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Gaussian Process Cosmography
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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.
Forward citations
Cited by 18 Pith papers
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General Relativistic Entropic Acceleration at the perturbation level: a CLASS implementation and first Boltzmann-code constraints
First full Boltzmann-code implementation of entropic dark energy, with MCMC constraints from CMB+BAO+SN, yields α≈1 and a fit statistically indistinguishable from ΛCDM.
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Hubble tension: the shape wall
Late-time modifications to the expansion history can raise H0 by at most about 2% (conservative) to 3.7% (permissive) if the CMB acoustic scale is fixed.
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Breaking the Dark Sector Degeneracy with Nonparametric Expansion--Growth Reconstruction
Joint nonparametric expansion–growth reconstruction finds no significant dark-sector interaction or dark-energy dynamics, remaining consistent with ΛCDM over 0≲z≲2.
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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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Model-Independent Reconstruction of Quintessence Potential and Kinetic Energy from DESI DR2 and Pantheon+ Supernovae
Quintessence potential decreases monotonically with redshift while kinetic energy crosses zero near z=1, with negative values at intermediate redshifts being statistical artifacts from derivative reconstruction.
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Latent-Space Gaussian Processes for Dark-Energy Reconstruction from Observational \(H(z)\) Data
Latent-f and latent-H Gaussian process reconstructions from OHD data both yield f(z), w(z), and Om(z) consistent with Lambda-CDM, with no strong predictive preference and small prior-dependent residuals mainly at high...
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Cosmo-Learn: code for learning cosmology using different methods and mock data
An open-source toolkit that simulates late-universe cosmological observations and benchmarks MCMC, genetic algorithms, Gaussian processes, Bayesian ridge regression, and neural networks in one pipeline.
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Multi-Messenger Cosmology: A Route to Accurate Inference of Dark Energy Beyond CPL Parametrization from XG Detectors
A simulation forecast claims CE+ET bright standard sirens can measure dark energy EoS parameters with sigma(w0)=0.010, sigma(wa)=0.049, sigma(wb)=0.072, better than other planned probes.
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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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Late Time Dynamical Dark Energy and the CMB-Distance Ladder Tension
The SNIa absolute-magnitude tension between the distance ladder (−19.204) and CMB+ΛCDM (−19.430) is independent of late-time expansion history, and DESI's w0–wa dark-energy hints shift H0 by only ~0.3–0.4 km/s/Mpc.
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EFT of Dark Energy with Cosmic Chronometers: Reconstructing Background EFT Functions
Reconstruction of EFT background functions from cosmic chronometer Hubble data allows model-independent tests of dark energy evolution in scalar-tensor theories.
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Crosschecking Cosmic Distances from DESI BAO and DES SNe
For DESI DR2 BAO versus DES SNe, the comoving-distance ratio is flat but the inverse-Hubble-distance ratio falls with redshift at 2.3–2.5σ, which the authors attribute to systematics.
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Extended Dark Energy analysis using DESI DR2 BAO measurements
Extended analysis of DESI DR2 data confirms robust evidence for dynamical dark energy with phantom crossing preference, stable under parametric and non-parametric modeling.
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Cosmic distance duality after DESI 2024 data release and dark energy evolution
Using DESI BAO, galaxy clusters, supernovae and Hubble data, the authors find no evidence for violation of the cosmic distance duality and favor flat ΛCDM.
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Non-parametric reconstructions of cosmic curvature: current constraints and forecasts
Using Gaussian-process reconstructions of cosmic distances and expansion rates, the authors find no statistically significant departure from flatness or from the cosmological principle in current data, and they foreca...
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Redshift Evolution of the HII Galaxy $L$-$\sigma$ Relation: Gaussian Process Analysis and Cosmological Implications
Bayesian model comparison using GP regression on Pantheon+ SNIa distances finds a logarithmic redshift correction to the HIIG L-σ relation statistically preferred when intrinsic dispersion is modeled, though evidence ...
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The Quintom theory of dark energy after DESI DR2
This review traces the history of dynamical dark energy, presents the no-go theorem against single-field crossing of w = -1, and surveys viable Quintom constructions including multi-field models and modified gravity i...
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A short review on Quintom dark energy theory
Quintom dark energy models permit the equation of state to cross w=-1, supporting bouncing cosmologies and CMB-based tests of dark energy nature.
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