Universal Low-Frequency Gravitational Wave Background : Nonlinear Memory
ORAL
Abstract
A universal contribution exists in the infrared (low frequency) regime of all gravitational waves, which results from nonlinear memory. Nonlinear memory is sourced by linear order gravitational waves and exists for any gravitational-wave background. We calculate the stochastic nonlinear memory signal of various stochastic backgrounds of cosmological (scalar induced, reheating, phase transition, topological defect, turbulence) and astrophysical (binary mergers of stellar-mass, intermediate mass, supermassive, and primordial black holes) origins. These results allow us to derive the complete frequency spectrum of cosmological and astrophysical Stochastic Gravitational Wave Background. We calculate how to probe the thermal state of the universe, i.e. the equation of the state, via the memory spectrum's slope and also discuss the detection prospects at various frequency bands with future experiments.
*C.U. and D.V. are supported by TUBITAK (The Scientific and Technological Research Council of Turkiye) through the grant number 123C484. C.U. acknowledges support from EU Cost Actions CA21136 (CosmoVerse) and CA21106 (Cosmic Wispers), and the METU DOSAP-C program. D.V. acknowledges support from the European Union’s Horizon Europe Research and Innovation Programme under the Marie Skolodowska-Curie Actions (MSCA) COFUND Programme with the grant number 101081645 and TUBITAK with the grant number 123C213. During the completion of this work, C.U. acknowledges and thanks for the hospitality of Flatiron Institute Center for Computational Astrophysics, Harvard & Smithsonian Center for Astrophysics, Heidelberg University, METU Research and Application Center for Space and Accelerator Technologies (METU IVMER) and New York University; also for the support, hospitality and companionship of Ozlu Aran, Ahmet Bingul, M. Bilge Demirkoz, Sakir Erkoc, Mursel Karadas, Hasan Karpuz, Ertan Kuntman, Seckin Kurkcuoglu, Sarah Libanore, Osman Baris Malcioglu, Anna Maslarova, Federico Oliva, Kaan Sen, Erica Pacchioni and Yiyao Zhang.
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Publication: https://arxiv.org/abs/2511.08514
Presenters
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Caner Unal
- Middle East Technical University