Biomedical subjects

Douglas G MacMartin

Publications and source records attributed to Douglas G MacMartin.

3 recordsLinked to original sources

PubMed2004

Control and alignment of segmented-mirror telescopes: matrices, modes, and error propagation.

Starting from the successful Keck telescope design, we construct and analyze the control matrix for the active control system of the primary mirror of a generalized segmented-mirror telescope, with up to 1000 segments and including an alternative sensor geometry to the one used at Keck. In particular we examine the noise propagation of the matrix and its consequences for both seeing-limited and diffraction-limited observations. The associated problem of optical alignment of such a primary mirror is also analyzed in terms of the distinct but related matrices that govern this latter problem.

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PubMed2004

Measurement accuracy in control of segmented-mirror telescopes.

Design concepts for future large optical telescopes have highly segmented primary mirrors, with the out-of-plane degrees of freedom actively controlled. We estimate the contribution to errors in controlling the primary mirror that results from sensor noise and, in particular, compare mechanical measurements of relative segment motion with optical wave-front information. Data from the Keck telescopes are used to obtain realistic estimates of the achievable noise due to mechanical sensors. On the basis of these estimates, mechanical sensors will be more accurate than wave-front information for any of the telescope design concepts currently under consideration, and therefore supplemental wave-front sensors are not required for real-time figure control. Furthermore, control system errors due to sensor noise will not significantly degrade either seeing-limited or diffraction-limited observations.

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PubMed2003

Local, hierarchic, and iterative reconstructors for adaptive optics.

Adaptive optics systems for future large optical telescopes may require thousands of sensors and actuators. Optimal reconstruction of phase errors using relative measurements requires feedback from every sensor to each actuator, resulting in computational scaling for n actuators of n2. The optimum local reconstructor is investigated, wherein each actuator command depends only on sensor information in a neighboring region. The resulting performance degradation "global" modes is quantified analytically, and two approaches are considered for recovering global performance. Combining local and global estimators in a two-layer hierarchic architecture yields computations scaling with n(4/3); extending this approach to multiple layers yields linear scaling. An alternative approach that maintains a local structure is to allow actuator commands to depend on both local sensors and prior local estimates. This iterative approach is equivalent to a temporal low-pass filter on global information and gives a scaling of n(3/2). The algorithms are simulated by using data from the Palomar Observatory adaptive optics system. The analysis is general enough to also be applicable to active optics or other systems with many sensors and actuators.

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