Alignment-free gapless segmented mirror for large telescope (Conference Presentation)

2018 ◽  
Author(s):  
Yasuhiro Nakahori ◽  
Yuji Ikeda ◽  
Shinji Mukai ◽  
Yuki Nishi ◽  
Hidehito Himeno ◽  
...  
Keyword(s):  
Large Telescope ◽  
Alignment Free ◽  
Segmented Mirror

scholarly journals The Extreme Structures of our Universe

2019 ◽  
Author(s):  
Vincent Icke
Keyword(s):  
Human Impact ◽  
Large Telescope ◽  
Galileo Galilei ◽  
Artificial Structures ◽  
The World ◽  
Segmented Mirror ◽  
The Universe

My story is a tale of extremes. Extreme artificial structures that we have built on and around planet Earth. Extreme natural structures that exist in our Universe, and extreme structures in our mind, when we try to understand how this all works. Of all the possible artificial structures, consider telescopes. The first one, invented by Johannes Lipperhey of Zeeland, was soon copied by Galileo Galilei, which dramatically changed our understanding of the Universe. The object itself did not look very dramatic, but its human impact was extreme. Currently, engineers in Chile are building the European Extremely Large Telescope, which will contain a segmented mirror with a total diameter of 39 meters. The building of this extreme instrument could more than cover the full grounds of the original Leiden Observatory, which is the oldest still operating observatory in the world.

B. Large Telescope Engineering Operations

1966 ◽  
Vol 27 ◽  
pp. 200-209
Keyword(s):  
Large Telescope ◽  
Advance Planning

Whitford : The next phase of the program has to do with advance planning of the instruments themselves, to make the logistics of operation simple and foolproof. I call first on Mr Rule to speak on ‘thinking ahead’.

scholarly journals Alignment-Free Sensing Module for Absolute and Incremental Lines in Linear Positioning System Based on Tunneling-Magnetoresistance Sensors

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4137
Author(s):  
Chia-Chang Lee ◽  
Yu-Shen Yen ◽  
Chih-Huang Lai
Keyword(s):  
Thin Film Deposition ◽  
Film Deposition ◽  
Alignment Error ◽  
Positioning System ◽  
Large Signal ◽  
Detection Scheme ◽  
Alignment Free ◽  
Reference Layer ◽  
Working Distance ◽  
Incremental Lines

An alignment-free sensing module for the positioning system based on tunneling magnetoresistive (TMR) sensors with an absolute-incremental-integrated scale is demonstrated. The sensors of the proposed system for both lines consist of identical layer stacks; therefore, all sensors can be fabricated in identical processes from thin film deposition to device patterning on a single substrate. Consequently, the relative position of the sensors can be predefined at the lithography stage and the alignment error between sensors caused by the manual installation is completely eliminated. Different from the existing sensing scheme for incremental lines, we proposed to utilize the magnetic tunnel junctions with a perpendicular anisotropy reference layer and an in-plane anisotropy sensing layer. The sensors are placed parallel to the scale plane with magnetization of the sensing layer in the plane, which show the capability of polarity detection for the absolute line and reveal sinusoidal output signal for the incremental line. Furthermore, due to the large signal of TMR, the working distance can be further improved compared with conventional sensors. In addition, the cost of the positioning system is expected to be lowered, since all the sensors are fabricated in the same process without extra installation. Our design may pave a new avenue for the positioning system based on a magnetic detection scheme.

Hybrid Planning System for In-Space Robotic Assembly of Telescopes using Segmented Mirror Tiles

2021 ◽  
Author(s):  
Juan Martinez-Moritz ◽  
Ismael Rodriguez ◽  
Korbinian Nottensteiner ◽  
Jean-Pascal Lutze ◽  
Peter Lehner ◽  
...  
Keyword(s):  
Planning System ◽  
Robotic Assembly ◽  
Segmented Mirror ◽  
Hybrid Planning

scholarly journals A Tip–Tilt and Piston Detection Approach for Segmented Telescopes

Photonics ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 3
Author(s):  
Shun Qin ◽  
Wai Kin Chan
Keyword(s):  
Error Detection ◽  
Phase Retrieval ◽  
Dynamic Range ◽  
Detection Accuracy ◽  
Wavefront Sensing ◽  
Next Generation ◽  
Large Aperture ◽  
Detection Approach ◽  
Segmented Mirror ◽  
And Control

Accurate segmented mirror wavefront sensing and control is essential for next-generation large aperture telescope system design. In this paper, a direct tip–tilt and piston error detection technique based on model-based phase retrieval with multiple defocused images is proposed for segmented mirror wavefront sensing. In our technique, the tip–tilt and piston error are represented by a basis consisting of three basic plane functions with respect to the x, y, and z axis so that they can be parameterized by the coefficients of these bases; the coefficients then are solved by a non-linear optimization method with the defocus multi-images. Simulation results show that the proposed technique is capable of measuring high dynamic range wavefront error reaching 7λ, while resulting in high detection accuracy. The algorithm is demonstrated as robust to noise by introducing phase parameterization. In comparison, the proposed tip–tilt and piston error detection approach is much easier to implement than many existing methods, which usually introduce extra sensors and devices, as it is a technique based on multiple images. These characteristics make it promising for the application of wavefront sensing and control in next-generation large aperture telescopes.

scholarly journals Prokaryotic virus host predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Congyu Lu ◽  
Zheng Zhang ◽  
Zena Cai ◽  
Zhaozhong Zhu ◽  
Ye Qiu ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Functional Characterization ◽  
Gaussian Model ◽  
Software Tool ◽  
Biological Properties ◽  
Rapid Identification ◽  
Taxonomic Assignment ◽  
Genus Level ◽  
Alignment Free ◽  
Archaeal Viruses

Abstract Background Viruses are ubiquitous biological entities, estimated to be the largest reservoirs of unexplored genetic diversity on Earth. Full functional characterization and annotation of newly discovered viruses requires tools to enable taxonomic assignment, the range of hosts, and biological properties of the virus. Here we focus on prokaryotic viruses, which include phages and archaeal viruses, and for which identifying the viral host is an essential step in characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus, which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts, which needs improvements at both accuracy and usability. Here we develop a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. Results We present here Prokaryotic virus Host Predictor (PHP), a software tool using a Gaussian model, to predict hosts for prokaryotic viruses using the differences of k-mer frequencies between viral and host genomic sequences as features. PHP gave a host prediction accuracy of 34% (genus level) on the VirHostMatcher benchmark dataset and a host prediction accuracy of 35% (genus level) on a new dataset containing 671 viruses and 60,105 prokaryotic genomes. The prediction accuracy exceeded that of two alignment-free methods (VirHostMatcher and WIsH, 28–34%, genus level). PHP also outperformed these two alignment-free methods much (24–38% vs 18–20%, genus level) when predicting hosts for prokaryotic viruses which cannot be predicted by the BLAST-based or the CRISPR-spacer-based methods alone. Requiring a minimal score for making predictions (thresholding) and taking the consensus of the top 30 predictions further improved the host prediction accuracy of PHP. Conclusions The Prokaryotic virus Host Predictor software tool provides an intuitive and user-friendly API for the Gaussian model described herein. This work will facilitate the rapid identification of hosts for newly identified prokaryotic viruses in metagenomic studies.

scholarly journals Use of an Alignment-Free Method for the Geographical Discrimination of GTPVs Based on the GPCR Sequences

2021 ◽  
Vol 9 (4) ◽  
pp. 855
Author(s):  
Tesfaye Rufael Chibssa ◽  
Yang Liu ◽  
Melaku Sombo ◽  
Jacqueline Kasiiti Lichoti ◽  
Janchivdorj Erdenebaatar ◽  
...  
Keyword(s):  
Lumpy Skin Disease ◽  
Alignment Free ◽  
Central Asian ◽  
Source Tracing ◽  
Geographical Regions ◽  
Gpcr Gene ◽  
Geographical Discrimination ◽  
Sequence Profiles ◽  
G Protein Coupled ◽  
Effective Source

Goatpox virus (GTPV) belongs to the genus Capripoxvirus, together with sheeppox virus (SPPV) and lumpy skin disease virus (LSDV). GTPV primarily affects sheep, goats and some wild ruminants. Although GTPV is only present in Africa and Asia, the recent spread of LSDV in Europe and Asia shows capripoxviruses could escape their traditional geographical regions to cause severe outbreaks in new areas. Therefore, it is crucial to develop effective source tracing of capripoxvirus infections. Earlier, conventional phylogenetic methods, based on limited samples, identified three different nucleotide sequence profiles in the G-protein-coupled chemokine receptor (GPCR) gene of GTPVs. However, this method did not differentiate GTPV strains by their geographical origins. We have sequenced the GPCR gene of additional GTPVs and analyzed them with publicly available sequences, using conventional alignment-based methods and an alignment-free approach exploiting k-mer frequencies. Using the alignment-free method, we can now classify GTPVs based on their geographical origin: African GTPVs and Asian GTPVs, which further split into Western and Central Asian (WCA) GTPVs and Eastern and Southern Asian (ESA) GTPVs. This approach will help determine the source of introduction in GTPV emergence in disease-free regions and detect the importation of additional strains in disease-endemic areas.

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