Deep learning-based galaxy image deconvolution

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The Epoch of Reionization (EoR) began when galaxies grew in abundance and luminosity, so their escaping Lyman continuum (LyC) radiation started ionizing the surrounding neutral intergalactic medium (IGM). Despite significant recent progress, the nature and ...

In algorithms for solving optimization problems constrained to a smooth manifold, retractions are a well-established tool to ensure that the iterates stay on the manifold. More recently, it has been demonstrated that retractions are a useful concept for ot ...

We present a finite elements-neural network approach for the numerical approximation of parametric partial differential equations. The algorithm generates training data from finite element simulations, and uses a data -driven (supervised) feedforward neura ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

To obtain an accurate cosmological inference from upcoming weak lensing surveys such as the one conducted by Euclid, the shear measurement requires calibration using galaxy image simulations. As it typically requires millions of simulated galaxy images and ...

The method of moments (MOM), as introduced by Roger F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (IE) formulations applied to both electrostatic (part 1) and electrodynamic or full-wave problem ...

The shapes of galaxies, their outer regions in particular, are important guideposts to their formation and evolution. In this work, we report on the discovery of strongly box-shaped morphologies of the otherwise well-studied elliptical and lenticular galax ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

We analyze and compare the satellite halo populations at z similar to 2 in the high-resolution cosmological zoom-in simulations of a 1012 M circle dot target halo (z = 0 mass) carried out on eight widely used astrophysical simulation codes (Art-I, Enzo, Ra ...

We present an end-to-end description of the formation of globular clusters (GCs) combining a treatment for their formation and dynamical evolution within galaxy haloes with a state-of-the-art semi-analytic simulation of galaxy formation. Our approach allow ...

The method of moments (MOM), as introduced by R. F. Harrington more than 50 years ago, is reviewed in the context of the classic potential integral equation (PIE) formulations applied to both electrostatic (part 1) and electrodynamic, or full-wave, problem ...

Context. The cosmological surveys that are planned for the current decade will provide us with unparalleled observations of the distribution of galaxies on cosmic scales, by means of which we can probe the underlying large-scale structure (LSS) of the Univ ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Literature on linear induction motors (LIMs) has proposed several approaches to model the behavior of such devices for different applications. In terms of accuracy and fidelity, field analysis-based models are the most relevant. Closed-form or numerical so ...

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

The distribution of mass in galaxy-scale strong gravitational lenses is often modelled as an elliptical power-law plus 'external shear', which notionally accounts for neighbouring galaxies and cosmic shear along our line of sight. A small amount of externa ...

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI ...

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

Deep learning-based galaxy image deconvolution

Chattez avec Graph Search

New insight on the nature of cosmic reionizers from the CEERS survey

From low-rank retractions to dynamical low-rank approximation and back

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Gibbs sampling the posterior of neural networks

Euclid: Improving the efficiency of weak lensing shear bias calibration

Roger F. Harrington and the Method of Moments: Part 2: Electrodynamics

The Halos and Environments of Nearby Galaxies (HERON) survey IV. Complexity in the boxy galaxies NGC720 and NGC2768

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

The AGORA High-resolution Galaxy Simulations Comparison Project. V. Satellite Galaxy Populations in a Cosmological Zoom-in Simulation of a Milky Way-Mass Halo

On the origin of globular clusters in a hierarchical universe

Roger F. Harrington and the Method of Moments: Part 1: Electrostatics

XXXIV. The effect of linear redshift-space distortions in photometric galaxy clustering and its cross-correlation with cosmic shear

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Pseudo-Three-Dimensional Analytical Model of Linear Induction Motors for High-Speed Applications

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Strong gravitational lensing's 'external shear' is not shear

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance