[ascl:2511.030]
CompactObject: Bayesian EOS inference for neutron stars
Huang, Chun;
Malik, Tuhin;
Cartaxo, João;
Sourav, Shashwat;
Yuan, Wenli;
Zhou, Tianzhe;
Liu, Xuezhi;
Groger, John;
Dong, Xieyuan;
Osborn, Nicole;
Whitsett, Nathan;
Wang, Zhiheng;
Providência, Constança;
Oertel, Micaela;
Chen, Alexander Y.;
Tolos, Laura;
Watts, Anna
CompactObject constrains the equation of state (EOS) of neutron stars using Bayesian inference. It includes modules for EOS generation (relativistic mean field, polytrope, quark or strange-star, speed-of-sound, or custom models), solving the Tolman–Oppenheimer–Volkoff equations to compute mass, radius, and tidal deformability, and performing Bayesian inference that incorporates astrophysical observations and theoretical constraints. Users can generate EOS samples, compute neutron star properties, and derive posterior distributions on EOS parameters. The CompactObject package also provides documentation and example workflows.
[ascl:2511.021]
Aperture: High-performance particle-in-cell framework for plasma simulations
Aperture provides a flexible, high-performance Particle-in-Cell (PIC) simulation framework for plasma physics with support for both CPU and GPU execution. It uses MPI for distributed-memory parallelism, OpenMP for shared-memory threading, and optional CUDA or HIP acceleration to run efficiently on diverse computing architectures. Aperture's modular design lets users incorporate new physics modules, numerical schemes, and diagnostics without modifying the core infrastructure.