publications

2023

1. 

   Opportunities and Limits of Lunar Gravitational-Wave Detection

   Andrea Cozzumbo , Benedetta Mestichelli , Marco Mirabile , Lavinia Paiella , Jacopo Tissino, and Jan Harms

   Philosophical Transactions A, 2023

   Abs arXiv Bib

   A new era of lunar exploration has begun with participation of all major space agencies. This activity brings opportunities for revolutionary science experiments and observatories on the Moon. The idea of a lunar gravitational-wave detector was already proposed during the Apollo program. The key characteristic of the Moon is that it is seismically extremely quiet. It was also pointed out that the permanently shadowed regions at the lunar poles provide ideal conditions for gravitational-wave detection. In recent years, three different detector concepts were proposed with varying levels of technological complexity and science potential. In this paper, we confront the three concepts in terms of their observational capabilities based on a first more detailed modeling of instrumental noise. We identify important technological challenges and potential show-stoppers.

   @article{cozzumboOpportunitiesLimitsLunar2023,
     title = {Opportunities and Limits of Lunar Gravitational-Wave Detection},
     author = {Cozzumbo, Andrea and Mestichelli, Benedetta and Mirabile, Marco and Paiella, Lavinia and Tissino, Jacopo and Harms, Jan},
     year = {2023},
     eprint = {2309.15160},
     eprinttype = {arxiv},
     journal = {Philosophical Transactions A},
     eprintclass = {astro-ph, physics:gr-qc, physics:physics},
     doi = {10.48550/arXiv.2309.15160},
     url = {http://arxiv.org/abs/2309.15160},
     urldate = {2023-09-28},
     keywords = {Astrophysics - Instrumentation and Methods for Astrophysics,General Relativity and Quantum Cosmology,Physics - Instrumentation and Detectors}
   }

2. 

   Gwfish: A Simulation Software to Evaluate Parameter-Estimation Capabilities of Gravitational-Wave Detector Networks

   U. Dupletsa , J. Harms , B. Banerjee , M. Branchesi , B. Goncharov , A. Maselli , A. C. S. Oliveira , S. Ronchini , and J. Tissino

   Astronomy and Computing, 2023

   Abs arXiv

   An important step in the planning of future gravitational-wave (GW) detectors and of the networks they will form is the estimation of their detection and parameter-estimation capabilities, which is the basis of science-case studies. Several future GW detectors have been proposed or are under development, which might also operate and observe in parallel. These detectors include terrestrial, lunar, and space-borne detectors. In this paper, we present gwfish,11github.com/janosch314/GWFish. a new software to simulate GW detector networks and to calculate measurement uncertainties based on the Fisher-matrix approximation. gwfish models the impact of detector motion on PE and makes it possible to analyze multiband scenarios, i.e., observation of a GW signal by different detectors in different frequency bands. We showcase a few examples for the Einstein Telescope (ET) including the sky-localization of binary neutron stars, and ET’s capability to measure the polarization of GWs.

3. 

   Combining Effective-One-Body Accuracy and Reduced-Order-Quadrature Speed for Binary Neutron Star Merger Parameter Estimation with Machine Learning

   Jacopo Tissino, Gregorio Carullo , Matteo Breschi , Rossella Gamba , Stefano Schmidt , and Sebastiano Bernuzzi

   Physical Review D, 2023

   Abs arXiv

   We present mlgw-bns, a gravitational waveform surrogate that allows for a significant improvement in the generation speed of frequency-domain waveforms for binary neutron star mergers, at a negligible cost in accuracy. This improvement is achieved by training a machine-learning model on a dataset of waveforms generated with an accurate but comparatively costlier approximant: the state-of-the-art effective-one-body model TEOBResumSPA. When coupled to a reduced-order scheme, mlgw-bns can accelerate waveform generation up to a factor of ~35. By analyzing GW170817 in realistic parameter estimation settings with our scheme, we showcase an overall speedup against TEOBResumSPA greater than an order of magnitude. Our methodology will bear its largest impact by allowing routine usage of accurate effective-one-body models with next-generation detectors.