Compressing SN Ia distance-redshift data to eleven Gaussian log r_p(z) points with covariance is shown to be operationally lossless for cosmological inference across multiple models and datasets.
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Calibration uncertainties during supernova light-curve fitting cause roughly 50% degradation in dark energy figure of merit for Stage IV surveys, dominating over 13% degradation from model training errors and showing near-degeneracy with cosmology.
Models of interacting bosonic dark energy and fermionic dark matter in Einstein-scalar-Gauss-Bonnet gravity with exponential and power-law potentials are dynamically analyzed and constrained by observational data, showing consistency with LambdaCDM.
Interacting scalar fields coupled to Gauss-Bonnet gravity yield viable dark energy and dark matter models that match Pantheon+ and DES supernova data while preferring over LambdaCDM at high redshifts with Roman mocks.
citing papers explorer
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Lossless Compression of Cosmological Information from Type Ia Supernova Distance Measurements
Compressing SN Ia distance-redshift data to eleven Gaussian log r_p(z) points with covariance is shown to be operationally lossless for cosmological inference across multiple models and datasets.
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Calibration-Induced Systematics in SALT3 Training and Their Impact on Dark Energy Constraints from Stage IV Supernova Surveys
Calibration uncertainties during supernova light-curve fitting cause roughly 50% degradation in dark energy figure of merit for Stage IV surveys, dominating over 13% degradation from model training errors and showing near-degeneracy with cosmology.
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Interacting bosonic dark energy and fermionic dark matter in Einstein scalar Gauss-Bonnet gravity
Models of interacting bosonic dark energy and fermionic dark matter in Einstein-scalar-Gauss-Bonnet gravity with exponential and power-law potentials are dynamically analyzed and constrained by observational data, showing consistency with LambdaCDM.
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Interacting Scalar Fields as Dark Energy and Dark Matter in Einstein scalar Gauss Bonnet Gravity
Interacting scalar fields coupled to Gauss-Bonnet gravity yield viable dark energy and dark matter models that match Pantheon+ and DES supernova data while preferring over LambdaCDM at high redshifts with Roman mocks.