The Next Generation Space Telescope will depart from the traditional means of providing high optical quality and stability, namely use of massive structures. Instead, a benign orbital environment will provide stability for a large, flexible, lightweight deployed structure, and active wavefront controls will compensate misalignments and figure errors induced during launch and cool-down on orbit. This paper presents a baseline architecture for NGST wavefront controls, including initial capture and alignment, segment phasing, wavefront sensing and deformable mirror control. Simulations and analyses illustrate expected scientific performance with respect to figure error, misalignments, and thermal deformation.
Advanced space telescopes which will eventually replace the Hubble Space Telescope (HST) will have 8-20 m diameter apertures. Primary mirrors (PM's) of these dimensions will fold to fit into the space launcher. By necessity, these mirrors will be extremely lightweight and flexible. The historical approaches to mirror designs, where the mirror is made as rigid as possible to maintain figure and to serve as the anchor for the entire telescope, can no longer be applied. New design concepts and verifications will depend entirely on analytical methods to predict optical performance. Integrated modeling of the structural, thermal, and optical performance of such mirrors is becoming the tool for advanced space mirror designs. This paper discusses some of the tasks and study results which are currently the basis for the design and integrated modeling studies ofthe Next Generation Space Telescope (NGST).
Since early 2020, non-pharmaceutical interventions (NPIs)—implemented at varying levels of severity and based on widely-divergent perspectives of risk tolerance—have been the primary means to control SARS-CoV-2 transmission. This paper aims to identify how risk tolerance and vaccination rates impact the rate at which a population can return to pre-pandemic contact behavior. To this end, we developed a novel mathematical model and we used techniques from feedback control to inform data-driven decision-making. We use this model to identify optimal levels of NPIs across geographical regions in order to guarantee that hospitalizations will not exceed given risk tolerance thresholds. Results are shown for the state of Colorado, United States, and they suggest that: coordination in decision-making across regions is essential to maintain the daily number of hospitalizations below the desired limits; increasing risk tolerance can decrease the number of days required to discontinue NPIs, at the cost of an increased number of deaths; and if vaccination uptake is less than 70%, at most levels of risk tolerance, return to pre-pandemic contact behaviors before the early months of 2022 may newly jeopardize the healthcare system. The sooner we can acquire population-level vaccination of greater than 70%, the sooner we can safely return to pre-pandemic behaviors.
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