Optimizing Gaussian Process Kernels Using Nested Sampling and ABC Rejection for H(z) Reconstruction
Fuente:
arXiv
Saved in:
| Main Authors: | Jiang, Jia-yan, Jiao, Kang, Zhang, Tong-Jie |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Latent-Space Gaussian Processes for Dark-Energy Reconstruction from Observational \(H(z)\) Data
by: Jiang, Jia-yan, et al.
Published: (2026)
by: Jiang, Jia-yan, et al.
Published: (2026)
Reconstruction of the dark energy scalar field potential by Gaussian process
by: Niu, Jing, et al.
Published: (2023)
by: Niu, Jing, et al.
Published: (2023)
A Non-parametric Reconstruction of the Hubble Parameter $H(z)$ Based on Radial Basis Function Neural Networks
by: Zhang, Jian-Chen, et al.
Published: (2023)
by: Zhang, Jian-Chen, et al.
Published: (2023)
Estimating Cosmological Parameters and Reconstructing Hubble Constant with Artificial Neural Networks: A Test with covariance matrix and mock H(z)
by: Chen, Jie-feng, et al.
Published: (2024)
by: Chen, Jie-feng, et al.
Published: (2024)
Comparative Analysis of EMCEE, Gaussian Process, and Masked Autoregressive Flow in Constraining the Hubble Constant Using Cosmic Chronometers Dataset
by: Niu, Jing, et al.
Published: (2025)
by: Niu, Jing, et al.
Published: (2025)
Model-independent measurement of the Hubble Constant and the absolute magnitude of Type Ia Supernovae
by: Zhang, Jian-Chen, et al.
Published: (2021)
by: Zhang, Jian-Chen, et al.
Published: (2021)
Reconstruction of the Quintessence Scalar Field Potential Using Gaussian Processes
by: Ouardi, Redouane El, et al.
Published: (2026)
by: Ouardi, Redouane El, et al.
Published: (2026)
Redshift-binned constraints on the Hubble constant under $Λ$CDM, CPL, and Padé cosmography
by: Mo, Zhi-Yuan, et al.
Published: (2026)
by: Mo, Zhi-Yuan, et al.
Published: (2026)
FLRW Kinematic-Induced Measurement of the Hubble Constant from Cosmic Chronometer and Redshift Drift Observations
by: Jiao, Kang, et al.
Published: (2025)
by: Jiao, Kang, et al.
Published: (2025)
Reconstructing the growth index $γ$ with Gaussian Processes
by: Oliveira, Fernanda, et al.
Published: (2023)
by: Oliveira, Fernanda, et al.
Published: (2023)
Testing the Cosmic Distance Duality Relation with Neural Kernel Gaussian Process Regression
by: Luo, Xin, et al.
Published: (2025)
by: Luo, Xin, et al.
Published: (2025)
From Hubble to Snap Parameters: A Gaussian Process Reconstruction
by: Jesus, J. F., et al.
Published: (2022)
by: Jesus, J. F., et al.
Published: (2022)
Toward a direct measurement of the cosmic acceleration: The pilot observation of H I 21cm absorption line at FAST
by: Kang, Jiangang, et al.
Published: (2023)
by: Kang, Jiangang, et al.
Published: (2023)
Reconstructing Gamma Ray Burst Energy Relations with Observational H(z) data in Neural Network Framework
by: Aurpa, Nilanjana Bagchi, et al.
Published: (2026)
by: Aurpa, Nilanjana Bagchi, et al.
Published: (2026)
A Stochastic Approach to Reconstructing the Speed of Light in Cosmology
by: Zhang, Cheng-Yu, et al.
Published: (2024)
by: Zhang, Cheng-Yu, et al.
Published: (2024)
Revisiting Gaussian Process Reconstruction for Cosmological Inference: The Generalised GP (Gen GP) Framework
by: Ruchika, et al.
Published: (2025)
by: Ruchika, et al.
Published: (2025)
Cosmological Prediction from the joint observation of MeerKAT and CSST at $z$ = 0.4 $\sim$ 1.2
by: Jiang, Yu-Er, et al.
Published: (2025)
by: Jiang, Yu-Er, et al.
Published: (2025)
Constraints on transition redshift utilizing the latest H(z) measurements and comments on the Hubble tension
by: Hu, Jianping, et al.
Published: (2025)
by: Hu, Jianping, et al.
Published: (2025)
Kernel dependence of the Gaussian Process reconstruction of late Universe expansion history
by: Johnson, Joseph P, et al.
Published: (2025)
by: Johnson, Joseph P, et al.
Published: (2025)
Lower $H_0$ within The Theoretical Insights of Special Cosmological Model Pertains to Derived from The Infinite Future
by: Lyu, Cheqiu, et al.
Published: (2019)
by: Lyu, Cheqiu, et al.
Published: (2019)
Polarization Properties of the Electromagnetic Response to High-frequency Gravitational Wave
by: Li, Jian-Kang, et al.
Published: (2025)
by: Li, Jian-Kang, et al.
Published: (2025)
Reconstructing the Baryonic Acoustic Oscillations in the presence of photo-$z$ uncertainties
by: Chan, Kwan Chuen, et al.
Published: (2023)
by: Chan, Kwan Chuen, et al.
Published: (2023)
Constraining the Hubble Constant with a Simulated Full Covariance Matrix Using Neural Networks
by: Niu, Jing, et al.
Published: (2025)
by: Niu, Jing, et al.
Published: (2025)
High-Dimensional Bayesian Model Comparison in Cosmology with GPU-accelerated Nested Sampling and Neural Emulators
by: Lovick, Toby, et al.
Published: (2025)
by: Lovick, Toby, et al.
Published: (2025)
Redshift drift effect through the observation of HI 21cm signal with SKA
by: Kang, Jiangang, et al.
Published: (2025)
by: Kang, Jiangang, et al.
Published: (2025)
Estimating constraints on cosmological parameters via the canonical and the differential redshift drift with SKA HI 21-cm observations
by: Kang, Jiangang, et al.
Published: (2025)
by: Kang, Jiangang, et al.
Published: (2025)
Null tests with Gaussian Process
by: Gao, Shengqing, et al.
Published: (2025)
by: Gao, Shengqing, et al.
Published: (2025)
Constraints on Baryon Density from the Effective Optical Depth of High-Redshift Quasars
by: Liu, Wen-Fei, et al.
Published: (2025)
by: Liu, Wen-Fei, et al.
Published: (2025)
An independent estimate of H(z) at z = 0.5 from the stellar ages of brightest cluster galaxies
by: Loubser, S. Ilani, et al.
Published: (2025)
by: Loubser, S. Ilani, et al.
Published: (2025)
$\texttt{unimpeded}$: A Public Nested Sampling Database for Bayesian Cosmology
by: Ong, Dily Duan Yi, et al.
Published: (2025)
by: Ong, Dily Duan Yi, et al.
Published: (2025)
Bayesian correction of $H(z)$ cosmic chronometers data with systematic errors
by: Kvint, Nícolas Romeiro, et al.
Published: (2025)
by: Kvint, Nícolas Romeiro, et al.
Published: (2025)
From Scalar $H_0$ to $E(z)$: A Reformulation of the Hubble Tension
by: Lee, Seokcheon
Published: (2026)
by: Lee, Seokcheon
Published: (2026)
DESI z >~ 5 Quasar Survey. I. A First Sample of 400 New Quasars at z ~ 4.7-6.6
by: Yang, Jinyi, et al.
Published: (2023)
by: Yang, Jinyi, et al.
Published: (2023)
Reconstructing a non-linear interaction in the dark sector with cosmological observations
by: Kang, Jiangang
Published: (2021)
by: Kang, Jiangang
Published: (2021)
Revised LOFAR upper limits on the 21-cm signal power spectrum at $\mathbf{z\approx9.1}$ using Machine Learning and Gaussian Process Regression
by: Acharya, Anshuman, et al.
Published: (2024)
by: Acharya, Anshuman, et al.
Published: (2024)
Constraints on bulk viscosity in $f(Q,T)$ gravity from H(z)/Pantheon+ data
by: Koussour, M., et al.
Published: (2024)
by: Koussour, M., et al.
Published: (2024)
Optimising Foreground Modelling for Global 21cm Cosmology with GPU-Accelerated Nested Sampling
by: Tutt, Jacob L., et al.
Published: (2026)
by: Tutt, Jacob L., et al.
Published: (2026)
LATIS: A Sample of IGM-selected Protoclusters and Protogroups at $z \sim 2.5$
by: Newman, Andrew B., et al.
Published: (2025)
by: Newman, Andrew B., et al.
Published: (2025)
Optimal Transport Reconstruction of Biased Tracers in Primordial Non-Gaussian Fields
by: Nikakhtar, Farnik, et al.
Published: (2026)
by: Nikakhtar, Farnik, et al.
Published: (2026)
Non-Gaussianity in CMB lensing from full-sky simulations
by: Hamann, Jan, et al.
Published: (2024)
by: Hamann, Jan, et al.
Published: (2024)
Similar Items
-
Latent-Space Gaussian Processes for Dark-Energy Reconstruction from Observational \(H(z)\) Data
by: Jiang, Jia-yan, et al.
Published: (2026) -
Reconstruction of the dark energy scalar field potential by Gaussian process
by: Niu, Jing, et al.
Published: (2023) -
A Non-parametric Reconstruction of the Hubble Parameter $H(z)$ Based on Radial Basis Function Neural Networks
by: Zhang, Jian-Chen, et al.
Published: (2023) -
Estimating Cosmological Parameters and Reconstructing Hubble Constant with Artificial Neural Networks: A Test with covariance matrix and mock H(z)
by: Chen, Jie-feng, et al.
Published: (2024) -
Comparative Analysis of EMCEE, Gaussian Process, and Masked Autoregressive Flow in Constraining the Hubble Constant Using Cosmic Chronometers Dataset
by: Niu, Jing, et al.
Published: (2025)