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We present the Differentiable Lensing Lightcone (DLL), a fully differentiable physical model designed for being used as a forward model in Bayesian inference algorithms requiring access to derivatives of lensing observables with respect to…

Spatial perception is the backbone of many robotics applications, and spans a broad range of research problems, including localization and mapping, point cloud alignment, and relative pose estimation from camera images. Robust spatial…

Machine Learning · Statistics 2019-07-31 Vasileios Tzoumas , Pasquale Antonante , Luca Carlone

One challenge in strong gravitational lensing cosmography is the measurement of time delays between multiple lensed images, which are essential for constraining the Hubble constant (\(H_0\)). In this study, we investigate how assumptions…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-20 Guanhua Rui , Bin Hu , Wei Du

We present a new observable, position-dependent power spectrum, to measure the large-scale structure bispectrum in the squeezed configuration, where one wavenumber is much smaller than the other two. The squeezed-limit bispectrum measures…

Cosmology and Nongalactic Astrophysics · Physics 2015-08-14 Chi-Ting Chiang

Due to the lack of state dimension optimization methods, deep state space models (SSMs) have sacrificed model capacity, training search space, or stability to alleviate computational costs caused by high state dimensions. In this work, we…

Machine Learning · Computer Science 2025-02-03 Minseon Gwak , Seongrok Moon , Joohwan Ko , PooGyeon Park

Angular power spectra are an important measure of the angular clustering of a given distribution. In Cosmology, they are applied to such vastly different observations as galaxy surveys that cover a fraction of the sky and the Cosmic…

Astrophysics · Physics 2007-11-15 Brett Hayes , Robert Brunner , Volodymyr Kindratenko

In recent years, spectral clustering has become a standard method for data analysis used in a broad range of applications. In this paper we propose a new class of algorithms for multiway spectral clustering based on optimization of a…

Machine Learning · Computer Science 2016-05-05 James Voss , Mikhail Belkin , Luis Rademacher

We have measured the angular correlation function w(theta) for a sample of 871 Lyman-break galaxies (LBGs) at z=3. Fitting a power-law to a weighted average of w(theta) from 5 fields, we find the amplitude to be A_w=2 arcsec^{\beta} and the…

We cross-correlate the 100 um Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-08 Adam D. Hincks , Amir Hajian , Graeme E. Addison

Weak gravitational lensing on a cosmological scales can provide strong constraints both on the nature of dark matter and the dark energy equation of state. Most current weak lensing studies are restricted to (two-dimensional) projections,…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-18 Dipak Munshi , Alan Heavens , Peter Coles

While the direct detection of the dark-matter particle remains very challenging, the nature of dark matter could be possibly constrained by comparing the observed abundance and properties of small-scale sub-galactic mass structures with…

Astrophysics of Galaxies · Physics 2023-05-17 D. Bayer , L. V. E. Koopmans , J. P. McKean , S. Vegetti , T. Treu , C. D. Fassnacht , K. Glazebrook

We present a new compilation of inferences of the linear 3D matter power spectrum at redshift $z\,{=}\,0$ from a variety of probes spanning several orders of magnitude in physical scale and in cosmic history. We develop a new lower-noise…

Cosmology and Nongalactic Astrophysics · Physics 2019-09-09 Solène Chabanier , Marius Millea , Nathalie Palanque-Delabrouille

The problem of clustering noisy and incompletely observed high-dimensional data points into a union of low-dimensional subspaces and a set of outliers is considered. The number of subspaces, their dimensions, and their orientations are…

Machine Learning · Statistics 2015-08-24 Reinhard Heckel , Helmut Bölcskei

Berliner (Likelihood and Bayesian prediction for chaotic systems, J. Am. Stat. Assoc. 1991) identified a number of difficulties in using the likelihood function within the Bayesian paradigm which arise both for state estimation and for…

Data Analysis, Statistics and Probability · Physics 2016-12-30 Hailiang Du , Leonard A. Smith

Recent discoveries on neural network pruning reveal that, with a carefully chosen layerwise sparsity, a simple magnitude-based pruning achieves state-of-the-art tradeoff between sparsity and performance. However, without a clear consensus…

Machine Learning · Computer Science 2021-05-11 Jaeho Lee , Sejun Park , Sangwoo Mo , Sungsoo Ahn , Jinwoo Shin

With the development of neural networks and the increasing popularity of automatic driving, the calibration of the LiDAR and the camera has attracted more and more attention. This calibration task is multi-modal, where the rich color and…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Pengjin Wei , Guohang Yan , Yikang Li , Kun Fang , Jie Yang , Wei Liu

Data analysis require a pairwise proximity measure over objects. Recent work has extended this to situations where the distance information between objects is given as comparison results of distances between three objects (triplets). Humans…

Machine Learning · Computer Science 2023-02-21 Sarwan Ali , Muhammad Ahmad , Umair ul Hassan , Muhammad Asad Khan , Shafiq Alam , Imdadullah Khan

Magnification bias, the lensing-induced modification of background source number counts, provides a uniquely powerful probe of the mass density profiles of galaxies and clusters down to kpc scales. Unlike shear-based weak lensing,…

We introduce a collection of statistics appropriate for the study of spinorial quantities defined in three dimensions, focussing on applications to cosmological weak gravitational lensing studies in 3D. In particular, we concentrate on…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Dipak Munshi , Thomas Kitching , Alan Heavens , Peter Coles

We show how thermodynamic properties of molecular models can be computed over a large, multidimensional parameter space by combining multistate reweighting analysis with a linear basis function approach. This approach reduces the…

Chemical Physics · Physics 2016-05-18 Levi N. Naden , Michael R. Shirts