A novel fast and accurate pseudo-analytical simulation approach for MOAO
A novel fast and accurate pseudo-analytical simulation approach for MOAO
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一种新颖、快速、准确的 MOAO 伪分析模拟方法
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
G. Rousset
中科院分区：
文献类型：
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作者：
E. Gendron;A. Charara;A. Abdelfattah;D. Gratadour;D. Keyes;H. Ltaief;C. Morel;F. Vidal;A. Sevin;G. Rousset
多目标自适应光学（MOAO）是一种用于宽视场多目标光谱仪（MOS）的新型自适应光学（AO）技术。MOAO的目标是将专用的波前校正应用于分布在大视场（FOV）上的许多分离的小块，仅受望远镜的限制。每个可变形反射镜（DM）的控制是单独使用的相位的断层重建的基础上，从一些波前传感器（WFS）指向自然和人工引导星在现场的测量。我们已经开发了一种新的混合，伪分析模拟方案，介于端到端和纯分析方法之间，使我们能够详细模拟断层问题以及高保真度的噪声和混叠，并包括拟合和带宽误差，这要归功于基于傅立叶的代码。我们的层析成像方法基于最小均方误差（MMSE）重建器的计算，从中我们以数值方式推导出层析成像误差的协方差矩阵，包括混叠和传播噪声。然后，我们能够模拟与残差的协方差矩阵相关联的点扩散函数（PSF），就像PSF重建算法一样。我们的方法的优点是，我们计算相同的断层重建，将计算时，操作的真实的仪器，使我们的发展开辟了未来的天空实施的断层控制，加上联合PSF和性能估计的方式。主要挑战在于断层重建器的计算，其中涉及大型矩阵（通常为40 000 × 40 000个元素）的求逆。为了有效地执行此计算，我们选择了一种基于GPU作为加速器并使用优化的线性代数库的优化方法：莫尔斯（MORSE）相对于标准面向CPU的库（如英特尔MKL）提供了显著的加速。因为协方差矩阵是对称的，所以可以设想几种优化方案来进一步加速计算。优化重建器计算的速度不仅对于MOAO仪器的设计研究，而且对于系统的未来常规操作都具有重大意义，因为重建器必须定期更新以科普大气变化。
Multi-object adaptive optics (MOAO) is a novel adaptive optics (AO) technique for wide-field multi-object spectrographs (MOS). MOAO aims at applying dedicated wavefront corrections to numerous separated tiny patches spread over a large field of view (FOV), limited only by that of the telescope. The control of each deformable mirror (DM) is done individually using a tomographic reconstruction of the phase based on measurements from a number of wavefront sensors (WFS) pointing at natural and artificial guide stars in the field. We have developed a novel hybrid, pseudo-analytical simulation scheme, somewhere in between the end-to- end and purely analytical approaches, that allows us to simulate in detail the tomographic problem as well as noise and aliasing with a high fidelity, and including fitting and bandwidth errors thanks to a Fourier-based code. Our tomographic approach is based on the computation of the minimum mean square error (MMSE) reconstructor, from which we derive numerically the covariance matrix of the tomographic error, including aliasing and propagated noise. We are then able to simulate the point-spread function (PSF) associated to this covariance matrix of the residuals, like in PSF reconstruction algorithms. The advantage of our approach is that we compute the same tomographic reconstructor that would be computed when operating the real instrument, so that our developments open the way for a future on-sky implementation of the tomographic control, plus the joint PSF and performance estimation. The main challenge resides in the computation of the tomographic reconstructor which involves the inversion of a large matrix (typically 40 000 × 40 000 elements). To perform this computation efficiently, we chose an optimized approach based on the use of GPUs as accelerators and using an optimized linear algebra library: MORSE providing a significant speedup against standard CPU oriented libraries such as Intel MKL. Because the covariance matrix is symmetric, several optimization schemes can be envisioned to speedup even further the computation. Optimizing the speed of the reconstructor computation is of major interest not only for the design study of MOAO instruments, but also for future routine operations of the system as the reconstructor has to be updated regularly to cope for atmospheric variability.
MOAO 首次与 CANARY 进行空中演示
影响因子：
6.5
作者：
Gendron E
通讯作者：
Gendron E