nbodykit
nbodykit: an open-source, massively parallel toolkit for large-scale structure. We present nbodykit, an open-source, massively parallel Python toolkit for analyzing large-scale structure (LSS) data. Using Python bindings of the Message Passing Interface (MPI), we provide parallel implementations of many commonly used algorithms in LSS. nbodykit is both an interactive and scalable piece of scientific software, performing well in a supercomputing environment while still taking advantage of the interactive tools provided by the Python ecosystem. Existing functionality includes estimators of the power spectrum, 2 and 3-point correlation functions, a Friends-of-Friends grouping algorithm, mock catalog creation via the halo occupation distribution technique, and approximate N-body simulations via the FastPM scheme. The package also provides a set of distributed data containers, insulated from the algorithms themselves, that enable nbodykit to provide a unified treatment of both simulation and observational data sets. nbodykit can be easily deployed in a high performance computing environment, overcoming some of the traditional difficulties of using Python on supercomputers. We provide performance benchmarks illustrating the scalability of the software. The modular, component-based approach of nbodykit allows researchers to easily build complex applications using its tools. The package is extensively documented at this http URL, which also includes an interactive set of example recipes for new users to explore. As open-source software, we hope nbodykit provides a common framework for the community to use and develop in confronting the analysis challenges of future LSS surveys.
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References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
Sorted by year (- Becker, Christoph; Eggemeier, Alexander; Davies, Christopher T.; Li, Baojiu: Proca-stinated cosmology. II: Matter, halo, and lensing statistics in the vector Galileon (2021)
- Chen, Shi-Fan; Vlah, Zvonimir; Castorina, Emanuele; White, Martin: Redshift-space distortions in Lagrangian perturbation theory (2021)
- Makiya, Ryu; Kayo, Issha; Komatsu, Eiichiro: Ray-tracing log-normal simulation for weak gravitational lensing: application to the cross-correlation with galaxies (2021)
- Schmittfull, Marcel; Dizgah, Azadeh Moradinezhad: Galaxy skew-spectra in redshift-space (2021)
- Schmittfull, Marcel; Simonović, Marko; Ivanov, Mikhail M.; Philcox, Oliver H. E.; Zaldarriaga, Matias: Modeling galaxies in redshift space at the field level (2021)
- Barrera-Hinojosa, Cristian; Li, Baojiu: GRAMSES: a new route to general relativistic (N)-body simulations in cosmology. II: Initial conditions (2020)
- Sosa Nuñez, Fidel; Niz, Gustavo: On the fast random sampling and other properties of the three point correlation function in galaxy surveys (2020)
- de Mattia, Arnaud; Ruhlmann-Kleider, Vanina: Integral constraints in spectroscopic surveys (2019)
- Ivanov, Mikhail M.; Kaurov, Alexander A.; Sibiryakov, Sergey: Non-perturbative probability distribution function for cosmological counts in cells (2019)