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One key task in environmental science is to map environmental variables continuously in space or even in space and time. Machine learning algorithms are frequently used to learn from local field observations to make spatial predictions by…

Machine Learning · Statistics 2024-04-11 Hanna Meyer , Marvin Ludwig , Carles Milà , Jan Linnenbrink , Fabian Schumacher

We present maps classifying regions of the sky according to their information gain potential as quantified by the Fisher information. These maps can guide the optimal retrieval of relevant physical information with targeted cosmological…

Cosmology and Nongalactic Astrophysics · Physics 2022-01-26 Andrija Kostić , Jens Jasche , Doogesh Kodi Ramanah , Guilhem Lavaux

Photometric redshifts of the source galaxies are a key source of systematic uncertainty in the Rubin Observatory Legacy Survey of Space and Time (LSST)'s galaxy clustering and weak lensing analysis, i.e., the $3\times 2$pt analysis. This…

CorStitch is an open-source software developed to automate the creation of accurate georeferenced reef mosaics from video transects obtained through Automated Rapid Reef Assessment System surveys. We utilized a Fourier-based image…

Image and Video Processing · Electrical Eng. & Systems 2025-05-05 Julian Christopher L. Maypa , Johnenn R. Manalang , Maricor N. Soriano

We present CosFly, a box-structured planning and multimodal simulation pipeline for aerial tracking, together with CosFly-Track, a large-scale UAV dataset for dynamic target tracking across diverse environments including urban centers,…

Seamless human-robot manipulation in close proximity relies on accurate forecasts of human motion. While there has been significant progress in learning forecast models at scale, when applied to manipulation tasks, these models accrue high…

Robotics · Computer Science 2023-11-28 Kushal Kedia , Prithwish Dan , Atiksh Bhardwaj , Sanjiban Choudhury

The ionosphere is a critical component of near-Earth space, shaping GNSS accuracy, high-frequency communications, and aviation operations. For these reasons, accurate forecasting and modeling of ionospheric variability has become…

Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to accurately forecast flood crests and issue time-critical…

Machine Learning · Computer Science 2024-03-20 Qingsong Xu , Yilei Shi , Jonathan Bamber , Chaojun Ouyang , Xiao Xiang Zhu

Stage IV large scale structure surveys are promising probes of gravity on cosmological scales. Due to the vast model-space in the modified gravity literature, model-independent parameterisations represent useful and scalable ways to test…

Cosmology and Nongalactic Astrophysics · Physics 2025-03-03 Sankarshana Srinivasan , Daniel B Thomas , Peter L. Taylor

This document is one of the deliverable reports created for the ESCAPE project. ESCAPE stands for Energy-efficient Scalable Algorithms for Weather Prediction at Exascale. The project develops world-class, extreme-scale computing…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-20 Willem Deconinck

Climate change is increasing the frequency of extreme precipitation events, making weather disasters such as flooding and landslides more likely. The ability to accurately nowcast precipitation is therefore becoming more critical for…

Machine Learning · Computer Science 2024-12-05 Daniel Seal , Rossella Arcucci , Salva Rühling-Cachay , César Quilodrán-Casas

This brief code paper presents a new Python-wrapped version of the popular 21cm cosmology simulator, 21cmFAST. The new version, v3+, maintains the same core functionality of previous versions of 21cmFAST, but features a simple and intuitive…

Instrumentation and Methods for Astrophysics · Physics 2020-10-30 Steven G. Murray , Bradley Greig , Andrei Mesinger , Julian B. Muñoz , Yuxiang Qin , Jaehong Park , Catherine A. Watkinson

The Fisher information matrix of the cosmic microwave background (CMB) radiation power spectrum coefficients is a fundamental quantity that specifies the information content of a CMB experiment. In the most general case, its exact…

Cosmology and Nongalactic Astrophysics · Physics 2012-03-30 Franz Elsner , Benjamin D. Wandelt

The Fisher matrix approach (Fisher 1935) allows one to calculate in advance how well a given experiment will be able to estimate model parameters, and has been an invaluable tool in experimental design. In the same spirit, we present here a…

Astrophysics · Physics 2009-01-22 A. F. Heavens , T. D. Kitching , L. Verde

The advent of Stage IV weak lensing surveys will open up a new era in precision cosmology. These experiments will offer more than an order-of-magnitude leap in precision over existing surveys, and we must ensure that the accuracy of our…

Cosmology and Nongalactic Astrophysics · Physics 2021-06-09 Anurag C. Deshpande , Thomas D. Kitching

We present a toolbox of new techniques and concepts for the efficient forecasting of experimental sensitivities. These are applicable to a large range of scenarios in (astro-)particle physics, and based on the Fisher information formalism.…

Instrumentation and Methods for Astrophysics · Physics 2018-02-28 Thomas D. P. Edwards , Christoph Weniger

We present a comparison of Fisher matrix forecasts for cosmological probes with Monte Carlo Markov Chain (MCMC) posterior likelihood estimation methods. We analyse the performance of future Dark Energy Task Force (DETF) stage-III and stage-…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-05 Laura Wolz , Martin Kilbinger , Jochen Weller , Tommaso Giannantonio

The High Latitude Imaging Survey (HLIS) of NASA's Nancy Grace Roman Space Telescope will provide powerful tests of cosmological models through sensitive measurements of cosmic shear, galaxy-galaxy lensing (GGL), and galaxy clustering. As…

Cosmology and Nongalactic Astrophysics · Physics 2026-01-05 Kaili Cao , David H. Weinberg , Vivian Miranda , Nihar Dalal , Tim Eifler , Jiachuan Xu , Haley Bowden

Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versatile tool to develop fast algorithms for addressing large-scale problems. While existing software packages for such matrices often focus on…

Numerical Analysis · Mathematics 2020-01-30 Stefano Massei , Leonardo Robol , Daniel Kressner

We introduce swordfish, a Monte-Carlo-free Python package to predict expected exclusion limits, the discovery reach and expected confidence contours for a large class of experiments relevant for particle- and astrophysics. The tool is…

High Energy Physics - Phenomenology · Physics 2017-12-15 Thomas D. P. Edwards , Christoph Weniger