相关论文: Probing Three-Dimensional Magnetic Fields: III -- …

We use models of spectrally resolved cosmic ray (CR) transport in TIGRESS MHD simulations of the local ISM to produce synthetic synchrotron emission and to test, on scales from a few kpc down to ~10 pc, the traditional estimate of magnetic…

The measure of the third-order structure function, Y, is employed in the solar wind to compute the cascade rate of turbulence. In the absence of a mean field B0=0, Y is expected to be isotropic (radial) and independent of the direction of…

It is well-known that magnetohydrodynamic (MHD) turbulence is ubiquitous in astrophysical environments. The correct understanding of the fundamental properties of MHD turbulence is a prerequisite for revealing many key astrophysical…

Diagnostics based on the polarization properties of the synchrotron emission can provide precious information on both the ordered structure and the random level of the magnetic field. While this issue has been already analysed in the radio,…

We present a method for parametric modelling of the physical components of the Galaxy's magnetised interstellar medium, simulating the observables, and mapping out the likelihood space using a Markov Chain Monte-Carlo analysis. We then…

We present an automated approach for identifying magnetospheric regions using supervised machine learning techniques applied to Magnetospheric MultiScale mission data. Our method utilizes ion energy spectra, total magnetic field, total ion…

Considering the spatially separated polarization radiation and Faraday rotation regions to simulate complex interstellar media, we study synchrotron polarization gradient techniques' measurement capabilities. We explore how to trace the…

The conventional MUltiple SIgnal Classification (MUSIC) algorithm is effective for angle-of-arrival estimation in the far-field and can be extended for full source localization in the near-field. However, it suffers from high computational…

In videos, the human's actions are of three-dimensional (3D) signals. These videos investigate the spatiotemporal knowledge of human behavior. The promising ability is investigated using 3D convolution neural networks (CNNs). The 3D CNNs…

Understanding the role of turbulence in shaping the interstellar medium (ISM) is crucial for studying star formation, molecular cloud evolution, and cosmic ray propagation. Central to this is the measurement of the sonic Mach number…

We present 3D models of the Galactic magnetic field including regular and turbulent components, and of the distribution of matter in the Galaxy including relativistic electrons and dust grains. By integrating along the line of sight, we…

Convolutional Neural Network (CNN)-based machine learning systems have made breakthroughs in feature extraction and image recognition tasks in two dimensions (2D). Although there is significant ongoing work to apply CNN technology to…

We have applied an effective numerical scheme for cosmic-ray transport to 3D MHD simulations of jet flow in radio galaxies (see the companion paper by Jones et al. 1999). The marriage of relativistic particle and 3D magnetic field…

Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to…

The advent of novel view synthesis techniques such as NeRF and 3D Gaussian Splatting (3DGS) has enabled learning precise 3D models only from posed monocular images. Although these methods are attractive, they hold two major limitations that…

We investigate how observations of synchrotron intensity fluctuations can be used to probe the sonic and Alfv\'enic Mach numbers of interstellar turbulence, based on mock observations performed on simulations of magnetohydrodynamic…

This work presents a novel Convolutional Neural Network (CNN) architecture and a training procedure to enable robust and accurate pose estimation of a noncooperative spacecraft. First, a new CNN architecture is introduced that has scored a…

Aims: Detecting diffuse synchrotron emission from the cosmic web is still a challenge for current radio telescopes. We aim to make predictions about the detectability of cosmic web filaments from simulations. Methods: We present the first…

Computational material modeling using advanced numerical techniques speeds up the design process and reduces the costs of developing new engineering products. In the field of multiscale modeling, huge computation efforts are expected for…

We propose a machine learning approach to the blind detection of extragalactic point sources on maps of the temperature anisotropies of the cosmic microwave background. Using realistic simulations of the microwave sky as seen by Planck, we…