 2007).…”
mentioning
confidence: 99%
“…We then Fraunhofer propagate these electric fields to the focal plane and compute the intensity using hcipy. 18 We create an ideal point spread function (PSF) by Fraunhofer propagating a clear aperture matching the shape of the valid DM actuators. We simulate the effect of an ideal coronagraph by subtracting this ideal PSF from the non-predictive and predictive PSFs.…”
Section: Synthetic Contrast Curvementioning
confidence: 99%
“…13. For comparison, we simulate the PSF of a single aperture over 12% bandwidth using HCIPy (Por et al, 2018). The simulations visually match the on-sky data apart from the AO residuals (mostly wind-driven halo) and low-order aberrations.…”
Section: Experimental Results For a Double-grating Vector Vortex Coromentioning
confidence: 99%
“…ERC Starting Grant 678194 (FALCONER); thank our all our collaborators from the LBT for helping us acquire the first on-sky results with the double-grating vAPP, especially Phil Hinz, Steve Ertel, Jordan Stone, and Eckhart Arthur Spalding. This research made use of HCIPy (Por et al, 2018), an open-source object-oriented framework written in Python for performing end-to-end simulations of high-contrast imaging instruments. We thank Christoph Keller for the many fruitful discussions, which helped improve the results presented in this work.…”
Section: Fundingmentioning
confidence: 99%