A contrastive self-supervised convolutional autoencoder detects core-collapse supernova gravitational waves with performance comparable to supervised CNNs, better generalization to unseen waveforms, and ~120 kpc sensitive distance under Einstein Telescope noise.
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HIcosmo is a new JAX-based differentiable framework for background cosmology inference that matches Cobaya results while delivering 8.7x CPU and up to 20x GPU speedups.
Combining GWTC-4 standard sirens with TDCOSMO2025 lensing data under the distance sum rule yields H0 = 83.78 +12.53/-10.23 km/s/Mpc (13.6% precision) in one configuration, consistent with both Planck and SH0ES.
Forecasts that cross-correlating 3G GW dark sirens with CSST photometric galaxies yields 1.04% precision on H0 and 2.04% on Omega_m while also constraining GW clustering bias.
Axion EDE model fitted to Planck/ACT/SPT CMB, DESI BAO, and JWST UV luminosity function data yields H0 = 71.58 ± 1.05 km s^{-1} Mpc^{-1}, reduces H0 tension to 1.0 sigma, and improves Δχ^{2}_tot = -18.26 over Λ CDM.
Cross-correlating CSST galaxies with mock GW catalogs from ET2CE and BDET2CE networks can detect PBH merger fractions above ~40% and ~20% respectively via clustering bias differences.
Simulations indicate joint Taiji+LISA analysis of five SLGW events yields H0 95% credible interval uncertainties of 0.11 (source redshift unknown) or 0.042 (source redshift known).
citing papers explorer
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Contrastive self-supervised convolutional autoencoder for core-collapse supernova gravitational-wave detection
A contrastive self-supervised convolutional autoencoder detects core-collapse supernova gravitational waves with performance comparable to supervised CNNs, better generalization to unseen waveforms, and ~120 kpc sensitive distance under Einstein Telescope noise.
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HIcosmo: a differentiable JAX-based framework for cosmology inference
HIcosmo is a new JAX-based differentiable framework for background cosmology inference that matches Cobaya results while delivering 8.7x CPU and up to 20x GPU speedups.
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Model-independent H0 from GWTC-4 standard sirens and TDCOSMO 2025 strong lensing time delays
Combining GWTC-4 standard sirens with TDCOSMO2025 lensing data under the distance sum rule yields H0 = 83.78 +12.53/-10.23 km/s/Mpc (13.6% precision) in one configuration, consistent with both Planck and SH0ES.
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Synergy between CSST and third-generation gravitational-wave detectors: Inferring cosmological parameters using cross-correlation of dark sirens and galaxies
Forecasts that cross-correlating 3G GW dark sirens with CSST photometric galaxies yields 1.04% precision on H0 and 2.04% on Omega_m while also constraining GW clustering bias.
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Resolving the Hubble Tension in the Early Dark Energy Framework with JWST and DESI Data
Axion EDE model fitted to Planck/ACT/SPT CMB, DESI BAO, and JWST UV luminosity function data yields H0 = 71.58 ± 1.05 km s^{-1} Mpc^{-1}, reduces H0 tension to 1.0 sigma, and improves Δχ^{2}_tot = -18.26 over Λ CDM.
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Synergy between CSST and future gravitational-wave detectors: Probing primordial black holes by cross-correlating dark sirens with galaxies
Cross-correlating CSST galaxies with mock GW catalogs from ET2CE and BDET2CE networks can detect PBH merger fractions above ~40% and ~20% respectively via clustering bias differences.
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Measuring the Hubble constant with strongly lensed gravitational waves from space-based detector networks
Simulations indicate joint Taiji+LISA analysis of five SLGW events yields H0 95% credible interval uncertainties of 0.11 (source redshift unknown) or 0.042 (source redshift known).