Tootfinder

Constant Modulus Waveforms for IoT-Centric Integrated Sensing and Communications
Tian Han, Shalanika Dayarathna, Rajitha Senanayake, Peter Smith, Aryan Kaushik, Alain Mourad, Richard A. Stirling-Gallacher, Jamie Evans
https://arxiv.org/abs/2506.21078

Constant Modulus Waveforms for IoT-Centric Integrated Sensing and Communications
Integrated sensing and communications (ISAC) is considered a key enabler to support application scenarios such as the Internet-of-Things (IoT) in which both communications and sensing play significant roles. Multi-carrier waveforms, such as orthogonal frequency division multiplexing (OFDM), have been considered as good candidates for ISAC due to their high communications data rate and good time bandwidth property for sensing. Nevertheless, their high peak-to-average-power-ratio (PAPR) values le…

Nonlinear Gravitational Memory in the Post-Minkowskian Expansion
Alessandro Georgoudis, Vasco Goncalves, Carlo Heissenberg, Julio Parra-Martinez
https://arxiv.org/abs/2506.20733

Nonlinear Gravitational Memory in the Post-Minkowskian Expansion
We present the first computation of the nonlinear gravitational memory waveform for the scattering of two compact objects in General Relativity at leading order in the post-Minkowskian expansion. We use the scattering-amplitudes-based representation of the gravitational waveform, which naturally expresses the nonlinear memory as the contribution of soft gravitons emitted by the gravitational waves themselves. We perform the calculation by applying a multipolar decomposition to the waveform and …

Systematic bias in LISA ringdown analysis due to waveform inaccuracy
Lodovico Capuano, Massimo Vaglio, Rohit S. Chandramouli, Chantal L Pitte, Adrien Kuntz, Enrico Barausse
https://arxiv.org/abs/2506.21181

Systematic bias in LISA ringdown analysis due to waveform inaccuracy
Inaccurate modeling of gravitational-wave signals can introduce systematic biases in the inferred source parameters. As detector sensitivities improve and signals become louder, mitigating such waveform-induced systematics becomes increasingly important. In this work, we assess the systematic biases introduced by an incomplete description of the ringdown signal from massive black hole binaries in the LISA band. Specifically, we investigate the impact of mode truncation in the ringdown template.…

Sensing-Aware Transmit Waveform/Receive Filter Design for OFDM-MBS Systems
Xinghe Li, Kainan Cheng, Huiyong Li, Huiyong Li, Ziyang Cheng
https://arxiv.org/abs/2506.20231

Sensing-Aware Transmit Waveform/Receive Filter Design for OFDM-MBS Systems
In this letter, we study the problem of cooperative sensing design for an orthogonal frequency division multiplexing (OFDM) multiple base stations (MBS) system. We consider a practical scenario where the base stations (BSs) exploit certain subcarriers to realize a sensing function. Since the high sidelobe level (SLL) of OFDM waveforms degrades radar detection for weak targets, and the cross-correlation generated by other BSs further exacerbates detection performance, we devise a joint design sc…

Adding equatorial-asymmetric effects for spin-precessing binaries into the SEOBNRv5PHM waveform model
H\'ector Estell\'es, Alessandra Buonanno, Raffi Enficiaud, Cheng Foo, Lorenzo Pompili
https://arxiv.org/abs/2506.19911

Adding equatorial-asymmetric effects for spin-precessing binaries into the SEOBNRv5PHM waveform model
Gravitational waves from spin-precessing binaries exhibit equatorial asymmetries absent in non-precessing systems, leading to net linear momentum emission and contributing to the remnant's recoil. This effect, recently incorporated into only a few waveform models, is crucial for accurate recoil predictions and improved parameter estimation. We present an upgrade to the SEOBNRv5PHM model -- SEOBNRv5PHM_w/asym -- which includes equatorial asymmetric contributions to the l=m<=4 waveform modes in t…

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch
Lei Liu, Chao Song, Liangsheng He, Silin Wang, Xuan Feng, Cai Liu
https://arxiv.org/abs/2506.20513

Fast ground penetrating radar dual-parameter full waveform inversion method accelerated by hybrid compilation of CUDA kernel function and PyTorch
This study proposes a high-performance dual-parameter full waveform inversion framework (FWI) for ground-penetrating radar (GPR), accelerated through the hybrid compilation of CUDA kernel functions and PyTorch. The method leverages the computational efficiency of GPU programming while preserving the flexibility and usability of Python-based deep learning frameworks. By integrating customized CUDA kernels into PyTorch's automatic differentiation mechanism, the framework enables accurate and effi…

A Hybrid Zernike-Lyapunov Framework for Aberration-Based Statistical Wavefront Reconstruction of Chaotic Optical Surfaces
Netzer Moriya
https://arxiv.org/abs/2506.16847

A Hybrid Zernike-Lyapunov Framework for Aberration-Based Statistical Wavefront Reconstruction of Chaotic Optical Surfaces
We present a comprehensive theoretical framework that unifies chaotic wavefront dynamics with classical aberration theory through a Statistical Wavefront Reconstruction Framework (SWRF) formalism. By establishing rigorous connections between ray trajectory deflections and wave-optical phase perturbations through the eikonal equation, we decompose chaotic wavefront perturbations into modified Zernike-Lyapunov hybrid expansions, establishing mathematical equivalences between Lyapunov exponents, f…

Waging a Campaign: Results from an Injection-Recovery Study involving 35 numerical Relativity Simulations and three Waveform Models
Sarp Ak\c{c}ay, Charlie Hoy, Jake Mac Uilliam
https://arxiv.org/abs/2506.19990

Waging a Campaign: Results from an Injection-Recovery Study involving 35 numerical Relativity Simulations and three Waveform Models
We present Bayesian inference results from an extensive injection-recovery campaign to test the validity of three state of the art quasicircular gravitational waveform models: \textsc{SEOBNRv5PHM}, \textsc{IMRPhenomTPHM}, \textsc{IMRPhenomXPHM}, the latter with the \textsc{SpinTaylorT4} implementation for its precession dynamics. We analyze 35 strongly precessing binary black hole numerical relativity simulations with all available harmonic content. Ten simulations have a mass ratio of $4:1$ an…

Laboratory Frame Representation for General High-Frequency Gravitational Waveforms
Lars Fischer, Tom Krokotsch, Gudrid Moortgat-Pick
https://arxiv.org/abs/2506.20198

Laboratory Frame Representation for General High-Frequency Gravitational Waveforms
Next-generation gravitational wave (GW) experiments will explore higher frequency ranges, where GW wavelengths approach the size of the detector itself. In this regime, GWs may be detected not just through the well-known mechanical deformation by tidal forces but also via induced effective currents in electromagnetic background fields. However, the calculation of this signal requires the GW metric in laboratory coordinates of the detector, and an accurate transformation to all orders into this …

Spherical inspirals of spinning bodies into Kerr black holes
Viktor Skoup\'y, Gabriel Andres Piovano, Vojt\v{e}ch Witzany
https://arxiv.org/abs/2506.20726

Spherical inspirals of spinning bodies into Kerr black holes
Extreme mass-ratio inspirals (EMRIs), consisting of a stellar-mass compact object spiraling into a massive black hole, are key sources for future space-based gravitational wave observatories such as LISA. Accurate modeling of these systems requires incorporating the spin effects of both the primary and secondary bodies, particularly for waveforms at the precision required for LISA detection and astrophysical parameter extraction. In this work, we develop a framework for modeling flux-driven sph…