Advice for stirring your online community and fostering engagement
When you enter into any new area of science, you almost always find
yourself with a baffling new language of technical terms to learn before you can converse with the experts. This is certainly true in astronomy both in terms of terms that refer to the cosmos and terms that describe the tools of the trade, the most prevalent being the telescope. So to get us off of first base, let’s define some of the key terms that pertain to telescopes to help you be able to talk to them more intelligently. The first area of specialization in telescopes has to do with the types of telescopes people use. The three designs of telescopes that most people use are the Refractor, the Reflector and the Schmidt Cassegrain telescope. The refractor telescope uses a convex lens to focus the light on the eyepiece. The reflector telescope has a concave lens which means it bends in. It uses mirrors to focus the image that you eventually see. The Schmidt Cassegrain telescope uses an involved system of mirrors to capture the image you want to see. A binocular telescope uses a set of telescopes mounted and synchronized so your view of the sky is 3-D. Beyond the basic types, other terms refer to parts of the telescope or to the science behind how telescopes work. Collimation is a term for how well tuned the telescope is to give you a good clear image of what you are looking at. You want your telescope to have good collimation so you are not getting a false image of the celestial body. Aperture is a fancy word for how big the lens of your telescope is. But it’s an important word because the aperture of the lens is the key to how powerful your telescope is. Magnification has nothing to do with it, its all in the aperture.
22459 comments
keramogranit kypit_axMr
сколько стоит керамогранит http://www.keramogranit-kupit-gs-2.ru .
Comment Linkdatasets_qrKa
Discover new opportunities with open-access ML datasets across domains
Comment Linksample data sets https://www.machine-learning-dataset.com/ .
datasets_gfKa
Empower your data science team with ML-ready datasets
Comment Linkcsv dataset https://www.machine-learning-dataset.com/ .
datasets_dvKa
Reliable datasets for training, testing, and validating machine learning models
Comment Linkdataset https://machine-learning-dataset.com .
datasets_btKa
Sentiment analysis, classification, and more: datasets that deliver value
Comment Linkgood dataset [url=https://machine-learning-dataset.com/]good dataset[/url] .
datasets_nuKa
Everything you need to train AI: datasets, metadata, and version control
Comment Linkdata set example [url=http://www.machine-learning-dataset.com/]http://www.machine-learning-dataset.com/[/url] .
datasets_xsKa
Access diverse machine learning datasets for better model performance
Comment Linkdata set example http://www.machine-learning-dataset.com/ .
datasets_spKa
Machine learning begins with data: discover thousands of quality datasets
Comment Linkfree datasets machine-learning-dataset.com .
Vse Pesni Ynnv_dfPi
уннв все треки уннв все треки .
Comment Linkdatasets_lhKa
Data that drives results: expertly curated datasets for machine learning
Comment Linkdata set example https://machine-learning-dataset.com .