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Are First Passage Time Distributions Necessary for Drift-Diffusion Modeling?
Drift diffusion models are used to model evidence accumulation in two-choice forced-tasks. The traditional approach to fitting Ratcliff’s standard drift diffusion model (where the drift and diffusion are constant) usually involves explicit modeling of the first passage time distributions of the upper and lower boundaries or likelihood approximations. We present the very first technique, to the best of our knowledge, that foregoes use of explicit modeling of the first passage time distributions with a random forest regressor. A random forest regression model that takes the first five moments of the response time distribution, and the upper boundary termination proportion, is used to predict the drift and diffusion parameters from response time data. A training set of response time samples of size 2500 from 121 distinct drift-diffusion pairs is used to train the random forest regressor. On a testing set of 10,000 distinct drift-diffusion combinations with response time sample sizes of 40, we find that our model surpasses techniques that make use of some form of analytical modeling of the first passage time distributions of the boundaries for prediction of the diffusion rate, but not the drift rate. We conclude that the application of machine learning to drift-diffusion modeling of empirical data is a topic worth further investigation
POSYDON: a general-purpose population synthesis code with detailed binary-evolution simulations
Most massive stars are members of a binary or a higher-order stellar systems,
where the presence of a binary companion can decisively alter their evolution
via binary interactions. Interacting binaries are also important astrophysical
laboratories for the study of compact objects. Binary population synthesis
studies have been used extensively over the last two decades to interpret
observations of compact-object binaries and to decipher the physical processes
that lead to their formation. Here, we present POSYDON, a novel, binary
population synthesis code that incorporates full stellar-structure and
binary-evolution modeling, using the MESA code, throughout the whole evolution
of the binaries. The use of POSYDON enables the self-consistent treatment of
physical processes in stellar and binary evolution, including: realistic
mass-transfer calculations and assessment of stability, internal
angular-momentum transport and tides, stellar core sizes, mass-transfer rates
and orbital periods. This paper describes the detailed methodology and
implementation of POSYDON, including the assumed physics of stellar- and
binary-evolution, the extensive grids of detailed single- and binary-star
models, the post-processing, classification and interpolation methods we
developed for use with the grids, and the treatment of evolutionary phases that
are not based on pre-calculated grids. The first version of POSYDON targets
binaries with massive primary stars (potential progenitors of neutron stars or
black holes) at solar metallicity.Comment: 60 pages, 33 figures, 8 tables, referee's comments addressed. The
code and the accompanying documentations and data products are available at
https:\\posydon.or