arXiv subjects

Jim W. Barrett

Publications and source records attributed to Jim W. Barrett.

9 recordsLinked to original sources

arXiv2026

A Scalable Predictive Modelling Approach to Identifying Duplicate Adverse Event Reports for Drugs and Vaccines

Objectives: To advance state-of-the-art for duplicate detection in large-scale pharmacovigilance databases and achieve more consistent performance across adverse event reports from different countries. Background: Unlinked adverse event reports referring to the same case impede statistical analysis and may mislead clinical assessment. Pharmacovigilance relies on large databases of adverse event reports to discover potential new causal associations, and computational methods are required to identify duplicates at scale. Current state-of-the-art is statistical record linkage which outperforms rule-based approaches. In particular, vigiMatch is in routine use for VigiBase, the WHO global database of adverse event reports, and represents the first statistical duplicate detection approach in pharmacovigilance deployed at scale. Originally developed for both medicines and vaccines, its application to vaccines has been limited due to inconsistent performance across countries. Methods: This paper extends vigiMatch from probabilistic record linkage to predictive modelling, refining features for medicines, vaccines, and adverse events using country-specific reporting rates, extracting dates from free text, and training separate support vector machine classifiers for medicines and vaccines. Recall was evaluated using 5 independent labelled test sets. Precision was assessed by annotating random selections of report pairs classified as duplicates. Results: Precision for the new method was 92% for vaccines and 54% for medicines, compared with 41% for the comparator method. Recall ranged from 80-85% across test sets for vaccines and from 40-86% for medicines, compared with 24-53% for the comparator method. Conclusion: Predictive modeling, use of free text, and country-specific features advance state-of-the-art for duplicate detection in pharmacovigilance.

cs.AI↗

arXiv2021

Rapid stellar and binary population synthesis with COMPAS

Compact Object Mergers: Population Astrophysics and Statistics (COMPAS; https://compas.science) is a public rapid binary population synthesis code. COMPAS generates populations of isolated stellar binaries under a set of parametrized assumptions in order to allow comparisons against observational data sets, such as those coming from gravitational-wave observations of merging compact remnants. It includes a number of tools for population processing in addition to the core binary evolution components. COMPAS is publicly available via the github repository https://github.com/TeamCOMPAS/COMPAS/, and is designed to allow for flexible modifications as evolutionary models improve. This paper describes the methodology and implementation of COMPAS. It is a living document which will be updated as new features are added to COMPAS; the current document describes COMPAS v02.21.00.

astro-ph.IM↗

arXiv2019

STROOPWAFEL: Simulating rare outcomes from astrophysical populations, with application to gravitational-wave sources

Gravitational-wave observations of double compact object (DCO) mergers are providing new insights into the physics of massive stars and the evolution of binary systems. Making the most of expected near-future observations for understanding stellar physics will rely on comparisons with binary population synthesis models. However, the vast majority of simulated binaries never produce DCOs, which makes calculating such populations computationally inefficient. We present an importance sampling algorithm, STROOPWAFEL, that improves the computational efficiency of population studies of rare events, by focusing the simulation around regions of the initial parameter space found to produce outputs of interest. We implement the algorithm in the binary population synthesis code COMPAS, and compare the efficiency of our implementation to the standard method of Monte Carlo sampling from the birth probability distributions. STROOPWAFEL finds $\sim$25-200 times more DCO mergers than the standard sampling method with the same simulation size, and so speeds up simulations by up to two orders of magnitude. Finding more DCO mergers automatically maps the parameter space with far higher resolution than when using the traditional sampling. This increase in efficiency also leads to a decrease of a factor $\sim$3-10 in statistical sampling uncertainty for the predictions from the simulations. This is particularly notable for the distribution functions of observable quantities such as the black hole and neutron star chirp mass distribution, including in the tails of the distribution functions where predictions using standard sampling can be dominated by sampling noise.

astro-ph.HE↗

arXiv2019

The effect of the metallicity-specific star formation history on double compact object mergers

We investigate the impact of uncertainty in the metallicity-specific star formation rate over cosmic time on predictions of the rates and masses of double compact object mergers observable through gravitational waves. We find that this uncertainty can change the predicted detectable merger rate by more than an order of magnitude, comparable to contributions from uncertain physical assumptions regarding binary evolution, such as mass transfer efficiency or supernova kicks. We statistically compare the results produced by the COMPAS population synthesis suite against a catalog of gravitational-wave detections from the first two Advanced LIGO and Virgo observing runs. We find that the rate and chirp mass of observed binary black hole mergers can be well matched under our default evolutionary model with a star formation metallicity spread of $0.39$ dex around a mean metallicity $\left $ that scales with redshift $z$ as $\left =0.035 \times 10^{-0.23 z}$, assuming a star formation rate of $0.01 \times (1+z)^{2.77} / (1+((1+z)/2.9)^{4.7}) \, \rm{M}_\odot$ Mpc$^{-3}$ yr$^{-1}$. Intriguingly, this default model predicts that 80\% of the approximately one binary black hole merger per day that will be detectable at design sensitivity will have formed through isolated binary evolution with only dynamically stable mass transfer, i.e., without experiencing a common-envelope event.

astro-ph.SR↗

arXiv2018

On the formation history of Galactic double neutron stars

Double neutron stars (DNSs) have been observed as Galactic radio pulsars, and the recent discovery of gravitational waves from the DNS merger GW170817 adds to the known DNS population. We perform rapid population synthesis of massive binary stars and discuss model predictions, including formation rates, mass distributions, and delay time distributions. We vary assumptions and parameters of physical processes such as mass transfer stability criteria, supernova kick distributions, remnant mass distributions and common-envelope energetics. We compute the likelihood of observing the orbital period-eccentricity distribution of the Galactic DNS population under each of our population synthesis models, allowing us to quantitatively compare the models. We find that mass transfer from a stripped post-helium-burning secondary (case BB) onto a neutron star is most likely dynamically stable. We also find that a natal kick distribution composed of both low (Maxwellian $σ=30\rm~km~s^{-1}$) and high ($σ=265\rm~km~s^{-1}$) components is preferred over a single high-kick component. We find that the observed DNS mass distribution can place strong constraints on model assumptions.

astro-ph.SR↗

arXiv2018

Accuracy of inference on the physics of binary evolution from gravitational-wave observations

The properties of the population of merging binary black holes encode some of the uncertain physics of the evolution of massive stars in binaries. The binary black hole merger rate and chirp mass distribution are being measured by ground-based gravitational-wave detectors. We consider isolated binary evolution and explore how accurately the physical model can be constrained with such observations by applying the Fisher information matrix to the merging black hole population simulated with the rapid binary population synthesis code COMPAS. We investigate variations in four COMPAS parameters: common envelope efficiency, kick velocity dispersion, and mass loss rates during the luminous blue variable and Wolf--Rayet stellar evolutionary phases. We find that 1000 observations would constrain these model parameters to a fractional accuracy of a few percent. Given the empirically determined binary black hole merger rate, we can expect gravitational-wave observations alone to place strong constraints on the physics of stellar and binary evolution within a few years.

astro-ph.HE↗

arXiv2018

Aldebaran b's temperate past uncovered in planet search data

The nearby red giant Aldebaran is known to host a gas giant planetary companion from decades of ground-based spectroscopic radial velocity measurements. Using Gaussian Process-based Continuous Auto-Regressive Moving Average (CARMA) models, we show that these historic data also contain evidence of acoustic oscillations in the star itself, and verify this result with further dedicated ground-based spectroscopy and space-based photometry with the Kepler Space Telescope. From the frequency of these oscillations we determine the mass of Aldebaran to be $1.16 \pm 0.07 \, M_\odot$, and note that this implies its planet will have been subject to insolation comparable to the Earth for some of the star's main sequence lifetime. Our approach to sparse, irregularly sampled time series astronomical observations has the potential to unlock asteroseismic measurements for thousands of stars in archival data, and push to lower-mass planets around red giant stars.

astro-ph.SR↗

arXiv2017

Exploring the Parameter Space of Compact Binary Population Synthesis

As we enter the era of gravitational wave astronomy, we are beginning to collect observations which will enable us to explore aspects of astrophysics of massive stellar binaries which were previously beyond reach. In this paper we describe COMPAS (Compact Object Mergers: Population Astrophysics and Statistics), a new platform to allow us to deepen our understanding of isolated binary evolution and the formation of gravitational-wave sources. We describe the computational challenges associated with their exploration, and present preliminary results on overcoming them using Gaussian process regression as a simulation emulation technique.

astro-ph.HE↗

arXiv2017

Formation of the first three gravitational-wave observations through isolated binary evolution

During its first 4 months of taking data, Advanced LIGO has detected gravitational waves from two binary black hole mergers, GW150914 and GW151226, along with the statistically less significant binary black hole merger candidate LVT151012. We use our rapid binary population synthesis code COMPAS to show that all three events can be explained by a single evolutionary channel -- classical isolated binary evolution via mass transfer including a common envelope phase. We show all three events could have formed in low-metallicity environments (Z = 0.001) from progenitor binaries with typical total masses $\gtrsim 160 M_\odot$, $\gtrsim 60 M_\odot$ and $\gtrsim 90 M_\odot$, for GW150914, GW151226, and LVT151012, respectively.

astro-ph.HE↗