How many simulations do we need for simulation-based inference in cosmology?
Fuente:
arXiv
Saved in:
| Main Authors: | Bairagi, Anirban, Wandelt, Benjamin, Villaescusa-Navarro, Francisco |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
PatchNet: A hierarchical approach for neural field-level inference from Quijote Simulations
by: Bairagi, Anirban, et al.
Published: (2025)
by: Bairagi, Anirban, et al.
Published: (2025)
Transfer learning for multifidelity simulation-based inference in cosmology
by: Saoulis, Alex A., et al.
Published: (2025)
by: Saoulis, Alex A., et al.
Published: (2025)
Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects
by: de Santi, Natalí S. M., et al.
Published: (2023)
by: de Santi, Natalí S. M., et al.
Published: (2023)
Galactification: painting galaxies onto dark matter only simulations using a transformer-based model
by: Pandey, Shivam, et al.
Published: (2025)
by: Pandey, Shivam, et al.
Published: (2025)
$\texttt{GENGARS}$: Accurate non-Gaussian initial conditions with arbitrary bispectrum for N-body simulations
by: Fondi, Emanuele, et al.
Published: (2025)
by: Fondi, Emanuele, et al.
Published: (2025)
Hierarchical summaries for primordial non-Gaussianities
by: Cagliari, M. S., et al.
Published: (2025)
by: Cagliari, M. S., et al.
Published: (2025)
Improved simulation of non-Gaussian temperature and polarization CMB maps
by: Elsner, Franz, et al.
Published: (2009)
by: Elsner, Franz, et al.
Published: (2009)
Multilevel neural simulation-based inference
by: Hikida, Yuga, et al.
Published: (2025)
by: Hikida, Yuga, et al.
Published: (2025)
CHARM: Creating Halos with Auto-Regressive Multi-stage networks
by: Pandey, Shivam, et al.
Published: (2024)
by: Pandey, Shivam, et al.
Published: (2024)
Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison
by: Jeffrey, Niall, et al.
Published: (2023)
by: Jeffrey, Niall, et al.
Published: (2023)
Simulation-based inference with scattering representations: scattering is all you need
by: Lin, Kiyam, et al.
Published: (2024)
by: Lin, Kiyam, et al.
Published: (2024)
A field-level emulator for modeling baryonic effects across hydrodynamic simulations
by: Sharma, Divij, et al.
Published: (2024)
by: Sharma, Divij, et al.
Published: (2024)
Towards Robustness Across Cosmological Simulation Models TNG, SIMBA, ASTRID, and EAGLE
by: Jo, Yongseok, et al.
Published: (2025)
by: Jo, Yongseok, et al.
Published: (2025)
Denoising Diffusion Delensing Delight: Reconstructing the Non-Gaussian CMB Lensing Potential with Diffusion Models
by: Flöss, Thomas, et al.
Published: (2024)
by: Flöss, Thomas, 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)
Zooming by in the CARPoolGP lane: new CAMELS-TNG simulations of zoomed-in massive halos
by: Lee, Max E., et al.
Published: (2024)
by: Lee, Max E., et al.
Published: (2024)
Galaxy cluster count cosmology with simulation-based inference
by: Regamey, M., et al.
Published: (2025)
by: Regamey, M., et al.
Published: (2025)
Simple lessons from complex learning: what a neural network model learns about cosmic structure formation
by: Jamieson, Drew, et al.
Published: (2022)
by: Jamieson, Drew, et al.
Published: (2022)
Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets
by: Roncoli, Andrea, et al.
Published: (2023)
by: Roncoli, Andrea, et al.
Published: (2023)
GalSBI: Phenomenological galaxy population model for cosmology using simulation-based inference
by: Fischbacher, Silvan, et al.
Published: (2024)
by: Fischbacher, Silvan, et al.
Published: (2024)
Hybrid summary statistics: neural weak lensing inference beyond the power spectrum
by: Makinen, T. Lucas, et al.
Published: (2024)
by: Makinen, T. Lucas, et al.
Published: (2024)
Quijote-PNG: Optimizing the summary statistics to measure Primordial non-Gaussianity
by: Jung, Gabriel, et al.
Published: (2024)
by: Jung, Gabriel, et al.
Published: (2024)
Teaching dark matter simulations to speak the halo language
by: Pandey, Shivam, et al.
Published: (2024)
by: Pandey, Shivam, et al.
Published: (2024)
Tests for model misspecification in simulation-based inference: from local distortions to global model checks
by: Montel, Noemi Anau, et al.
Published: (2024)
by: Montel, Noemi Anau, et al.
Published: (2024)
The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison
by: Piras, Davide, et al.
Published: (2024)
by: Piras, Davide, et al.
Published: (2024)
Constraining Cosmology with Simulation-based inference and Optical Galaxy Cluster Abundance
by: Reza, Moonzarin, et al.
Published: (2024)
by: Reza, Moonzarin, et al.
Published: (2024)
CIGaRS I: Combined simulation-based inference from type Ia supernovae and host photometry
by: Karchev, Konstantin, et al.
Published: (2025)
by: Karchev, Konstantin, et al.
Published: (2025)
Cosmological simulations of scale-dependent primordial non-Gaussianity
by: Baldi, Marco, et al.
Published: (2024)
by: Baldi, Marco, et al.
Published: (2024)
From Dark Matter to Galaxies with Convolutional Neural Networks
by: Yip, Jacky H. T., et al.
Published: (2019)
by: Yip, Jacky H. T., et al.
Published: (2019)
Interpretable machine learning of halo gas density profiles: a sensitivity analysis of cosmological hydrodynamical simulations
by: Sorini, Daniele, et al.
Published: (2025)
by: Sorini, Daniele, et al.
Published: (2025)
Model-independent cosmological inference post DESI DR1 BAO measurements
by: Mukherjee, Purba, et al.
Published: (2024)
by: Mukherjee, Purba, et al.
Published: (2024)
Cosmology with Topological Deep Learning
by: Lee, Jun-Young, et al.
Published: (2025)
by: Lee, Jun-Young, et al.
Published: (2025)
Constrained cosmological simulations of the Local Group using Bayesian hierarchical field-level inference
by: Wempe, Ewoud, et al.
Published: (2024)
by: Wempe, Ewoud, et al.
Published: (2024)
Predicting large scale cosmological structure evolution with generative adversarial network-based autoencoders
by: Ullmo, Marion, et al.
Published: (2024)
by: Ullmo, Marion, et al.
Published: (2024)
How DREAMS are made: Emulating Satellite Galaxy and Subhalo Populations with Diffusion Models and Point Clouds
by: Nguyen, Tri, et al.
Published: (2024)
by: Nguyen, Tri, et al.
Published: (2024)
Cosmology from Point Clouds with Dark Matter Halos from the Quijote Simulations
by: Chatterjee, Atrideb, et al.
Published: (2024)
by: Chatterjee, Atrideb, et al.
Published: (2024)
Cylindrical cosmological simulations with StePS
by: Rácz, Gábor, et al.
Published: (2026)
by: Rácz, Gábor, et al.
Published: (2026)
Taming assembly bias for primordial non-Gaussianity
by: Fondi, Emanuele, et al.
Published: (2023)
by: Fondi, Emanuele, et al.
Published: (2023)
Field-level multi-tracers simulation-based inference of cosmological parameters from 3D maps
by: Scelfo, Giulio, et al.
Published: (2026)
by: Scelfo, Giulio, et al.
Published: (2026)
The negative BAO shift in the Ly$α$ forest from cosmological simulations
by: Sinigaglia, Francesco, et al.
Published: (2024)
by: Sinigaglia, Francesco, et al.
Published: (2024)
Similar Items
-
PatchNet: A hierarchical approach for neural field-level inference from Quijote Simulations
by: Bairagi, Anirban, et al.
Published: (2025) -
Transfer learning for multifidelity simulation-based inference in cosmology
by: Saoulis, Alex A., et al.
Published: (2025) -
Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects
by: de Santi, Natalí S. M., et al.
Published: (2023) -
Galactification: painting galaxies onto dark matter only simulations using a transformer-based model
by: Pandey, Shivam, et al.
Published: (2025) -
$\texttt{GENGARS}$: Accurate non-Gaussian initial conditions with arbitrary bispectrum for N-body simulations
by: Fondi, Emanuele, et al.
Published: (2025)