paper.md

title	tags	authors	affiliations	date	bibliography	aas-doi	aas-journal
COMPAS: A rapid binary population synthesis suite	Python C++ astronomy gravitational waves binary evolution	name affiliation Team COMPAS 1 name affiliation Jeff Riley 2,3 name affiliation Poojan Agrawal 4,3 name affiliation Jim W. Barrett 5 name affiliation Kristian N. K. Boyett 6 name affiliation Floor S. Broekgaarden 7 name affiliation Debatri Chattopadhyay 8,4,3 name affiliation Sebastian M. Gaebel 9 name affiliation Fabian Gittins 10 name affiliation Ryosuke Hirai 2,3 name affiliation George Howitt 11 name affiliation Stephen Justham 12,13,14 name affiliation Lokesh Khandelwal 12 name affiliation Floris Kummer 12 name affiliation Mike Y. M. Lau 2,3 name affiliation Ilya Mandel 2,3,5 name affiliation Selma E. de Mink 14,12,7 name affiliation Coenraad Neijssel 5,3 name affiliation Tim Riley 2,3 name affiliation Lieke van Son 7,12,14 name affiliation Simon Stevenson 4,3 name affiliation Alejandro Vigna-Gómez 15,16 name affiliation Serena Vinciguerra 12 name affiliation Tom Wagg 7,14 name affiliation Reinhold Willcox 2,3	name index The public COMPAS code is a product of work by the entire COMPAS collaboration over many years; we therefore kindly request that, in recognition of this team effort, the paper is cited as Team COMPAS - J. Riley et al. 1 name index School of Physics and Astronomy, Monash University, Clayton, Victoria 3800, Australia 2 name index OzGrav, Australian Research Council Centre of Excellence for Gravitational Wave Discovery, Australia 3 name index Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, VIC 3122, Australia 4 name index Institute of Gravitational Wave Astronomy and School of Physics and Astronomy, University of Birmingham, Birmingham, B15 2TT 5 name index Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, UK 6 name index Center for Astrophysics |Harvard & Smithsonian, 60 Garden St., Cambridge, MA 02138, USA 7 name index School of Physics and Astronomy, Cardiff University, Cardiff, CF24 3AA, United Kingdom 8 name index Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Callinstrasse 38, D-30167 Hannover, Germany 9 name index Mathematical Sciences and STAG Research Centre, University of Southampton, Southampton SO17 1BJ, UK 10 name index School of Physics, University of Melbourne, Parkville, Victoria, 3010, Australia 11 name index Anton Pannekoek Institute of Astronomy and GRAPPA, Science Park 904, University of Amsterdam, 1098XH Amsterdam, The Netherlands 12 name index School of Astronomy & Space Science, University of the Chinese Academy of Sciences, Beijing 100012, China 13 name index Max Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, 85748 Garching, Germany 14 name index DARK, Niels Bohr Institute, University of Copenhagen, Jagtvej 128, 2200, Copenhagen, Denmark 15 name index Niels Bohr International Academy, The Niels Bohr Institute, Blegdamsvej 17, 2100 Copenhagen, Denmark 16	xx Month 2021	paper.bib	10.3847/1538-4365/ac416c	Astrophysical Journal Supplements

Summary

Most massive stars---those with initial masses greater than 8 $M_\odot$---are born with another massive star as a companion [@Sana:2012Sci;@Moe:2017ApJS]. Massive binary stars are responsible for producing many exotic astrophysical phenomena, such as the observed diversity of supernovae, binary pulsars, X-ray binaries and merging compact objects. The latter are now regularly observed by the ground-based gravitational wave observatories Advanced LIGO and Virgo [@abbott2016observation;@GWTC3]. Population models of massive binary evolution make it possible to interpret existing observations and to make predictions for future observing campaigns.

Statement of need

Binary population synthesis generates population models of isolated stellar binaries under a set of parametrized assumptions. These models permit comparisons against observational data sets, such as X-ray binaries of gravitational-wave mergers.

In particular, rapid binary population synthesis is needed in order to efficiently explore a broad parameter space of uncertain assumptions about the physics of stellar and binary evolution, including supernova remnant masses and natal kicks, mass transfer efficiency and stability, and the outcome of common-envelope events.

A range of binary population synthesis codes have been developed over the last three decades. These include the Scenario Machine [@Scenario], IBiS [@IBiS], SeBa [@SeBa], BSE [@Hurley:2002rf], StarTrack [@Belczynski:2008], binary$_$c [@BinaryC], MOBSE [@2018MNRAS.474.2959G] and COSMIC [@2019arXiv191100903B]. These codes range from private to semi-public to fully public, and differ in the range of available tools, computational complexity, and speed of execution.

COMPAS is a rapid binary population synthesis suite. It parametrizes complex astrophysical processes with prescriptions calibrated to detailed models. COMPAS is designed to allow for flexible modifications as evolutionary models improve. All code is fully public and, including pre-processing and post-processing tools. COMPAS is computationally efficient, with a focus on the statistical analysis of large populations, particularly but not exclusively in the context of gravitational-wave astronomy.

Details

The core engine of COMPAS---responsible for calculating the evolution of single [@Hurley:2000pk] and binary [@Hurley:2002rf] stars---is written in object oriented C++ for speed and flexibility. COMPAS is able to simulate the evolution of a typical binary over 10 Gyr in approximately 10 milliseconds.

A detailed description of the implementation of the COMPAS suite can be found in @COMPAS:2021methodsPaper.

In addition to the core stellar and binary evolution engine, we provide Python scripts for both pre- and post-processing COMPAS outputs. Post-processing can account for integrating populations formed throughout cosmic history [@2019MNRAS.490.3740N] and methods to account for gravitational-wave selection effects [@Barrett:2017fcw]. A set of examples is also provided.

COMPAS is embarrassingly parallel and can be trivially run on high performance computers and distributed on cloud computing.

COMPAS was initially designed to focus on studies of merging binaries containing neutron stars and black holes that are being observed through gravitational waves [@Stevenson2017FormationEvolution;@2018MNRAS.481.4009V]. In recent years, the scope of systems investigated with COMPAS has expanded to incorporate, e.g., Be X-ray binaries [@Vinciguerra:2020] and luminous red novae [@Howitt:2020] (see @COMPAS:2021methodsPaper or the COMPAS collaboration website for a summary of COMPAS publications to date.)

COMPAS development happens on Github. We maintain a Zenodo community where data from many publications using COMPAS is publicly available.

Acknowledgements

Multiple authors are supported by the Australian Research Council Centre of Excellence for Gravitational Wave Discovery (OzGrav), through project number CE170100004. Multiple authors were funded in part by the National Science Foundation under Grant No. (NSF grant number 2009131), the Netherlands Organization for Scientific Research (NWO) as part of the Vidi research program BinWaves with project number 639.042.728 and by the European Union’s Horizon 2020 research and innovation program from the European Research Council (ERC, Grant agreement No. 715063). FSB is supported in part by the Prins Bernard Cultuurfonds studiebeurs. IM is a recipient of an Australian Research Council Future Fellowship (FT190100574). AVG acknowledges funding support by the Danish National Research Foundation (DNRF132)

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