First detection of an ultra-fast outflow (v≈0.07c) in a quiescent galaxy quenched ~9 Gyr ago, suggesting AGN winds can maintain quiescence independent of global star formation.
NAUTILUS: boosting Bayesian importance nested sampling with deep learning
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abstract
We introduce a novel approach to boost the efficiency of the importance nested sampling (INS) technique for Bayesian posterior and evidence estimation using deep learning. Unlike rejection-based sampling methods such as vanilla nested sampling (NS) or Markov chain Monte Carlo (MCMC) algorithms, importance sampling techniques can use all likelihood evaluations for posterior and evidence estimation. However, for efficient importance sampling, one needs proposal distributions that closely mimic the posterior distributions. We show how to combine INS with deep learning via neural network regression to accomplish this task. We also introduce NAUTILUS, a reference open-source Python implementation of this technique for Bayesian posterior and evidence estimation. We compare NAUTILUS against popular NS and MCMC packages, including EMCEE, DYNESTY, ULTRANEST and POCOMC, on a variety of challenging synthetic problems and real-world applications in exoplanet detection, galaxy SED fitting and cosmology. In all applications, the sampling efficiency of NAUTILUS is substantially higher than that of all other samplers, often by more than an order of magnitude. Simultaneously, NAUTILUS delivers highly accurate results and needs fewer likelihood evaluations than all other samplers tested. We also show that NAUTILUS has good scaling with the dimensionality of the likelihood and is easily parallelizable to many CPUs.
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Neglecting linear GR effects biases f_NL at 1–3σ for Euclid/SPHEREx in SFB forecasts; multi-tracer improves Doppler detection and weakly breaks b_ϕ f_NL degeneracy.
Full DES data from SN+BAO+3x2pt yields w0=-0.84, wa=-0.44 with 2.2σ deviation from ΛCDM; adding DESI+CMB reaches 3.0σ while 3x2pt improves figure of merit by ~10%.
Beyond-GR polarization modes in a single supermassive black hole binary show up linearly (not quadratically) in pulsar-timing cross-correlations, massive-graviton dispersion shifts antenna patterns and pulsar-term phases, and most parity-violating birefringence is suppressed at nanohertz frequencies
Generalized interacting dark energy models with constant or dynamical couplings yield analytical density expressions but are not preferred over LambdaCDM by Bayesian evidence from DESI, Pantheon+, and CMB data.
citing papers explorer
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First detection of ultra-fast outflows in a quiescent galaxy
First detection of an ultra-fast outflow (v≈0.07c) in a quiescent galaxy quenched ~9 Gyr ago, suggesting AGN winds can maintain quiescence independent of global star formation.
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Impact and measurability of linear relativistic effects in galaxy surveys
Neglecting linear GR effects biases f_NL at 1–3σ for Euclid/SPHEREx in SFB forecasts; multi-tracer improves Doppler detection and weakly breaks b_ϕ f_NL degeneracy.
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Constraints on Dynamical Dark Energy from Multiple Probes in the Full Dark Energy Survey
Full DES data from SN+BAO+3x2pt yields w0=-0.84, wa=-0.44 with 2.2σ deviation from ΛCDM; adding DESI+CMB reaches 3.0σ while 3x2pt improves figure of merit by ~10%.
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Testing General Relativity with Individual Supermassive Black Hole Binaries
Beyond-GR polarization modes in a single supermassive black hole binary show up linearly (not quadratically) in pulsar-timing cross-correlations, massive-graviton dispersion shifts antenna patterns and pulsar-term phases, and most parity-violating birefringence is suppressed at nanohertz frequencies
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Generalizing the CPL Parametrization through Dark Sector Interaction
Generalized interacting dark energy models with constant or dynamical couplings yield analytical density expressions but are not preferred over LambdaCDM by Bayesian evidence from DESI, Pantheon+, and CMB data.