Gaussian Process Cosmography

Abstract

Gaussian processes provide a method for extracting cosmological information from observations without assuming a cosmological model. We carry out cosmography -- mapping the time evolution of the cosmic expansion -- in a model-independent manner using kinematic variables and a geometric probe of cosmology. Using the state of the art supernova distance data from the Union2.1 compilation, we constrain, without any assumptions about dark energy parametrization or matter density, the Hubble parameter and deceleration parameter as a function of redshift. Extraction of these relations is tested successfully against models with features on various coherence scales, subject to certain statistical cautions.

9 pages, 5 figures; v2 minor changes to match PRD version

References in corpus (23)

• Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant
• Measurements of Omega and Lambda from 42 High-Redshift Supernovae
• The Hubble Space Telescope Cluster Supernova Survey: V. Improving the Dark Energy Constraints Above z>1 and Building an Early-Type-Hosted Supernova Sample
• SALT2: using distant supernovae to improve the use of Type Ia supernovae as distance indicators
• Reconstructing Dark Energy
• Two new diagnostics of dark energy
• Nonparametric Dark Energy Reconstruction from Supernova Data
• Smoothing Supernova Data to Reconstruct the Expansion History of the Universe and its Age
• A model independent approach to the dark energy equation of state
• Nonparametric Reconstruction of the Dark Energy Equation of State
• Mapping the Cosmological Expansion
• What Do We Really Know About Cosmic Acceleration?
• Model independent tests of the standard cosmological model
• The dark degeneracy: On the number and nature of dark components
• Model Independent Reconstruction of the Expansion History of the Universe and the Properties of Dark Energy
• The dark degeneracy and interacting cosmic components
• Nonparametric Reconstruction of the Dark Energy Equation of State from Diverse Data Sets
• Fables of reconstruction: controlling bias in the dark energy equation of state
• Calibrating Dark Energy
• Constraining the dark fluid
• Crossing Statistic: Bayesian interpretation, model selection and resolving dark energy parametrization problem
• The Crossing Statistic: Dealing with Unknown Errors in the Dispersion of Type Ia Supernovae
• Model-Independent Reconstruction of the Expansion History of the Universe from Type Ia Supernovae

Cited by in corpus (215)

• Challenges for $\Lambda$CDM: An update
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• The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics
• To H0 or not to H0?
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• Running Hubble Tension and a H0 Diagnostic
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• DESI 2024: Reconstructing Dark Energy using Crossing Statistics with DESI DR1 BAO data
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• Can dark energy be dynamical?
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• A Comparative Analysis of the Supernova Legacy Survey Sample with ΛCDM and the $R_{\mathrm{h}}=ct$ Universe
• Model Independent Tests of Cosmic Growth vs Expansion
• New Model-independent Method to Test the Curvature of the Universe
• How to use GP: Effects of the mean function and hyperparameter selection on Gaussian Process regression
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• Current Constraints on Anisotropic and Isotropic Dark Energy Models
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• Modified gravity realizations of quintom dark energy after DESI DR2
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• On the consistency of $\Lambda$CDM with CMB measurements in light of the latest Planck, ACT, and SPT data
• Model Independent Expansion History from Supernovae: Cosmology versus Systematics
• Gaussian Processes Reconstruction of the Dark Energy Potential
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• A model-independent test of speed of light variability with cosmological observations
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