Applies high-T dimensional reduction for the first time to a classically scale-invariant model, computes NLO nucleation rate via determinants, and predicts LISA-detectable GW from supercooled PT in SU(2)cSM.
Gravitational waves from first-order phase transitions in LISA: reconstruction pipeline and physics interpretation,
7 Pith papers cite this work. Polarity classification is still indexing.
citation-role summary
citation-polarity summary
fields
hep-ph 7roles
background 1polarities
background 1representative citing papers
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.
Computes dimension-six operators in finite-temperature massive scalar QED via heat kernel methods and evaluates their combined effect with the Polyakov loop on first-order phase transition thermodynamics.
A realistic Taiji-like analysis recovers an injected complex-singlet phase-transition gravitational-wave signal at relative SNR ≈ 53 with ln BF ≈ 11.6, and maps the spectrum posterior onto the Higgs cubic self-coupling deviation δκ3.
Using simulated Taiji data, the authors show that a stochastic gravitational-wave signal from an electroweak phase transition in the singlet-extended Standard Model can constrain the Higgs cubic and quartic self-couplings.
Radiative electroweak symmetry breaking with a logarithmic potential yields analytical vacuum solutions, four thermal history patterns, and supercooled FOPT gravitational waves whose signals combined with collider data can probe conformal scales to 10^5-10^8 GeV.
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.
citing papers explorer
-
Theoretical consistency and phenomenology of supercooled cosmological phase transitions
Applies high-T dimensional reduction for the first time to a classically scale-invariant model, computes NLO nucleation rate via determinants, and predicts LISA-detectable GW from supercooled PT in SU(2)cSM.
-
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.
-
Higher-dimensional operators and Polyakov loop in hot Scalar QED from the heat kernel
Computes dimension-six operators in finite-temperature massive scalar QED via heat kernel methods and evaluates their combined effect with the Polyakov loop on first-order phase transition thermodynamics.
-
Bayesian analysis of the complex singlet model with phase transition gravitational waves
A realistic Taiji-like analysis recovers an injected complex-singlet phase-transition gravitational-wave signal at relative SNR ≈ 53 with ln BF ≈ 11.6, and maps the spectrum posterior onto the Higgs cubic self-coupling deviation δκ3.
-
Measuring gravitational wave spectrum from electroweak phase transition and Higgs self-couplings
Using simulated Taiji data, the authors show that a stochastic gravitational-wave signal from an electroweak phase transition in the singlet-extended Standard Model can constrain the Higgs cubic and quartic self-couplings.
-
Probing radiative electroweak symmetry breaking with colliders and gravitational waves
Radiative electroweak symmetry breaking with a logarithmic potential yields analytical vacuum solutions, four thermal history patterns, and supercooled FOPT gravitational waves whose signals combined with collider data can probe conformal scales to 10^5-10^8 GeV.
-
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.