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Следующее заседание планируется в понедельник, 8 декабря, в 17-30 в аудитории 4-46

Доклад Марии Рах (Национальная астрономическая обсерватория, Китай; Бюраканская астрофизическая обсерватория, Армения)

Тема доклада: A Modular Computational Pipeline for Neutron Star Evolution with Reduced Computational Cost

This proposal introduces a modular computational framework designed to model the evolution of neutron stars while maintaining wide accessibility across diverse computational environments. The project aims to integrate parametric physics models that reproduce the central evolutionary processes of neutron stars; structural evolution, thermal history, magnetic field development, magnetospheric behavior, spin dynamics, environmental interaction, binary orbital evolution, and observable signatures; within a unified and flexible pipeline.

Each module is planned to undergo independent benchmarking against established astrophysical tools such as NSCool, Viganò et al., and COSMIC to ensure consistency with widely used approaches in the field. The modular architecture supports future upgrades and the incorporation of new physics as theoretical and computational advances emerge.

Based on current projections, the completed framework is expected to perform evolutionary simulations with substantially reduced runtime while delivering results comparable in accuracy to detailed GPU-based methods. This capability is anticipated to enable extensive exploration of formation and evolutionary scenarios, including millisecond-pulsar pathways, magnetar population development, neutron stars in diverse galactic environments, and gravitational-wave progenitors.

The proposed system is envisioned as a complementary tool within the broader astrophysics ecosystem, positioned to bridge high-detail numerical methods and population-level synthesis approaches. Once accomplished, it may enhance neutron-star evolution research by providing a platform that supports both physical fidelity and efficient parameter-space exploration across a wide range of computational resources.

доклад планируется в гибридном режиме