Black hole spin evolution across cosmic time from the NewHorizon simulation

(2024)

Authors:

Ricarda S Beckmann, Yohan Dubois, Marta Volonteri, Chi An Dong-Paez, Sebastien Periani, Joanna M Piotrowska, Garreth Martin, Katharina Kraljic, Julien Devriendt, Christophe Peirani, Sukyoung K Yi

Self-interacting scalar dark matter around binary black holes

(2024)

Authors:

Josu C Aurrekoetxea, James Marsden, Katy Clough, Pedro G Ferreira

Self-interacting scalar dark matter around binary black holes

Physical Review D (particles, fields, gravitation, and cosmology) American Physical Society 110:8 (2024) 83011

Authors:

Josu C Aurrekoetxea, James Marsden, Katy Clough, Pedro G Ferreira

Abstract:

Gravitational waves can provide crucial insights about the environments in which black holes live. In this work, we use numerical relativity simulations to study the behavior of self-interacting scalar (wavelike) dark matter clouds accreting onto isolated and binary black holes. We find that repulsive self-interactions smoothen the "spike"of an isolated black hole and saturate the density. Attractive self-interactions enhance the growth and result in more cuspy profiles, but can become unstable and undergo explosions akin to the superradiant bosenova that reduce the local cloud density. We quantify the impact of self-interactions on an equal-mass black hole merger by computing the dephasing of the gravitational-wave signal for a range of couplings. We find that repulsive self-interactions saturate the density of the cloud, thereby reducing the dephasing. For attractive self-interactions, the dephasing may be larger, but if these interactions dominate prior to the merger, the dark matter can undergo bosenova during the inspiral phase, disrupting the cloud and subsequently reducing the dephasing.

Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam

ArXiv 2410.00401 (2024)

Authors:

Joaquin Armijo, Gabriela A Marques, Camila P Novaes, Leander Thiele, Jessica A Cowell, Daniela Grandón, Masato Shirasaki, Jia Liu

Finding radio transients with anomaly detection and active learning based on volunteer classifications

(2024)

Authors:

Alex Andersson, Chris Lintott, Rob Fender, Michelle Lochner, Patrick Woudt, Jakob van den Eijnden, Alexander van der Horst, Assaf Horesh, Payaswini Saikia, Gregory R Sivakoff, Lilia Tremou, Mattia Vaccari