PIRSA:21060029

Gravitational-wave imprints of non-integrable extreme-mass-ratio inspirals

APA

Destounis, K. (2021). Gravitational-wave imprints of non-integrable extreme-mass-ratio inspirals. Perimeter Institute for Theoretical Physics. https://pirsa.org/21060029

MLA

Destounis, Kyriakos. Gravitational-wave imprints of non-integrable extreme-mass-ratio inspirals. Perimeter Institute for Theoretical Physics, Jun. 08, 2021, https://pirsa.org/21060029

BibTex

          @misc{ scivideos_PIRSA:21060029,
            doi = {10.48660/21060029},
            url = {https://pirsa.org/21060029},
            author = {Destounis, Kyriakos},
            keywords = {Other Physics},
            language = {en},
            title = {Gravitational-wave imprints of non-integrable extreme-mass-ratio inspirals},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2021},
            month = {jun},
            note = {PIRSA:21060029 see, \url{https://scivideos.org/index.php/pirsa/21060029}}
          }
          

Kyriakos Destounis University of Tübingen

Talk numberPIRSA:21060029
Talk Type Conference
Subject

Abstract

The detection of gravitational waves from extreme-mass-ratio inspirals (EMRIs) with upcoming space-borne detectors will allow for unprecedented tests of general relativity in the strong-field regime. Aside from assessing whether black holes are unequivocally described by the Kerr metric, they may place constraints on the degree of spacetime symmetry. Depending on exactly how a hypothetical departure from the Kerr metric manifests, the Carter symmetry, which implies the integrability of the geodesic equations, may be broken. In this talk, I will discuss the impact of non-integrability in EMRIs which involve a supermassive compact object with anomalous multipolar structure. After reviewing the features of chaotic phenomena in EMRIs, I will argue that non-integrability is precisely imprinted in the gravitational waveform. Explicit examples of non-integrable EMRIs will be discussed, as well as their role in LISA data analysis.