Month: March 2022

Since 2016, when the first gravitational wave detection was announced (signal GW150914, originating from the merger of two black holes with masses of ~29 and ~36 solar masses), astrophysics has opened a completely new window for observing the cosmos. Gravitational waves – predicted over 100 years ago by Einstein as an effect of his general theory of relativity – are subtle disturbances in the very fabric of spacetime, now detectable with a precision of about 1/10,000 the width of a proton by the LIGO and Virgo detectors.

To date, around 90 such signals have been recorded, dominated by merging binary black hole systems. This data provides invaluable information about the evolution of massive stars, the mechanisms behind the formation of black holes and neutron stars, and even the origin of heavy elements such as gold and platinum.

The mechanisms leading to the formation of such compact binary systems are not yet fully understood. One of the leading scenarios involves the isolated evolution of massive binary star systems – precisely the topic investigated by the research group at CAMK PAN led by Prof. Krzysztof Belczynski.

This is only the beginning. Next-generation detectors – the Einstein Telescope and Cosmic Explorer – are expected to capture signals from the early stages of the Universe’s expansion, opening up the prospect of testing theories about its evolution and the history of star formation.

Link to article: https://journals.pan.pl/Content/124728/PDF/66-68_Olejak_pol.pdf

The Universe@Home project is currently running at its highest level of activity to date, with several hundred thousand work units in progress simultaneously and around 300,000 completed per day. Each work unit is a self-contained StarTrack simulation — evolving a large sample of binary star systems through all stages of their lives and returning the final populations of compact objects for analysis. The sheer scale of this throughput is what allows us to map out broad grids of model parameters rather than testing a handful of scenarios: only by exploring many thousands of models can we properly characterise the theoretical uncertainties in binary evolution and make statistically meaningful comparisons with observations.

This kind of computing muscle — donated by tens of thousands of volunteers running BOINC on their home and office machines — is not a convenience but a scientific necessity. The merger rate predictions, spin distributions, and formation efficiency estimates that appear in our papers are only as reliable as the parameter coverage behind them. We are grateful to every volunteer who has kept their machine crunching.

Link to stats: https://universeathome.pl/universe/server_status.php