Related papers: Machine Learning Approach for Estimating Magnetic …
We present self-consistent cosmological magnetohydrodynamic (MHD) simulations that simultaneously follow the formation of a galaxy cluster and the magnetic field ejection by an active galactic nucleus (AGN). We find that the magnetic fields…
We present the first cosmological simulations of primordial magnetic fields derived from the constraints by the Cosmic Microwave Background observations, based on the fields' gravitational effect on cosmological perturbations. We evolved…
The magnetic field of molecular clouds (MCs) plays an important role in the process of star formation: it determins the statistical properties of supersonic turbulence that controls the fragmentation of MCs, controls the angular momentum…
Faraday rotation of the polarization plane in magnetized thermal plasma provides one of the most efficient methods to deduce regular magnetic fields from radio astronomical observations. Since the Faraday rotation measure RM is proportional…
Magnetic fields in large scale structure filaments beyond galaxy clusters remain poorly understood. Superclusters offer a unique setting to study these low density environments, where weak signals make detection challenging. The Faraday…
We present a model for the seeding and evolution of magnetic fields in galaxies by supernovae (SN). SN explosions during galaxy assembly provide seed fields, which are subsequently amplified by compression, shear flows and random motions.…
Exoplanet observations are currently analysed with Bayesian retrieval techniques. Due to the computational load of the models used, a compromise is needed between model complexity and computing time. Analysis of data from future facilities,…
Forthcoming large imaging surveys such as Euclid and the Vera Rubin Observatory Legacy Survey of Space and Time are expected to find more than $10^5$ strong gravitational lens systems, including many rare and exotic populations such as…
Galaxy clusters are valuable cosmological probes. However, cluster mass estimates rely on observable quantities that are affected by complicated baryonic physics in the intracluster medium (ICM), including feedback from active galactic…
This work presents a new approach for premixed turbulent combustion modeling based on convolutional neural networks (CNN). We first propose a framework to reformulate the problem of subgrid flame surface density estimation as a machine…
In this work we study the contribution of magnetic fields to the Sunyaev Zeldovich (SZ) effect in the intracluster medium. In particular we calculate the SZ angular power spectrum and the central temperature decrement. The effect of…
Faraday rotation and synchrotron emission from extragalactic radio sources give evidence for the presence of magnetic fields extending over ~Mpc scales. However, the origin of these fields remains elusive. With new high-resolution grid…
We explore in this paper the ability to constrain the Galactic magnetic field intensity and spatial distribution with the incoming data from the Planck satellite experiment. We perform realistic simulations of the Planck observations at the…
This study quantitatively evaluates the impact of MRI scanner magnetic field strength on the performance and generalizability of deep learning-based segmentation algorithms. Three publicly available MRI datasets (breast tumor, pancreas, and…
We perform a forecast analysis on how well a Euclid-like photometric galaxy cluster survey will constrain the total neutrino mass and effective number of neutrino species. We base our analysis on the Monte Carlo Markov Chains technique by…
The presence of strong magnetic fields in neutron stars, such as in magnetars, may significantly affect their crust-core transition properties and the crust size. This knowledge is crucial in the correct interpretation of astrophysical…
The cosmic microwave background (CMB), carrying the inhomogeneous information of the very early universe, is of great significance for understanding the origin and evolution of our universe. However, observational CMB maps contain serious…
[Abridged] Galaxy clusters are the most massive gravitationally-bound systems in the universe and are widely considered to be an effective cosmological probe. We propose the first Machine Learning method using galaxy cluster properties to…
One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is…
The equipartition model is widely used to estimate magnetic field strength from synchrotron intensity in radio galaxies, yet the validity of its underlying assumptions remains uncertain. Using an Arepo simulation which incorporates a…