Tensor-induced non-Gaussianity from primordial gravitational waves generates a unique scale-dependent halo bias correction that can reach order-one amplitude for rare high-redshift halos at z=7.
Improved reconstruction of a stochastic gravitational wave background with LISA
10 Pith papers cite this work. Polarity classification is still indexing.
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abstract
We present a data analysis methodology for a model-independent reconstruction of the spectral shape of a stochastic gravitational wave background with LISA. We improve a previously proposed reconstruction algorithm that relied on a single Time-Delay-Interferometry (TDI) channel by including a complete set of TDI channels. As in the earlier work, we assume an idealized equilateral configuration. We test the improved algorithm with a number of case studies, including reconstruction in the presence of two different astrophysical foreground signals. We find that including additional channels helps in different ways: it reduces the uncertainties on the reconstruction; it makes the global likelihood maximization less prone to falling into local extrema; and it efficiently breaks degeneracies between the signal and the instrumental noise.
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LISA forecasts for quadratically coupled ultralight dark matter show competitive or superior sensitivity to terrestrial and astrophysical probes in selected mass windows, free of screening.
Bayesian multiband analysis shows LISA and Taiji reconstruct PTA-compatible domain wall parameters in the strong-signal regime, with joint PTA priors reducing 10D degeneracies.
An axion-like particle's domain wall or shock wave induces an electroweak phase boundary whose motion creates a local B+L chemical potential that biases active sphalerons to generate net baryon asymmetry.
A neural posterior estimator trained on simulated LISA foreground spectra recovers galactic binary population parameters, including total number, with good accuracy in validation tests.
A trans-dimensional MCMC pipeline recovers parameters of injected SGWB signals in Taiji simulations and reconstructs backgrounds with unknown spectral shapes.
Nested sampling analysis indicates LISA could constrain H1, m, sigma_i and beta in the pre-big-bang model to relative uncertainties of about 18 percent under favorable conditions when including foregrounds.
Hybrid string-bounded domain wall networks from sequential U(1)_F and Z2 symmetry breaking generate a GW spectrum with a unique low-frequency slope that future detectors can observe and an MLP surrogate can characterize for fast SNR inference.
Simulations show TianQin and LISA can reconstruct the dimension-six model parameter Λ to sub-percent statistical precision for strong signals using Fisher, Bayesian sampling, and machine learning on data with noise and foregrounds.
The paper evaluates how triangular versus two-L-shaped geometries, arm lengths, and presence of low-frequency instruments affect the science reach of the Einstein Telescope for compact binaries, multi-messenger events, and stochastic backgrounds.
citing papers explorer
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Tracing Primordial Gravitational Waves via non-Gaussian Signatures of Halo Bias
Tensor-induced non-Gaussianity from primordial gravitational waves generates a unique scale-dependent halo bias correction that can reach order-one amplitude for rare high-redshift halos at z=7.
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Probing Quadratically Coupled Ultralight Dark Matter with the Laser Interferometer Space Antenna
LISA forecasts for quadratically coupled ultralight dark matter show competitive or superior sensitivity to terrestrial and astrophysical probes in selected mass windows, free of screening.
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PTA-Compatible Domain Walls at LISA and Taiji: Bayesian Reconstruction and Multiband Inference
Bayesian multiband analysis shows LISA and Taiji reconstruct PTA-compatible domain wall parameters in the strong-signal regime, with joint PTA priors reducing 10D degeneracies.
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Spontaneous Baryogenesis from Axions on Induced Electroweak Walls
An axion-like particle's domain wall or shock wave induces an electroweak phase boundary whose motion creates a local B+L chemical potential that biases active sphalerons to generate net baryon asymmetry.
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Inferring the population properties of galactic binaries from LISA's stochastic foreground
A neural posterior estimator trained on simulated LISA foreground spectra recovers galactic binary population parameters, including total number, with good accuracy in validation tests.
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Isotropic stochastic gravitational wave background reconstruction for Taiji constellation
A trans-dimensional MCMC pipeline recovers parameters of injected SGWB signals in Taiji simulations and reconstructs backgrounds with unknown spectral shapes.
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LISA as a probe of pre-big-bang physics: a nested sampling analysis
Nested sampling analysis indicates LISA could constrain H1, m, sigma_i and beta in the pre-big-bang model to relative uncertainties of about 18 percent under favorable conditions when including foregrounds.
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Gravitational Waves from hybrid defects as probe of Flavor symmetry breaking: Machine-Learning Approach
Hybrid string-bounded domain wall networks from sequential U(1)_F and Z2 symmetry breaking generate a GW spectrum with a unique low-frequency slope that future detectors can observe and an MLP surrogate can characterize for fast SNR inference.
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Model Parameter Reconstruction of Electroweak Phase Transition with TianQin and LISA: Insights from the Dimension-Six Model
Simulations show TianQin and LISA can reconstruct the dimension-six model parameter Λ to sub-percent statistical precision for strong signals using Fisher, Bayesian sampling, and machine learning on data with noise and foregrounds.
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Science with the Einstein Telescope: a comparison of different designs
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