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Related papers: KaRMMa -- Kappa Reconstruction for Mass Mapping

200 papers

We introduce a method for analyzing radio interferometry data which produces maps which are optimal in the Bayesian sense of maximum posterior probability density, given certain prior assumptions. It is similar to maximum entropy…

Astrophysics · Physics 2009-11-11 Edmund C. Sutton , Benjamin D. Wandelt

We present a new method for constructing three-dimensional mass maps from gravitational lensing shear data. We solve the lensing inversion problem using truncation of singular values (within the context of generalized least squares…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-19 Jake VanderPlas , Andrew Connolly , Bhuvnesh Jain , Mike Jarvis

Probabilistic State Space Models (SSMs) are essential for Reinforcement Learning (RL) from high-dimensional, partial information as they provide concise representations for control. Yet, they lack the computational efficiency of their…

Machine Learning · Computer Science 2024-06-24 Philipp Becker , Niklas Freymuth , Gerhard Neumann

With increasingly large data sets, weak lensing measurements are able to measure cosmological parameters with ever greater precision. However this increased accuracy also places greater demands on the statistical tools used to extract the…

Astrophysics · Physics 2015-05-13 S. Pires , J. -L. Starck , A. Amara , R. Teyssier , A. Refregier , J. Fadili

In compressed sensing one measures sparse signals directly in a compressed form via a linear transform and then reconstructs the original signal. However, it is often the case that the linear transform itself is known only approximately, a…

Information Theory · Computer Science 2013-11-13 Florent Krzakala , Marc Mézard , Lenka Zdeborová

The reliability of cluster lens reconstruction techniques based on weak lensing is studied in terms of the accuracy of their reproduction of the total cluster mass as a function of distance from the cluster center. To do so, a variety of…

Astrophysics · Physics 2011-05-23 Matthias Bartelmann

We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1)…

Galaxy clusters are powerful probes of astrophysics and cosmology through gravitational lensing: the clusters' mass, dominated by 85% dark matter, distorts background light. Yet, mass reconstruction lacks the scalability and large-scale…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Diego Royo , Brandon Zhao , Adolfo Muñoz , Diego Gutierrez , Katherine L. Bouman

Analyses of cosmic shear typically condense weak lensing information over a range of scales to a single cosmological parameter, $S_8$. This paper presents a method to extract more information from Stage-IV cosmic shear measurements by…

Cosmology and Nongalactic Astrophysics · Physics 2024-04-30 Calvin Preston , Alexandra Amon , George Efstathiou

We report the first result of weak gravitational lensing survey on a 2.1 sq deg Rc-band image taken with a wide field camera (Suprime-Cam) on the prime focus of 8.2 m Subaru Telescope. The weak lensing mass reconstruction is applied to the…

Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution and the Bayesian posterior. Such an approximation leads to severe mode collapse and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Weimin Bai , Yuxuan Gu , Yifei Wang , Weijian Luo , He Sun

We model weak gravitational lensing of light by large-scale structure using ray tracing through N-body simulations. The method is described with particular attention paid to numerical convergence. We investigate some of the key…

Astrophysics · Physics 2008-11-26 Chris Vale , Martin White

This paper introduces a computational framework to incorporate flexible regularization techniques in ensemble Kalman methods for nonlinear inverse problems. The proposed methodology approximates the maximum a posteriori (MAP) estimate of a…

Computation · Statistics 2022-05-20 Hwanwoo Kim , Daniel Sanz-Alonso , Alexander Strang

Many nuclear safety applications need fast, portable, and accurate imagers to better locate radiation sources. The Rotating Scatter Mask (RSM) system is an emerging device with the potential to meet these needs. The main challenge is the…

Signal Processing · Electrical Eng. & Systems 2023-08-01 Yilun Zhu , Clayton Scott , Darren Holland , George Landon , Aaron Fjeldsted , Azaree Lintereur

A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and software innovations such as parallel imaging, compressed sensing, and deep…

Medical Physics · Physics 2023-03-27 Yihong Xu , Chad W. Farris , Stephan W. Anderson , Xin Zhang , Keith A. Brown

This paper proposes a novel self-supervised learning method, RELAX-MORE, for quantitative MRI (qMRI) reconstruction. The proposed method uses an optimization algorithm to unroll a model-based qMRI reconstruction into a deep learning…

Biological Physics · Physics 2023-07-26 Wanyu Bian , Albert Jang , Fang Liu

The dark sirens method combines gravitational waves and catalogs of galaxies to constrain the cosmological expansion history, merger rates and mass distributions of compact objects, and the laws of gravity. However, the incompleteness of…

Cosmology and Nongalactic Astrophysics · Physics 2024-12-09 Konstantin Leyde , Tessa Baker , Wolfgang Enzi

We present wide-field (167 deg$^2$) weak lensing mass maps from the Hyper Supreme-Cam Subaru Strategic Program (HSC-SSP). We compare these weak lensing based dark matter maps with maps of the distribution of the stellar mass associated with…

Next-generation cosmic microwave background (CMB) surveys are expected to provide valuable information about the primordial universe by creating maps of the mass along the line of sight. Traditional tools for creating these lensing…

Cosmology and Nongalactic Astrophysics · Physics 2022-05-17 Peikai Li , Ipek Ilayda Onur , Scott Dodelson , Shreyas Chaudhari

In this paper we present a fast and efficient method for the reconstruction of Magnetic Resonance Images (MRI) from severely under-sampled data. From the Compressed Sensing theory we have mathematically modeled the problem as a constrained…

Numerical Analysis · Computer Science 2017-12-01 Damiana Lazzaro , Elena Loli Piccolomini , Fabiana Zama