- IRAF github page: “Image Reduction and Analysis Facility” (IRAF) is one of the oldest but most useful tools nowadays when dealing with astronomical data. It was developed in the 1980’s decade by the National Optical Astronomy Observatories (NOAO) in Tucson, Arizona. However, development and maintenance of IRAF is discontinued since 2012. The latest release had a large number of problems, including major license issues and security bugs. Although it’s old, it’s utility,
compatibility and wide of use in the astronomy world is making their users to find workarounds and overpass bugs in order to continue using it. One of the most promising packages involved is the Pyraf wrapper for Python.
- GitHub project: The official GitHub repository for the project (discontinued).
- Pyraf: A very interesting module in Python to include the tools in the IRAF package.
- Customer support: An (intented to be) actualized webpage to support customers using IRAF.
- SExtractor: Source-Extractor (SExtractor) is a program that builds a catalogue of objects from an astronomical image.
- DS9: SAOImageDS9 is an astronomical imaging and data visualization application. DS9 supports FITS images and binary tables, multiple frame buffers, region manipulation, and many scale algorithms and colormaps.
- TOPCAT: TOPCAT is an interactive graphical viewer and editor for tabular data. Its aim is to provide most of the facilities that astronomers need for analysis and manipulation of source catalogues and other tables, though it can be used for non-astronomical data as well.
Python:
- Astropy: A core package for all astronomers and astrophysicists in Python.
- PyTorch: This is my recommended framework for Deep Learning and Machine Learning tasks. It is more integrated with Python, which is cool once you get used to this language and it provides high manipulation capabilities in certain black-box scenarios where other alternatives usually decay. Other alternatives for the same purposes are, in order of relevance: Tensorflow, Keras, fastai
- Jupyter Notebooks: This is one of the most interesting features for interactive and exploratory Python out there. Those widely-used and extremely handy notebooks are nowadays an standard to effectively communicate and transmit science and Python routines. As an enhancemente, Jupyter Lab provides a more useful GUI and extensions that can be enabled one-by-one.
- Essential Core in Python: What to say about eternal scientific packages? Top 5 for me: numpy, pandas, matplotlib, scipy, scikit-learn
- Python standard library: As everyone knows (or should), there are plenty of full-integrated standard libraries in Python for most common tasks. Also, there is little effort to create your oun functions and accomplish most of the things.
Specific areas:
- Vapor: Interesting software for running simulations in 2D/3D. It is well known in solar physics. An interesting alternative is VISIT
- Docker: Docker is a CaaS(Container-as-a-Service) platform, you can build your own software from predefined packages from multi-architectures. Generally, you don’t need anything else but to know Docker to start any software instance on your computer. As an enhance, nvidia-docker provides you with a GPU runtime to leverage your docker containers.
- NASA: NASA(National Aeronautics and Space Administration) Home link.
- ESA: ESA(European Space Agency) Home link.
- NASA APOD: APOD(Astronomy Picture of the Day) Archive.
- STScI:
- AAS: AAS(American Astronomical Society) is the major organization of professional astronomers in North America.
- EAS: EAS(European Astronomical Society) promotes and advances astronomy in Europe.
- IAU: IAU(International Astronomical Union) was founded in 1919. Its mission is to promote and safeguard the science of astronomy in all its aspects, including research, communication, education and development, through international cooperation.
- NAOC: NAOC(National Astronomical Observatories of China)
- AstroWeb: AstroWeb is a collection of pointers to astronomical Internet Resources.
Courses/Resources:
Databases/Surveys:
- CDS: “Centre de Données astronomiques de Strasbourg”(CDS) has popular tools like: Simbad, Vizier, Aladin, X-Match, and all integrated in a simple search. It is also a meta-searcher for catalogues and tabular data related to our astronomical queries.
- SDSS: SDSS(Sloan Digital Sky Survey) has created the most detailed three-dimensional maps of the Universe ever made, with deep multi-color images of one third of the sky, and spectra for more than three million astronomical objects.
- 2MASS: 2MASS(Two Micron All-Sky Survey) from IPAC has uniformly scanned the entire sky in three near-infrared bands to detect and characterize point sources brighter than about 1 mJy in each band, with signal-to-noise ratio (SNR) greater than 10, using a pixel size of 2.0”.
- NASA/IPAD Extragalactic Database: NED(NASA/IPAD Extragalactic Database) is a comprehensive database of multiwavelength data for extragalactic objects, providing a systematic, ongoing fusion of information integrated from hundreds of large sky surveys and tens of thousands of research publications.
- Pan-STARRS: Pan-STARRS(Panoramic Survey Telescope and Rapid Response System) is a system for wide-field astronomical imaging developed and operated by the Institute for Astronomy at the University of Hawaii. Pan-STARRS1 (PS1) is the first part of Pan-STARRS to be completed and is the basis for both Data Releases 1 and 2 (DR1 and DR2).
- HST, Mikulski Archive: HST(Hubble Space Telescope) website.
Articles/Papers:
Talks:
Jobs:
- UNet detector : This is a project involving an encoder-decoder CNN and SExtractor to make image segmentation on .fits images of a galaxy simulation (VELA galaxies). Then, we can catalogue the clumps properties.
- Astrophysical Gravitational Lenses : A repo from a course in gravitational lenses that reproduces some of their properties in Python.
- Astrophysical Waves : A forked repo taken from Coursera that sounds very interesting to me. It is an entire course about waves in astrophysics and their environments. The code tries to reproduce waves in diferent contexts in interactive Jupyter notebooks.
last_updated: 2021-01-28
(I!) This a personal webpage with some information of interest in the topic selected. Some of these webpages are not intended to be guides, but to provide useful tips for those interested in a topic and to tell my personal walkthrough.