Where to Search For Life: Evidence from narrative sources with established predictive efficacy

The search for habitable planets, and even for ``Earth 2.0'', is a major driver in contemporary astronomy. However selecting target fields to prioritise for such searches presents a challenge. Here we establish a statistical analysis of the appearance of constellation names in science fiction magazines of the pulp era, evaluating the most commonly mentioned constellations and thus those which the science fiction community collectively identify as the most likely locations to find life. Given that the predictive power of science fiction is well established, we suggest that these locations might be prioritised by searches for extrasolar biospheres.

Big Data in Astronomy: Surveys, Catalogs, Databases and Archives

We present the modern situation in astronomy, where Big Data coming from the Universe put new tasks for catalogizing, storage, archiving, analysis and usage of the scientific information. The two major characteristics of modern astronomy are multiwavelength (MW) studies (from \gamma-ray to radio, as well as multi-messenger studies, using also neutrinos, gravitational waves, etc.) and Big Data (including data acquisition, storage and analysis). Present astronomical databases and archives contain billions of objects observed in various wavelengths, both Galactic and extragalactic, and the vast amount of data on them allows new studies and discoveries. Astronomers deal with big numbers. Surveys are the main source for discovery of astronomical objects and accumulation of observational data for further analysis, interpretation, and achieving scientific results. We review the main characteristics of astronomical surveys, we compare photographic and digital eras of astronomical studies (including the development of wide-field observations), we give the present state of MW surveys, and we discuss the Big Data in astronomy and related topics of Virtual Observatories and Computational Astrophysics. The review includes many numbers and data that can be compared to have a possibly overall understanding on the studied Universe, cosmic numbers and their relationship to modern computational possibilities.

sbpy: A Python module for small-body planetary astronomy

The Luminosity Function and Stellar Evolution.

The evolutionary significance of the observed luminosity function for main-sequence stars in the solar neighborhood is discussed. The hypothesis is made that stars move off the main sequence after burning about 10 per cent of their hydrogen mass and that stars have been created at a uniform rate in the solar neighborhood for the last five billion years. Using this hypothesis and the observed luminosity function, the rate of star creation as a function of stellar mass is calculated. The total number and mass of stars which have moved off the main sequence is found to be comparable with the total number of white dwarfs and with the total mass of all fainter main-sequence stars, respectively.

The UMIST Database for Astrochemistry 2022

Context. Detailed astrochemical models are a key component to interpret the observations of interstellar and circumstellar molecules since they allow important physical properties of the gas and its evolutionary history to be deduced. <BR /> Aims: We update one of the most widely used astrochemical databases to reflect advances in experimental and theoretical estimates of rate coefficients and to respond to the large increase in the number of molecules detected in space since our last release in 2013. <BR /> Methods: We present the sixth release of the UMIST Database for Astrochemistry (UDfA), a major expansion of the gas-phase chemistry that describes the synthesis of interstellar and circumstellar molecules. Since our last release, we have undertaken a major review of the literature which has increased the number of reactions by over 40% to a total of 8767 and increased the number of species by over 55% to 737. We have made a particular attempt to include many of the new species detected in space over the past decade, including those from the QUIJOTE and GOTHAM surveys, as well as providing references to the original data sources. <BR /> Results: We use the database to investigate the gas-phase chemistries appropriate to both O-rich and C-rich conditions in TMC-1 and to the circumstellar envelope of the C-rich AGB star IRC+10216 and identify successes and failures of gas-phase only models. <BR /> Conclusions: This update is a significant improvement to the UDfA database. For both the dark cloud and C-rich circumstellar envelope models, calculations match around 60% of the abundances of observed species to within an order of magnitude. There are a number of detected species, however, that are not included in the model either because their gas-phase chemistry is unknown or because they are likely formed via surface reactions on icy grains. Future laboratory and theoretical work is needed to include such species in reaction networks.

The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package

The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates on the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project.