Neural networks calibrate 2D and 3D Dainotti relations on the Platinum GRB sample via ANN-driven MCMC to produce a model-independent Hubble diagram with reduced scatter.
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Phase-space analysis of a quadratic dark energy model finds that negative η produces stable phantom attractors while the effective equation of state approaches -1 asymptotically from both sides without crossing.
Re-analysis with PR4 Planck likelihoods reduces lensing anomaly significance and curvature preference in Lambda CDM extensions while indicating a preference for evolving dark energy consistent with DESI.
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Model-independent calibration of Gamma-Ray Bursts with neural networks
Neural networks calibrate 2D and 3D Dainotti relations on the Platinum GRB sample via ANN-driven MCMC to produce a model-independent Hubble diagram with reduced scatter.
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Quadratic Dark Energy Phase-Space Dynamics and Analysis
Phase-space analysis of a quadratic dark energy model finds that negative η produces stable phantom attractors while the effective equation of state approaches -1 asymptotically from both sides without crossing.
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Revisiting $\Lambda$CDM extensions in light of re-analyzed CMB data
Re-analysis with PR4 Planck likelihoods reduces lensing anomaly significance and curvature preference in Lambda CDM extensions while indicating a preference for evolving dark energy consistent with DESI.
- Exploring the interplay of late-time dynamical dark energy and new physics before recombination