SearcharxivSearch

arXiv · 2203.06016

Astrophysics with the Laser Interferometer Space Antenna

Pau Amaro Seoane·Jeff Andrews·Manuel Arca Sedda·Abbas Askar·Quentin Baghi·Razvan Balasov·Imre Bartos·Simone S. Bavera·Jillian Bellovary·Christopher P. L. Berry·Emanuele Berti·Stefano Bianchi·Laura Blecha·Stephane Blondin·Tamara Bogdanović·Samuel Boissier·Matteo Bonetti·Silvia Bonoli·Elisa Bortolas·Katelyn Breivik·Pedro R. Capelo·Laurentiu Caramete·Federico Cattorini·Maria Charisi·Sylvain Chaty·Xian Chen·Martyna Chruślińska·Alvin J. K. Chua·Ross Church·Monica Colpi·Daniel D'Orazio·Camilla Danielski·Melvyn B. Davies·Pratika Dayal·Alessandra De Rosa·Andrea Derdzinski·Kyriakos Destounis·Massimo Dotti·Ioana Duţan·Irina Dvorkin·Gaia Fabj·Thierry Foglizzo·Saavik Ford·Jean-Baptiste Fouvry·Alessia Franchini·Tassos Fragos·Chris Fryer·Massimo Gaspari·Davide Gerosa·Luca Graziani·Paul Groot·Melanie Habouzit·Daryl Haggard·Zoltan Haiman·Wen-Biao Han·Alina Istrate·Peter H. Johansson·Fazeel Mahmood Khan·Tomas Kimpson·Kostas Kokkotas·Albert Kong·Valeriya Korol·Kyle Kremer·Thomas Kupfer·Astrid Lamberts·Shane Larson·Mike Lau·Dongliang Liu·Nicole Lloyd-Ronning·Giuseppe Lodato·Alessandro Lupi·Chung-Pei Ma·Tomas Maccarone·Ilya Mandel·Alberto Mangiagli·Michela Mapelli·Steéphane Mathis·Lucio Mayer·Sean McGee·Berry McKernan·M. Coleman Miller·David F. Mota·Matthew Mumpower·Syeda S Nasim·Gijs Nelemans·Scott Noble·Fabio Pacucci·Francesca Panessa·Vasileio Paschalidis·Hugo Pfister·Delphine Porquet·John Quenby·Angelo Ricarte·Friedrich K. Röpke·John Regan·Stephan Rosswog·Ashley Ruiter·Milton Ruiz·Jessie Runnoe·Raffaella Schneider

Abstract

The Laser Interferometer Space Antenna (LISA) will be a transformative experiment for gravitational wave astronomy, and, as such, it will offer unique opportunities to address many key astrophysical questions in a completely novel way. The synergy with ground-based and space-born instruments in the electromagnetic domain, by enabling multi-messenger observations, will add further to the discovery potential of LISA. The next decade is crucial to prepare the astrophysical community for LISA's first observations. This review outlines the extensive landscape of astrophysical theory, numerical simulations, and astronomical observations that are instrumental for modeling and interpreting the upcoming LISA datastream. To this aim, the current knowledge in three main source classes for LISA is reviewed; ultracompact stellar-mass binaries, massive black hole binaries, and extreme or intermediate mass ratio inspirals. The relevant astrophysical processes and the established modeling techniques are summarized. Likewise, open issues and gaps in our understanding of these sources are highlighted, along with an indication of how LISA could help making progress in the different areas. New research avenues that LISA itself, or its joint exploitation with upcoming studies in the electromagnetic domain, will enable, are also illustrated. Improvements in modeling and analysis approaches, such as the combination of numerical simulations and modern data science techniques, are discussed. This review is intended to be a starting point for using LISA as a new discovery tool for understanding our Universe.

Explore related subjects

Keep this discovery

BibTeXRIS

Pau Amaro Seoane, Jeff Andrews, Manuel Arca Sedda, Abbas Askar, Quentin Baghi, Razvan Balasov, Imre Bartos, Simone S. Bavera, Jillian Bellovary, Christopher P. L. Berry, Emanuele Berti, Stefano Bianchi, Laura Blecha, Stephane Blondin, Tamara Bogdanović, Samuel Boissier, Matteo Bonetti, Silvia Bonoli, Elisa Bortolas, Katelyn Breivik, Pedro R. Capelo, Laurentiu Caramete, Federico Cattorini, Maria Charisi, Sylvain Chaty, Xian Chen, Martyna Chruślińska, Alvin J. K. Chua, Ross Church, Monica Colpi, Daniel D'Orazio, Camilla Danielski, Melvyn B. Davies, Pratika Dayal, Alessandra De Rosa, Andrea Derdzinski, Kyriakos Destounis, Massimo Dotti, Ioana Duţan, Irina Dvorkin, Gaia Fabj, Thierry Foglizzo, Saavik Ford, Jean-Baptiste Fouvry, Alessia Franchini, Tassos Fragos, Chris Fryer, Massimo Gaspari, Davide Gerosa, Luca Graziani, Paul Groot, Melanie Habouzit, Daryl Haggard, Zoltan Haiman, Wen-Biao Han, Alina Istrate, Peter H. Johansson, Fazeel Mahmood Khan, Tomas Kimpson, Kostas Kokkotas, Albert Kong, Valeriya Korol, Kyle Kremer, Thomas Kupfer, Astrid Lamberts, Shane Larson, Mike Lau, Dongliang Liu, Nicole Lloyd-Ronning, Giuseppe Lodato, Alessandro Lupi, Chung-Pei Ma, Tomas Maccarone, Ilya Mandel, Alberto Mangiagli, Michela Mapelli, Steéphane Mathis, Lucio Mayer, Sean McGee, Berry McKernan, M. Coleman Miller, David F. Mota, Matthew Mumpower, Syeda S Nasim, Gijs Nelemans, Scott Noble, Fabio Pacucci, Francesca Panessa, Vasileio Paschalidis, Hugo Pfister, Delphine Porquet, John Quenby, Angelo Ricarte, Friedrich K. Röpke, John Regan, Stephan Rosswog, Ashley Ruiter, Milton Ruiz, Jessie Runnoe, Raffaella Schneider. 2022-03-11. Astrophysics with the Laser Interferometer Space Antenna. https://doi.org/10.1007/s41114-022-00041-y

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Electrovacuum Black Hole Uniqueness

We prove the black hole uniqueness conjecture in the axially symmetric, stationary, electrovacuum setting, subject to the refined asymptotic analysis of the associated singular harmonic maps, which includes an analyticity hypothesis at the axes. More precisely, it is shown that any asymptotically flat solution of the Einstein--Maxwell equations in this class, with more than one black hole horizon component is either: Majumdar--Papapetrou, up to a duality rotation, in which case all logarithmic angle defects vanish, or every finite axis rod logarithmic angle defect is strictly negative and hence every interaction force is strictly attractive. The proof extends the singular harmonic map method used for vacuum Kerr uniqueness in [18].

gr-qc

Constraining Modified Mass-to-Horizon Cosmology Through Primordial Inflationary Observables

We investigate slow-roll inflation in a modified cosmological framework inspired by a generalized mass-to-horizon relation (MHR), $M=\gamma {c^2 L^n}/{G}$, where $n$ is a real parameter and $\gamma$ a dimensional constant. Using Padmanabhan's emergence paradigm, we derive the modified Friedmann equations for a flat FRW universe and analyze the dynamics of a canonical scalar field (inflaton) under the slow-roll approximation. We study the resulting inflationary phenomenology for power-law and Starobinsky potentials. For power-law potentials, the MHR modification fails to reconcile these models with current CMB constraints on $r$ and $n_s$. In contrast, Starobinsky inflation exhibits significant sensitivity to deviations from $n=1$. A perturbative analysis ($n=1+\Delta$) yields corrections to inflationary observables. We observe that the scalar power-spectrum normalization, under a fixed-Starobinsky prescription, imposes the stringent constraint $0.960 \lesssim n \lesssim 1.040$ for $N=60$ efolds. This is considerably tighter than spectral-index bounds. Our results establish inflation, particularly Starobinsky-like models, as a sensitive probe of generalized horizon thermodynamics and departures from standard MHR scaling.

gr-qc

Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction

In the last decade, kilometre-scale interferometric gravitational-wave detectors have observed hundreds of compact binary mergers, the majority of which are binary black holes. However, the data are noise-dominated, and multiple independent search algorithms (pipelines) are used to enhance sensitivity and improve robustness. Rather than the standard approach of selecting the most significant pipeline output, we combine the outputs from all pipelines using a conformal prediction-based framework to provide statistically rigorous confidence estimates for candidate events. While combining pipelines improves sensitivity and ranking robustness, it requires a principled statistical framework that remains valid as data properties evolve across observing runs. A key challenge is distribution shifts between simulated datasets used for training and calibration and the real, unlabelled, observations used for testing, which can invalidate coverage guarantees and bias confidence estimates. In this work, we address this challenge by incorporating likelihood-ratio reweighting into our conformal prediction framework to account for covariate shift. Using mock datasets containing simulated signals, we demonstrate that weighted conformal prediction restores well-calibrated coverage under covariate shift and increases the confidence of events near the detection threshold, recovering true signals that would otherwise be missed.

gr-qc