Impact of redshift distribution uncertainties on Lyman-break galaxy cosmological parameter inference
Fuente:
arXiv
Saved in:
| Main Authors: | Petri, Francesco, Leistedt, Boris, Mortlock, Daniel J., Leja, Joel, Thorp, Stephen, Alsing, Justin, Peiris, Hiranya V., Deger, Sinan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model
by: Thorp, Stephen, et al.
Published: (2024)
by: Thorp, Stephen, et al.
Published: (2024)
pop-cosmos: A comprehensive picture of the galaxy population from COSMOS data
by: Alsing, Justin, et al.
Published: (2024)
by: Alsing, Justin, et al.
Published: (2024)
pop-cosmos: Insights from generative modeling of a deep, infrared-selected galaxy population
by: Thorp, Stephen, et al.
Published: (2025)
by: Thorp, Stephen, et al.
Published: (2025)
Data-Space Validation of High-Dimensional Models by Comparing Sample Quantiles
by: Thorp, Stephen, et al.
Published: (2024)
by: Thorp, Stephen, et al.
Published: (2024)
pop-cosmos: Forward modeling KiDS-1000 redshift distributions using realistic galaxy populations
by: Leistedt, Boris, et al.
Published: (2026)
by: Leistedt, Boris, et al.
Published: (2026)
pop-cosmos: Redshifts and physical properties of KiDS-1000 galaxies
by: Halder, Anik, et al.
Published: (2026)
by: Halder, Anik, et al.
Published: (2026)
StAD: Stein Amortized Divergence for Fast Likelihoods with Diffusion and Flow
by: Jagwani, Gurjeet, et al.
Published: (2026)
by: Jagwani, Gurjeet, et al.
Published: (2026)
Thermostats, Not Engines: A New Picture of Halo Gas Regulation
by: Peiris, Hiranya V., et al.
Published: (2026)
by: Peiris, Hiranya V., et al.
Published: (2026)
Convolutional neural network for Lyman break galaxies classification and redshift regression in DESI (Dark Energy Spectroscopic Instrument)
by: Taran, Julien
Published: (2024)
by: Taran, Julien
Published: (2024)
Benchmarking field-level cosmological inference from galaxy redshift surveys
by: Simon, Hugo, et al.
Published: (2025)
by: Simon, Hugo, et al.
Published: (2025)
Simulation-based inference of deep fields: galaxy population model and redshift distributions
by: Moser, Beatrice, et al.
Published: (2024)
by: Moser, Beatrice, et al.
Published: (2024)
Cosmological inference with halo clustering reconstructed from the redshift-space galaxy distribution
by: Hada, Ryuichiro, et al.
Published: (2026)
by: Hada, Ryuichiro, et al.
Published: (2026)
Scalable hierarchical BayeSN inference: Investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift
by: Grayling, Matthew, et al.
Published: (2024)
by: Grayling, Matthew, et al.
Published: (2024)
Extracting cosmological information from the abundance of galaxy clusters with simulation-based inference
by: Zubeldia, Íñigo, et al.
Published: (2025)
by: Zubeldia, Íñigo, et al.
Published: (2025)
Towards Accurate Field-Level Inference of Massive Cosmic Structures
by: Stopyra, Stephen, et al.
Published: (2023)
by: Stopyra, Stephen, et al.
Published: (2023)
On the redshift evolution of the spin parameter in cosmological simulations
by: Riera, Tomas, et al.
Published: (2026)
by: Riera, Tomas, et al.
Published: (2026)
Deep learning insights into cosmological structure formation
by: Lucie-Smith, Luisa, et al.
Published: (2020)
by: Lucie-Smith, Luisa, et al.
Published: (2020)
Propagating data-driven galaxy redshift distribution uncertainties in 3$\times$2-pt analyses
by: Ruiz-Zapatero, Jaime, et al.
Published: (2026)
by: Ruiz-Zapatero, Jaime, et al.
Published: (2026)
A novel analysis of contamination in Lyman-break galaxy samples at $\boldsymbol{z\sim6-8}$: spatial correlation with intermediate-redshift galaxies at $\boldsymbol{z\sim1.3-2}$
by: Hilmi, Miftahul, et al.
Published: (2024)
by: Hilmi, Miftahul, et al.
Published: (2024)
Quantifying the Impact of LSST $u$-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
by: Crenshaw, John Franklin, et al.
Published: (2025)
by: Crenshaw, John Franklin, et al.
Published: (2025)
Calibrating redshift distributions at $z>2$ with Lyman-$α$ forest cross-correlations
by: Hang, Qianjun, et al.
Published: (2026)
by: Hang, Qianjun, et al.
Published: (2026)
Explaining dark matter halo density profiles with neural networks
by: Lucie-Smith, Luisa, et al.
Published: (2023)
by: Lucie-Smith, Luisa, et al.
Published: (2023)
An Anti-halo Void Catalogue of the Local Super-Volume
by: Stopyra, Stephen, et al.
Published: (2023)
by: Stopyra, Stephen, et al.
Published: (2023)
Digging into the ultraviolet luminosity functions of galaxies at high redshifts: galaxies evolution, reionization, and cosmological parameters
by: Wang, Yi-Ying, et al.
Published: (2024)
by: Wang, Yi-Ying, et al.
Published: (2024)
Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing
by: Euclid Collaboration, et al.
Published: (2026)
by: Euclid Collaboration, et al.
Published: (2026)
Reconstructing redshift distributions with photometric galaxy clustering
by: Peng, Hui, et al.
Published: (2024)
by: Peng, Hui, et al.
Published: (2024)
The limits of feedback from active galactic nuclei
by: Pontzen, Andrew, et al.
Published: (2026)
by: Pontzen, Andrew, et al.
Published: (2026)
The FLAMINGO Project: An assessment of the systematic errors in the predictions of models for galaxy cluster counts used to infer cosmological parameters
by: Kugel, Roi, et al.
Published: (2024)
by: Kugel, Roi, et al.
Published: (2024)
Influence of photometric galaxies redshift distribution in BAO estimation
by: Ferreira, Paula S., et al.
Published: (2025)
by: Ferreira, Paula S., et al.
Published: (2025)
The connection between high-redshift galaxies and Lyman $α$ transmission in the Sherwood-Relics simulations of patchy reionisation
by: Conaboy, Luke, et al.
Published: (2025)
by: Conaboy, Luke, et al.
Published: (2025)
Deep learning insights into non-universality in the halo mass function
by: Guo, Ningyuan, et al.
Published: (2024)
by: Guo, Ningyuan, et al.
Published: (2024)
KiDS+VIKING-450 cosmology with Bayesian hierarchical model redshift distributions
by: Kyriacou, George T., et al.
Published: (2026)
by: Kyriacou, George T., et al.
Published: (2026)
Simulation-based inference from the Lyman-alpha forest 1D power spectrum with CAMELS
by: Sinigaglia, Francesco, et al.
Published: (2026)
by: Sinigaglia, Francesco, et al.
Published: (2026)
Angular correlation functions of bright Lyman-break galaxies at $\mathbf{3 \lesssim z \lesssim 5}$
by: Ye, Isabelle, et al.
Published: (2025)
by: Ye, Isabelle, et al.
Published: (2025)
Optimal data compression for Lyman-$α$ forest cosmology
by: Gerardi, Francesca, et al.
Published: (2023)
by: Gerardi, Francesca, et al.
Published: (2023)
Quantifying the uncertainty in the time-redshift relationship
by: Turner, Michael S.
Published: (2024)
by: Turner, Michael S.
Published: (2024)
Perturbation theory challenge for cosmological parameters estimation II.: Matter power spectrum in redshift space
by: Osato, Ken, et al.
Published: (2023)
by: Osato, Ken, et al.
Published: (2023)
Impact of survey spatial variability on galaxy redshift distributions and the cosmological $3\times2$-point statistics for the Rubin Legacy Survey of Space and Time (LSST)
by: Hang, Qianjun, et al.
Published: (2024)
by: Hang, Qianjun, et al.
Published: (2024)
Systematics mitigation for catalogue-based angular power spectra
by: Cornish, Thomas, et al.
Published: (2025)
by: Cornish, Thomas, et al.
Published: (2025)
Imaging systematics induced by galaxy sub-sample fluctuation: new systematics at second order
by: Kong, Hui, et al.
Published: (2025)
by: Kong, Hui, et al.
Published: (2025)
Similar Items
-
pop-cosmos: Scaleable inference of galaxy properties and redshifts with a data-driven population model
by: Thorp, Stephen, et al.
Published: (2024) -
pop-cosmos: A comprehensive picture of the galaxy population from COSMOS data
by: Alsing, Justin, et al.
Published: (2024) -
pop-cosmos: Insights from generative modeling of a deep, infrared-selected galaxy population
by: Thorp, Stephen, et al.
Published: (2025) -
Data-Space Validation of High-Dimensional Models by Comparing Sample Quantiles
by: Thorp, Stephen, et al.
Published: (2024) -
pop-cosmos: Forward modeling KiDS-1000 redshift distributions using realistic galaxy populations
by: Leistedt, Boris, et al.
Published: (2026)