4.6 Article

Probabilistic mass-mapping with neural score estimation

Related references

Note: Only part of the references are listed.
Article Astronomy & Astrophysics

KaRMMa - kappa reconstruction for mass mapping

Pier Fiedorowicz et al.

Summary: We propose a new method called KaRMMa for reconstructing mass maps from weak-lensing surveys. By testing it on a suite of dark matter N-body simulations, we find that KaRMMa outperforms the basic Kaiser-Squires method and successfully captures the non-Gaussian nature of the simulated maps.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2022)

Article Astronomy & Astrophysics

Lifting weak lensing degeneracies with a field-based likelihood

Natalia Porqueres et al.

Summary: We present a field-based approach for analyzing cosmic shear data to infer cosmological parameters and dark matter distribution. This approach utilizes a physical gravity model to link the initial matter fluctuations to the non-linear matter distribution, allowing for consistent sampling and updating of cosmological parameters. The field-based approach is found to extract more information from the data compared to methods based on two-point statistics, and it provides tight constraints on parameters from weak lensing data alone.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2022)

Article Astronomy & Astrophysics

Realistic galaxy image simulation via score-based generative models

Michael J. Smith et al.

Summary: The study demonstrates the application of a denoising diffusion probabilistic model (DDPM) for generating realistic galaxy images. Results show that the generated galaxies are highly realistic compared to real data, and metrics are introduced to quantify the similarity and physical properties. The DDPM approach produces sharper and more realistic images than other generative methods, and has potential uses in inpainting occluded data and domain transfer for imaging surveys.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2022)

Article Astronomy & Astrophysics

The CAMELS Multifield Data Set: Learning the Universe's Fundamental Parameters with Artificial Intelligence

Francisco Villaescusa-Navarro et al.

Summary: This paper presents the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) Multifield Data set (CMD), which contains millions of 2D maps and 3D grids from more than 2000 simulated universes. CMD is designed for training machine-learning models and is the largest data set of its kind. The paper describes CMD in detail and focuses on parameter inference as one of its applications.

ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES (2022)

Article Astronomy & Astrophysics

A tomographic spherical mass map emulator of the KiDS-1000 survey using conditional generative adversarial networks

Timothy Wing Hei Yiu et al.

Summary: Large sets of matter density simulations are crucial in large-scale structure cosmology. However, these simulations are computationally expensive. To overcome this challenge, researchers propose map-level density field emulators based on deep generative models. In this study, a novel mass map emulator for the KiDS-1000 survey footprint is introduced, which can generate noise-free spherical maps in seconds.

JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS (2022)

Article Astronomy & Astrophysics

Starlet l1-norm for weak lensing cosmology

Virginia Ajani et al.

Summary: The newly proposed summary statistic "starlet l(1)-norm" for weak lensing observables provides a fast multi-scale calculation of the full void and peak distribution, outperforming commonly used summary statistics in terms of constraining power. It encodes information from all pixels of the map, rather than just local maxima and minima, making it a promising new approach for extracting non-Gaussian cosmological information and inferring cosmological parameters.

ASTRONOMY & ASTROPHYSICS (2021)

Article Computer Science, Artificial Intelligence

Regularisation of neural networks by enforcing Lipschitz continuity

Henry Gouk et al.

Summary: The study investigates the effect of enforcing Lipschitz continuity of neural networks with respect to inputs, providing a technique for computing upper bound of Lipschitz constant for multiple p-norms. It formulates training with bounded Lipschitz constant as a constrained optimization problem and shows that resulting models outperform those trained with common regularizers. The study also demonstrates intuitive tuning of hyperparameters, impact of norm choice on model, and significant performance gains with limited training data.

MACHINE LEARNING (2021)

Article Astronomy & Astrophysics

Power spectrum of halo intrinsic alignments in simulations

Toshiki Kurita et al.

Summary: The study used N-body simulations to investigate intrinsic alignments of halo shapes with large-scale structure, finding non-vanishing IA power spectra over linear to non-linear scales. The IA power spectra show different k-dependences at large and non-linear scales relative to the matter power spectrum, and can be used to probe the underlying matter power spectrum, primordial curvature perturbations, and cosmological parameters.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2021)

Article Astronomy & Astrophysics

Likelihood-free inference with neural compression of DES SV weak lensing map statistics

Niall Jeffrey et al.

Summary: Likelihood-free inference is a novel method for rigorously estimating posterior distributions of parameters using forward modelling of mock data, which can effectively infer cosmological parameters. This study employs weak lensing maps and neural data compression for cosmological parameter inference, demonstrating methods to validate the inference process.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2021)

Article Astronomy & Astrophysics

Weak-lensing mass reconstruction using sparsity and a Gaussian random field

J. -L. Starck et al.

Summary: A novel approach is introduced for reconstructing dark matter mass maps from weak gravitational lensing measurements, which models the matter density field in the Universe as a mixture of sparsity-based and Gaussian random field components. An algorithm called MCALens is proposed, which jointly estimates these components through an alternating minimisation incorporating sparse recovery and proximal iterative Wiener filtering. Experimental results on simulated data demonstrate improved estimation accuracy compared to customised mass-map reconstruction methods.

ASTRONOMY & ASTROPHYSICS (2021)

Article Astronomy & Astrophysics

Power spectrum of intrinsic alignments of galaxies in IllustrisTNG

Jingjing Shi et al.

Summary: By analyzing the cosmological hydrodynamical simulation data, we have identified the intrinsic alignment relationship between the projected 2D galaxy shape/spin and the 3D tidal field, revealing the influence of tidal field on galaxies of different masses and their connection with the primordial tidal field.

JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS (2021)

Article Astronomy & Astrophysics

κTNG: effect of baryonic processes on weak lensing with IllustrisTNG simulations

Ken Osato et al.

Summary: In this study, the authors used a suite of mock weak lensing (WL) maps, the kappa TNG, based on the cosmological hydrodynamic simulations IllustrisTNG, to investigate the effect of baryonic processes on WL observables. They found that baryonic processes reduce small-scale power, suppress the tails of the PDF, peak and minimum counts, and change the total number of peaks and minima. The study also includes the redshift evolution of these effects, which helps in distinguishing baryonic effects from fundamental physics.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2021)

Article Astronomy & Astrophysics

Noise reduction for weak lensing mass mapping: an application of generative adversarial networks to Subaru Hyper Suprime-Cam first-year data

Masato Shirasaki et al.

Summary: In this study, a deep-learning approach based on generative adversarial networks (GANs) was proposed to reduce noise in weak lensing mass maps, which was successfully applied to real data. The effectiveness of the method was confirmed through the study of one-point distribution functions and matching analysis. The PDFs in denoised maps show stronger cosmological dependence, increasing the reliability of cosmological research.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2021)

Article Astronomy & Astrophysics

Cosmic shear cosmology beyond two-point statistics: a combined peak count and correlation function analysis of DES-Y1

Joachim Harnois-Deraps et al.

Summary: In this study, cosmological parameters are constrained through a joint analysis of peak counts and two-point shear correlation functions from the Dark Energy Survey (DES-Y1). The structure growth parameter S-8 is determined to be 0.766(-0.038)(+0.033), providing one of the tightest constraints on S-8 from DES-Y1 weak lensing data with 4.8 percent precision. Through simulations, the expected DES-Y1 peak-count signal for various cosmologies is determined, and the impact of photometric redshift and shear calibration uncertainty is calibrated in the cosmological analysis.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2021)

Article Astronomy & Astrophysics

Deep learning dark matter map reconstructions from DES SV weak lensing data

Niall Jeffrey et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2020)

Article Astronomy & Astrophysics

A new approach to observational cosmology using the scattering transform

Sihao Cheng et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2020)

Review Multidisciplinary Sciences

Array programming with NumPy

Charles R. Harris et al.

NATURE (2020)

Article Astronomy & Astrophysics

Sparse Bayesian mass mapping with uncertainties: peak statistics and feature locations

M. A. Price et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2019)

Article Astronomy & Astrophysics

Efficient optimal reconstruction of linear fields and band-powers from cosmological data

B. Horowitz et al.

JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS (2019)

Article Astronomy & Astrophysics

An improved cosmological parameter inference scheme motivated by deep learning

Dezso Ribli et al.

NATURE ASTRONOMY (2019)

Article Astronomy & Astrophysics

LSST: From Science Drivers to Reference Design and Anticipated Data Products

Zeljko Ivezic et al.

ASTROPHYSICAL JOURNAL (2019)

Article Astronomy & Astrophysics

First results from the IllustrisTNG simulations: the galaxy colour bimodality

Dylan Nelson et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2018)

Article Astronomy & Astrophysics

First results from the IllustrisTNG simulations: matter and galaxy clustering

Volker Springel et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2018)

Article Astronomy & Astrophysics

KiDS-450: cosmological constraints from weak-lensing peak statistics - II: Inference from shear peaks using N-body simulations

Nicolas Martinet et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2018)

Article Astronomy & Astrophysics

First results from the IllustrisTNG simulations: the stellar mass content of groups and clusters of galaxies

Annalisa Pillepich et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2018)

Article Astronomy & Astrophysics

First results from the IllustrisTNG simulations: a tale of two elements - chemical evolution of magnesium and europium

Jill P. Naiman et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2018)

Article Astronomy & Astrophysics

Improving weak lensing mass map reconstructions using Gaussian and sparsity priors: application to DES SV

N. Jeffrey et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2018)

Article Astronomy & Astrophysics

Fast sampling from Wiener posteriors for image data with dataflow engines

N. Jeffrey et al.

ASTRONOMY AND COMPUTING (2018)

Article Astronomy & Astrophysics

Binary Companions of Evolved Stars in APOGEE DR14: Search Method and Catalog of ∼5000 Companions

Adrian M. Price-Whelan et al.

ASTRONOMICAL JOURNAL (2018)

Article Astronomy & Astrophysics

Sparse Reconstruction of the Merging A520 Cluster System

Austin Peel et al.

ASTROPHYSICAL JOURNAL (2017)

Article Astronomy & Astrophysics

Probabilistic Cosmological Mass Mapping from Weak Lensing Shear

M. D. Schneider et al.

ASTROPHYSICAL JOURNAL (2017)

Article Astronomy & Astrophysics

Hierarchical cosmic shear power spectrum inference

Justin Alsing et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2016)

Article Astronomy & Astrophysics

High resolution weak lensing mass mapping combining shear and flexion

F. Lanusse et al.

ASTRONOMY & ASTROPHYSICS (2016)

Article Astronomy & Astrophysics

Planck 2015 results XIII. Cosmological parameters

P. A. R. Ade et al.

ASTRONOMY & ASTROPHYSICS (2016)

Article Astronomy & Astrophysics

Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data

T. Kacprzak et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2016)

Article Astronomy & Astrophysics

High resolution weak lensing mass mapping combining shear and flexion

F. Lanusse et al.

ASTRONOMY & ASTROPHYSICS (2016)

Article Astronomy & Astrophysics

Planck 2015 results XIII. Cosmological parameters

P. A. R. Ade et al.

ASTRONOMY & ASTROPHYSICS (2016)

Article Astronomy & Astrophysics

Cosmological constraints from weak lensing peak statistics with Canada-France-Hawaii Telescope Stripe 82 Survey

Xiangkun Liu et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2015)

Review Physics, Multidisciplinary

Cosmology with cosmic shear observations: a review

Martin Kilbinger

REPORTS ON PROGRESS IN PHYSICS (2015)

Article Astronomy & Astrophysics

Efficient Wiener filtering without preconditioning

F. Elsner et al.

ASTRONOMY & ASTROPHYSICS (2013)

Article Astronomy & Astrophysics

Astropy: A community Python package for astronomy

Thomas P. Robitaille et al.

ASTRONOMY & ASTROPHYSICS (2013)

Article Astronomy & Astrophysics

A compressed sensing approach to 3D weak lensing

A. Leonard et al.

ASTRONOMY & ASTROPHYSICS (2012)

Article Astronomy & Astrophysics

ON DARK PEAKS AND MISSING MASS: A WEAK-LENSING MASS RECONSTRUCTION OF THE MERGING CLUSTER SYSTEM A520

Douglas Clowe et al.

ASTROPHYSICAL JOURNAL (2012)

Article Astronomy & Astrophysics

A STUDY OF THE DARK CORE IN A520 WITH THE HUBBLE SPACE TELESCOPE: THE MYSTERY DEEPENS

M. J. Jee et al.

ASTROPHYSICAL JOURNAL (2012)

Article Astronomy & Astrophysics

Spatial matter density mapping of the STAGES Abell A901/2 supercluster field with 3D lensing

P. Simon et al.

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY (2012)

Article Astronomy & Astrophysics

CMB Map Restoration

J. Bobin et al.

ADVANCES IN ASTRONOMY (2012)

Review Statistics & Probability

Riemann manifold Langevin and Hamiltonian Monte Carlo methods

Mark Girolami et al.

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2011)

Article Computer Science, Artificial Intelligence

A Connection Between Score Matching and Denoising Autoencoders

Pascal Vincent

NEURAL COMPUTATION (2011)

Article Astronomy & Astrophysics

Evidence of the accelerated expansion of the Universe from weak lensing tomography with COSMOS

T. Schrabback et al.

ASTRONOMY & ASTROPHYSICS (2010)

Review Astronomy & Astrophysics

Gravitational lensing

Matthias Bartelmann

CLASSICAL AND QUANTUM GRAVITY (2010)

Article Astronomy & Astrophysics

COSMOS PHOTOMETRIC REDSHIFTS WITH 30-BANDS FOR 2-deg2

O. Ilbert et al.

ASTROPHYSICAL JOURNAL (2009)

Article Astronomy & Astrophysics

COSMOS:: Hubble space telescope observations

N. Scoville et al.

ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES (2007)

Article Astronomy & Astrophysics

COSMOS:: Three-dimensional weak lensing and the growth of structure

Richard Massey et al.

ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES (2007)

Article Computer Science, Interdisciplinary Applications

IPython:: A system for interactive scientific computing

Fernando Perez et al.

COMPUTING IN SCIENCE & ENGINEERING (2007)

Review Astronomy & Astrophysics

The XMM-Newton wide-field survey in the COSMOS field: Statistical properties of clusters of galaxies

A. Finoguenov et al.

ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES (2007)

Article Astronomy & Astrophysics

Weak lensing mass reconstruction using wavelets

JL Starck et al.

ASTRONOMY & ASTROPHYSICS (2006)

Article Astronomy & Astrophysics

The three-point correlation function for spin-2 fields

M Takada et al.

ASTROPHYSICAL JOURNAL (2003)

Article Astronomy & Astrophysics

How accurately can we measure weak gravitational shear?

T Erben et al.

ASTRONOMY & ASTROPHYSICS (2001)