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Related papers: Optimizing NILC Extractions of the Thermal Sunyaev…

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The thermal Sunyaev-Zel'dovich (tSZ) effect measures the line-of-sight projection of the thermal pressure of free electrons and lacks any redshift information. By cross correlating the tSZ effect with an external cosmological tracer we can…

Cosmology and Nongalactic Astrophysics · Physics 2014-06-11 Geraint Pratten , Dipak Munshi

We propose a cross-internal linear combination (cross-ILC) approach to measure the small-scale cosmic microwave background (CMB) anisotropies robustly against the contamination from astrophysical signals. In particular, we focus on the…

Cosmology and Nongalactic Astrophysics · Physics 2023-06-21 Srinivasan Raghunathan , Yuuki Omori

We develop a general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases. We focus on Graph Neural Networks (GNNs). The technique works as follows: we first encourage sparse latent…

Machine Learning · Computer Science 2020-11-19 Miles Cranmer , Alvaro Sanchez-Gonzalez , Peter Battaglia , Rui Xu , Kyle Cranmer , David Spergel , Shirley Ho

We propose the use of the kinetic Sunyaev-Zel'dovich (kSZ) effect to probe the circumgalactic medium (CGM), with the aid of a spectroscopic survey covering the same area of a SZ survey. One can design an optimal estimator of the kSZ effect…

Cosmology and Nongalactic Astrophysics · Physics 2016-03-23 Jiawei Shao , Taotao Fang

We present new clean maps of the CMB temperature anisotropies (as measured by Planck) constructed with a novel internal linear combination (ILC) algorithm using directional, scale-discretised wavelets --- Scale-discretised, directional…

Cosmology and Nongalactic Astrophysics · Physics 2016-06-24 Keir K. Rogers , Hiranya V. Peiris , Boris Leistedt , Jason D. McEwen , Andrew Pontzen

Training spiking neural networks (SNNs) remains challenging due to temporal dynamics, non-differentiability of spike events, and sparse event-driven activations. This paper studies how the choice of learning paradigm (unsupervised,…

Artificial Intelligence · Computer Science 2026-03-03 Zofia Rudnicka , Janusz Szczepanski , Agnieszka Pregowska

Strategic classification~(SC) explores how individuals or entities modify their features strategically to achieve favorable classification outcomes. However, existing SC methods, which are largely based on linear models or shallow neural…

The Sunyaev-Zeldovich (SZ) effect has proven to be an extremely powerful tool to study the physical and evolutionary properties of rich clusters of galaxies. Upcoming SZ experiments, with their much improved sensitivity and angular…

Astrophysics · Physics 2009-11-10 G. De Zotti , C. Burigana , A. Cavaliere , L. Danese , G. L. Granato , A. Lapi , P. Platania , L. Silva

We use the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) signal measured by the Planck satellite and the luminous red galaxy (LRG) samples provided by the SDSS DR7 to study the properties of galaxy cluster and intra-cluster…

Cosmology and Nongalactic Astrophysics · Physics 2019-05-08 Yan Gong , Yin-Zhe Ma , Hideki Tanimura

We study the Solid Isotropic Material Penalisation (SIMP) method with a density field generated by a fully-connected neural network, taking the coordinates as inputs. In the large width limit, we show that the use of DNNs leads to a…

Machine Learning · Statistics 2025-01-09 Benjamin Dupuis , Arthur Jacot

Iterative methods such as iterative closest point (ICP) for point cloud registration often suffer from bad local optimality (e.g. saddle points), due to the nature of nonconvex optimization. To address this fundamental challenge, in this…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Ziming Zhang , Yuping Shao , Yiqing Zhang , Fangzhou Lin , Haichong Zhang , Elke Rundensteiner

Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…

Cosmology and Nongalactic Astrophysics · Physics 2019-04-17 Julian Merten , Carlo Giocoli , Marco Baldi , Massimo Meneghetti , Austin Peel , Florian Lalande , Jean-Luc Starck , Valeria Pettorino

The Cherenkov Telescope Array (CTA) will be the next generation gamma-ray observatory and will be the major global instrument for very-high-energy astronomy over the next decade, offering 5 - 10 x better flux sensitivity than current…

Instrumentation and Methods for Astrophysics · Physics 2021-08-03 J. Aschersleben , R. F. Peletier , M. Vecchi , M. H. F. Wilkinson

Illuminant estimation plays a key role in digital camera pipeline system, it aims at reducing color casting effect due to the influence of non-white illuminant. Recent researches handle this task by using Convolution Neural Network (CNN) as…

Computer Vision and Pattern Recognition · Computer Science 2019-02-14 Yongjie Liu , Sijie Shen

We have derived whole-sky CMB polarization maps from the WMAP 5 year polarization data, using the Harmonic Internal Linear Combination (HILC) method. Our HILC method incorporates spatial variability of linear weights in a natural way and…

Astrophysics · Physics 2009-04-06 Jaiseung Kim , Pavel Naselsky , Per Rex Christensen

High-resolution mapping of the intra-cluster medium (ICM) up to high redshift and down to low masses is crucial to derive accurate mass estimates of the galaxy cluster and to understand the systematic effects affecting cosmological studies…

As a training and analysis strategy for convolutional neural networks (CNNs), we slice images into tiled segments and use, for training and prediction, segments that both satisfy a criterion of information diversity and contain sufficient…

Computer Vision and Pattern Recognition · Computer Science 2020-05-06 Steven J. Frank , Andrea M. Frank

Learning to generate complex combinatorial structures satisfying constraints will have transformative impacts in many application domains. However, it is beyond the capabilities of existing approaches due to the highly intractable nature of…

Machine Learning · Computer Science 2023-09-06 Nan Jiang , Yi Gu , Yexiang Xue

We determine the efficacy of the kinematic Sunyaev-Zel'dovich signal extraction pipeline, using pairwise kSZ measurements, in recovering unbiased estimates of the signal and inference of the associated optical depth. We consider the impact…

Cosmology and Nongalactic Astrophysics · Physics 2024-01-15 Yulin Gong , Rachel Bean , Patricio A. Gallardo , Eve M. Vavagiakis , Nicholas Battaglia , Michael Niemack