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.
Search for sterile neutrinos in a universe of vacuum energy interacting with cold dark matter
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abstract
We investigate the cosmological constraints on sterile neutrinos in a universe in which vacuum energy interacts with cold dark matter by using latest observational data. We focus on two specific interaction models, $Q=\beta H\rho_{\rm v}$ and $Q=\beta H\rho_{\rm c}$. To overcome the problem of large-scale instability in the interacting dark energy scenario, we employ the parametrized post-Friedmann (PPF) approach for interacting dark energy to do the calculation of perturbation evolution. The observational data sets used in this work include the Planck 2015 temperature and polarization data, the baryon acoustic oscillation measurements, the type-Ia supernova data, the Hubble constant direct measurement, the galaxy weak lensing data, the redshift space distortion data, and the Planck lensing data. Using the all-data combination, we obtain $N_{\rm eff}<3.522$ and $m_{\nu,{\rm sterile}}^{\rm eff}<0.576$ eV for the $Q=\beta H\rho_{\rm v}$ model, and $N_{\rm eff}=3.204^{+0.049}_{-0.135}$ and $m_{\nu,{\rm sterile}}^{\rm eff}=0.410^{+0.150}_{-0.330}$ eV for the $Q=\beta H\rho_{\rm c}$ model. The latter indicates $\Delta N_{\rm eff}>0$ at the 1.17$\sigma$ level and a nonzero mass of sterile neutrino at the 1.24$\sigma$ level. In addition, for the $Q=\beta H\rho_{\rm v}$ model, we find that $\beta=0$ is consistent with the current data, and for the $Q=\beta H\rho_{\rm c}$ model, we find that $\beta>0$ is obtained at more than 1$\sigma$ level.
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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.
New ACT and DESI data yield model-dependent upper limits on sum of neutrino masses, with holographic dark energy giving the tightest bounds and a consistent preference for degenerate hierarchy.
Upper bounds on total neutrino mass in four phenomenological interacting dark energy models are derived from DESI DR2 BAO plus CMB and SNIa data, showing strong dependence on the interaction term form and statistical preference for models that tighten the bound below the oscillation lower limit.
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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Measuring neutrino mass in light of ACT DR6 and DESI DR2
New ACT and DESI data yield model-dependent upper limits on sum of neutrino masses, with holographic dark energy giving the tightest bounds and a consistent preference for degenerate hierarchy.
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Neutrino mass constraints in interacting dark energy models after DESI DR2
Upper bounds on total neutrino mass in four phenomenological interacting dark energy models are derived from DESI DR2 BAO plus CMB and SNIa data, showing strong dependence on the interaction term form and statistical preference for models that tighten the bound below the oscillation lower limit.