Related papers: A deep ensemble approach to X-ray polarimetry
Recent advancements in image translation for enhancing mixed-exposure images have demonstrated the transformative potential of deep learning algorithms. However, addressing extreme exposure variations in images remains a significant…
The horizontal orientation angle and vertical inclination angle of an elongated subsurface object are key parameters for object identification and imaging in ground penetrating radar (GPR) applications. Conventional methods can only extract…
Large energy-dependent X-ray polarization degree is detected by the Imaging X-ray Polarimetry Explorer ({IXPE}) in the high-soft emission state of the black hole X-ray binary 4U 1630--47. The highly significant detection (at…
The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields non-Cartesian sampling trajectories that jointly fulfill a target sampling density while…
Deep learning based methods have recently pushed the state-of-the-art on the problem of Single Image Super-Resolution (SISR). In this work, we revisit the more traditional interpolation-based methods, that were popular before, now with the…
Relativistic magnetic reconnection is a potential particle acceleration mechanism for high-frequency BL Lacs (HBLs). The {\it Imaging X-ray Polarimetry Explorer} ({\it IXPE}) scheduled to launch in 2021 has the capability to probe the…
Simulation-based inference (SBI) with neural posterior estimation (NPE) provides rapid X-ray spectral fitting in both Gaussian and Poisson regimes by learning approximate parameter posteriors from simulations. We investigate auto-encoders…
Ensembling a neural network is a widely recognized approach to enhance model performance, estimate uncertainty, and improve robustness in deep supervised learning. However, deep ensembles often come with high computational costs and memory…
We develop a novel algorithm for characterizing Deep Sub-Electron Read Noise (DSERN) image sensors. This algorithm is able to simultaneously compute maximum likelihood estimates of quanta exposure, conversion gain, bias, and read noise of…
The coming decade will be crucial for determining the final design and configuration of a global network of next-generation (XG) gravitational-wave detectors, including the Einstein Telescope (ET) and Cosmic Explorer (CE). In this study,…
The large number of strong lenses discoverable in future astronomical surveys will likely enhance the value of strong gravitational lensing as a cosmic probe of dark energy and dark matter. However, leveraging the increased statistical…
X-ray polarimetry has the potential to make key-contributions to our understanding of galactic compact objects like binary black hole systems and neutron stars, and extragalactic objects like active galactic nuclei, blazars, and Gamma Ray…
Active galactic nuclei (AGN) produce the highest intrinsic luminosities in the Universe from within a compact region. The central engine is thought to be powered by accretion onto a supermassive black hole. A fraction of this huge release…
Wave equations help us to understand phenomena ranging from earthquakes to tsunamis. These phenomena materialise over very large scales. It would be computationally infeasible to track them over a regular mesh. Yet, since the phenomena are…
We present X-ray polarimetry observations from the Imaging X-ray Polarimetry Explorer (IXPE) of three low spectral peak and one intermediate spectral peak blazars, namely 3C 273, 3C 279, 3C 454.3, and S5 0716+714. For none of these objects…
The last decade has seen a leapfrog in the interest in X-ray polarimetry with a number of new polarization measurements in hard X-rays from AstroSat, POLAR, GAP, and PoGO+. The measurements provide some interesting insights into various…
The Sun is the nearest astrophysical source with a very intense emission in the X-ray band. The study of energetic events, such as solar flares, can help us to understand the behaviour of the magnetic field of our star. There are in the…
This paper proposes the first self-supervised 6D object pose prediction from multimodal RGB+polarimetric images. The novel training paradigm comprises 1) a physical model to extract geometric information of polarized light, 2) a…
Well over 700 exoplanets have been detected to date. Only a handful of these have been observed directly. Direct observation is extremely challenging due to the small separation and very large contrast involved. Imaging polarimetry offers a…
Solving 6D pose estimation is non-trivial to cope with intrinsic appearance and shape variation and severe inter-object occlusion, and is made more challenging in light of extrinsic large illumination changes and low quality of the acquired…