Hoki: Making BPASS accessible through Python

Abstract

We now know that a large number of stars are born in multiple systems. Additionally, more than 70% of massive stars are found in close binary systems, meaning that they will interact over the course of their lifetime (Sana et al., 2012). This has strong implications for their evolution as well as the transients (e.g supernovae) and the potential gravitational wave progenitors they produce. Therefore, in order to understand and correctly interpret astronomical observations of stellar populations, we must use theoretical models able to account for the effects of binary stars. This is the case of the Binary Population and Spectral Synthesis code (BPASS) (Eldridge et al., 2017;Stanway & Eldridge, 2018), which has been a staple of the field for over 10 years (Eldridge, Izzard, & Tout, 2008;Eldridge & Stanway, 2009). As is the case for most other theoretical models, the data products of BPASS are large, varied and complex. As a result, their use requires a level of expertise that is not immediately accessible to a wider community that may hold key observational data. The goal of hoki is to bridge the gap between observation and theory, by providing a set of tools to make BPASS data easily accessible and facilitate analysis. The use of Python is deliberate as it is a ubiquitous language within Astronomy. This allows BPASS results to be used naturally within the pre-existing workflow of most astronomers.

The R136 star cluster dissected with Hubble Space Telescope/STIS – II. Physical properties of the most massive stars in R136

“…14) within 150 pc (10 arcmin) from R136a1 (Walborn 1991) to the population synthesis prediction from BPASS (v.2.2.1, Stanway & Eldridge 2018). We downloaded the commonly used and publicly available BPASS output 3 and visualised it with the python package Hoki which has been designed to interface with the BPASS models and their outputs (Stevance et al 2020). The publicly available BPASS models for binary population synthesis used the binary, period and mass distribution according to Sana et al (2012); Moe & Di Stefano (2017).…”

“…Black solid lines are bonn evolutionary tracks and ZAMS(Brott et al 2011;Köhler et al 2015). The grey shaded contours visualise the predicted binary stellar population from BPASS(Eldridge et al 2017;Stevance et al 2020) for the observed age range. Each contour represents an order of magnitude difference in stellar number density.…”

Binary evolution pathways of blue large-amplitude pulsators

“…Analysis of these models made use of the pandas data frames of the BPASS models (Stevance 2020), which were constructed by the Python package(Stevance et al 2020a) …”

Riroriro: Simulating gravitational waves and evaluating their detectability in Python

“…Riroriro has been used for research in conjunction with BPASS, a suite of computer programs that simulates the evolution of a population of binary and single-star systems from a wide range of initial conditions and predicts their electromagnetic spectral emission (Eldridge et al, 2017;Stanway & Eldridge, 2018). There is also a Python interface for BPASS called Hoki (Stevance et al, 2020). This research took rates of formation of merging systems from BPASS and then evaluated the detectability of the gravitational wave signals from those systems using Riroriro.…”