2–4 Mar 2026
Harokopio University
Europe/Athens timezone

Synchrotron Self-Compton code for mutlimessenger study of Black Hole-Neutron coalescence events

3 Mar 2026, 11:50
25m
Harokopio University

Harokopio University

Thiseos 70, Kallithea 176 76

Speaker

Tobia Matcovich (INFN- Perugia)

Description

Looking to the future of multi-messenger astrophysics, it is still unclear what we can expect, but phenomena that are difficult to observe now will likely become
relevant and significant. These certainly include the coalescence of compact objects such as neutron star binaries and black hole-neutron star pairs.
Although the gravitational waves produced by these events have only been detected in a few cases (for example, GW170817, GW200105, and GW200115), and there has only been one actual
multimessenger event, it remains important to study these phenomena in view of the many detections that will be possible with the next generation of interferometers (Einstein Telescope and Cosmic Explorer).

The study of BNS and NSBH coalescences, alongside neutron star binary (BNS) mergers, is pivotal due to their status as prime multimessenger candidates capable of producing
a wide range of electromagnetic counterparts, including Gamma-ray Bursts (GRBs) and Kilonovae. By conducting joint analyses of both the gravitational and electromagnetic signals,
it becomes feasible to derive more precise insights into the properties of the involved celestial objects and the myriad processes occurring during and after the merge.

In our work, we are developing a numerical code to evaluate the Synchrotron Self-Compton (SSC) spectrum that characterizes the afterglow of emitted GRBs. Our approach is able to consider structured type GRBs, and so it allows us to assess the expected emission as a function of viewing angle and time. The goal is to use the predicted SSC signal to estimate the number of multi-messenger events that instruments such as CTAO will detect, and to investigate how the multi-messenger approach—especially at high energies—can improve parameter estimation for the objects involved in the merger.

Primary author

Tobia Matcovich (INFN- Perugia)

Co-authors

Dr Paolo Cristarella Orestano (INFN- Perugia) Prof. Sara Cutini (INFN- Perugia) Prof. Stefano Germani (INFN- Perugia)

Presentation materials

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