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Related papers: A deep ensemble approach to X-ray polarimetry

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The Dark MAtter Particle Explorer (DAMPE) instrument is a space-borne cosmic-ray detector, capable of measuring ion fluxes up to $\sim$500 TeV/n. This energy scale is made accessible through its calorimeter, which is the deepest currently…

X-ray Computed Tomography (XCT) techniques have evolved to a point that high-resolution data can be acquired so fast that classic segmentation methods are prohibitively cumbersome, demanding automated data pipelines capable of dealing with…

Image and Video Processing · Electrical Eng. & Systems 2023-12-05 João P C Bertoldo , Etienne Decencière , David Ryckelynck , Henry Proudhon

The Gemini Planet Imager (GPI) has been designed for the direct detection and characterization of exoplanets and circumstellar disks. GPI is equipped with a dual channel polarimetry mode designed to take advantage of the inherently…

The hard X-ray emission from magnetars and other isolated neutron stars remains under-explored. An instrument with higher sensitivity to hard X-rays is critical to understanding the physics of neutron star magnetospheres and also the…

Many pulsar folding algorithms are currently deployed to generate strong SNRs for the total intensity profiles. But they require large observation times to improve the SNR effectively. New approaches to de-noise the pulsar total intensity…

High Energy Astrophysical Phenomena · Physics 2021-08-03 Amitesh Singh , Kamlesh N Pathak

In pulsar astronomy, detecting effective pulsar signals among numerous pulsar candidates is an important research topic. Starting from space X-ray pulsar signals, the two-dimensional autocorrelation profile map (2D-APM) feature modelling…

Instrumentation and Methods for Astrophysics · Physics 2021-09-08 Longqi Wang , Jing Jin , Lu Liu , Yi Shen

Recently, sparsity-based algorithms are proposed for super-resolution spectrum estimation. However, to achieve adequately high resolution in real-world signal analysis, the dictionary atoms have to be close to each other in frequency,…

Machine Learning · Statistics 2015-06-05 Yiyuan She , Huanghuang Li , Jiangping Wang , Dapeng Wu

In the era of exploding survey volumes, traditional methods of spectroscopic analysis are being pushed to their limits. In response, we develop deep-REMAP, a novel deep learning framework that utilizes a regularized, multi-task approach to…

Instrumentation and Methods for Astrophysics · Physics 2025-10-13 Sankalp Gilda

The Imaging X-ray Polarimetry Explorer (IXPE) observations of accreting X-ray pulsars (XRPs) continue to provide novel insights into the physics and geometry of these sources. We present the first X-ray polarimetric study of the persistent…

While the scientific potential of high-energy X-ray and gamma-ray polarimetry has long been recognized, measuring the polarization of high-energy photons is challenging. To date, there has been very few significant detections from an…

Instrumentation and Methods for Astrophysics · Physics 2023-04-05 Denis Bernard , Tanmoy Chattopadhyay , Fabian Kislat , Nicolas Produit

We introduce Deep-CEE (Deep Learning for Galaxy Cluster Extraction and Evaluation), a proof of concept for a novel deep learning technique, applied directly to wide-field colour imaging to search for galaxy clusters, without the need for…

Astrophysics of Galaxies · Physics 2019-11-26 Matthew C. Chan , John P. Stott

Seismic data often contain gaps due to various obstacles in the investigated area and recording instrument failures. Deep learning techniques offer promising solutions for reconstructing missing data parts by leveraging existing…

Geophysics · Physics 2024-04-04 Mohammad Mahdi Abedi , David Pardo , Tariq Alkhalifah

Today, three-dimensional reconstruction of objects has many applications in various fields, and therefore, choosing a suitable method for high resolution three-dimensional reconstruction is an important issue and displaying high-level…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 F. S. Mortazavi , S. Dajkhosh , M. Saadatseresht

Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that…

Numerical Analysis · Mathematics 2020-02-26 Kailai Xu , Eric Darve

Quantifying uncertainty in weather forecasts is critical, especially for predicting extreme weather events. This is typically accomplished with ensemble prediction systems, which consist of many perturbed numerical weather simulations, or…

Machine Learning · Computer Science 2021-03-17 Peter Grönquist , Chengyuan Yao , Tal Ben-Nun , Nikoli Dryden , Peter Dueben , Shigang Li , Torsten Hoefler

The best way to combine the results of deep learning with standard 3D reconstruction pipelines remains an open problem. While systems that pass the output of traditional multi-view stereo approaches to a network for regularisation or…

Computer Vision and Pattern Recognition · Computer Science 2022-07-28 Tristan Laidlow , Jan Czarnowski , Andrea Nicastro , Ronald Clark , Stefan Leutenegger

Images captured nowadays are of varying dimensions with smartphones and DSLR's allowing users to choose from a list of available image resolutions. It is therefore imperative for forensic algorithms such as resampling detection to scale…

Computer Vision and Pattern Recognition · Computer Science 2020-04-29 Mohit Lamba , Kaushik Mitra

X-ray polarimetry of solar flares is still a not well established field of observation of our star. Past polarimeters were not able to measure with a high significance the polarization in X-rays from solar flares. Moreover, they had no…

We present an analytical inversion technique which can be used to recover ionization probabilities from spatially averaged data in an N-dimensional detection scheme. The solution is given as a power series in intensity. For this reason, we…

Quantum Physics · Physics 2015-05-18 J. Strohaber , A. A. Kolomenskii , H. A. Schuessler

The planned in-ice radio array of IceCube-Gen2 at the South Pole will provide unprecedented sensitivity to ultra-high-energy (UHE) neutrinos in the EeV range. The ability of the detector to measure the neutrino's energy and direction is of…

High Energy Astrophysical Phenomena · Physics 2023-08-02 Nils Heyer , Christian Glaser , Thorsten Glüsenkamp