相关论文: Machine Learning Applications to Kronian Magnetosp…
The interaction between interplanetary small-scale magnetic flux ropes and the magnetic field in the ambient solar wind is an important topic to understand- ing the evolution of magnetic structures in the heliosphere. Through a survey of…
The topology and dynamics of the solar chromosphere are greatly affected by the presence of magnetic fields. The magnetic field can be inferred by analyzing polarimetric observations of spectral lines. Polarimetric signals induced by…
We present astrometric observations of the Saturnian satellites Mimas, Enceladus, Tethys, Dione and Rhea from Cassini Imaging Science Subsystem (ISS) narrow-angle camera (NAC) images. Image sequences were designed to observe mutual…
In the collider phenomenology of extensions of the Standard Model with partner particles, cascade decays occur generically, and they can be challenging to discover when the spectrum of new particles is compressed and the signal cross…
A proof-of-concept solution based on the machine learning techniques has been implemented and tested within the MUonE experiment designed to search for New Physics in the sector of anomalous magnetic moment of a muon. The results of the DNN…
It is widely accepted that spin-orbit coupling (SOC) generally locks spin and spatial degrees of freedom, as a result, the spin, despite being an axial vector, is fixed and cannot rotate independently, and the magnetic system should be…
Detection of a separator line that connects magnetic nulls and the determination of the dynamics and plasma environment of such a structure can improve our understanding of the three-dimensional (3D) magnetic reconnection process. However,…
Hamiltonian parameter estimation is crucial in condensed matter physics, but time and cost consuming in terms of resources used. With advances in observation techniques, high-resolution images with more detailed information are obtained,…
Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…
Magnetic reconnection is an important driving mechanism of many chromospheric phenomena, e.g., UV bursts and chromospheric jets. Information about magnetic field is indispensable for analyzing chromospheric magnetic reconnection, which is…
Machine learning techniques are utilised in several areas of astrophysical research today. This dissertation addresses the application of ML techniques to two classes of problems in astrophysics, namely, the analysis of individual…
Muons and other ionizing radiation produced by cosmic rays and radiative decays affect CMOS/CCD sensor. When particles colliding with sensors atoms cause specific kind of noise on images recorded by cameras. We present a concept and…
The last 22.5 orbits of the Cassini mission brought the spacecraft to less than 3000 km from Saturn's 1-bar surface. These close encounters offered an unprecedented view of Saturn's magnetic field, including contributions from the internal…
Symmetry is a key feature observed in nature (from flowers and leaves, to butterflies and birds) and in human-made objects (from paintings and sculptures, to manufactured objects and architectural design). Rotational, translational, and…
The development of machine learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals. However, creating interatomic potentials for magnetic systems that account for both magnetic…
We take a pragmatic definition of reconnection to find locations where a reconnection electric field causes a ExB drift that carries two components of the magnetic field towards their elimination. With this in mind as our target, we observe…
Magnetic reconnection is a process that changes magnetic field topology in highly conducting fluids. Within the standard Sweet-Parker model, this process would be too slow to explain observations (e.g. solar flares). In reality, the process…
We present the results of numerical simulations of wave-induced magnetic reconnection in a model of the solar atmosphere. In the magnetic field geometry we study in this article, the waves, driven by a monochromatic piston and a driver…
In this work, we propose a deep learning-based classification model of astronomical objects using alerts reported by the Zwicky Transient Facility (ZTF) survey. The model takes as inputs sequences of stamp images and metadata contained in…
Complex behavior poses challenges in extracting models from experiment. An example is spin liquid formation in frustrated magnets like Dy$_2$Ti$_2$O$_7$. Understanding has been hindered by issues including disorder, glass formation, and…