arXiv subjects

I. Chifu

Publications and source records attributed to I. Chifu.

5 recordsLinked to original sources

arXiv2026

A New Multi-Constraint Potential Field Source Surface (PFSS) Extrapolation Model

The Potential Field Source Surface (PFSS) model is the most used approach for extrapolating the global coronal magnetic field, offering efficiency and strong performance at large scales. However, PFSS assumes a potential coronal field, so it cannot account for distortions from electric currents. More advanced methods, such as nonlinear force-free field (NLFFF) models, can represent these effects but are much more computationally intensive. Recent observational techniques also allow 3D reconstruction of coronal loops, which trace solar magnetic field geometry. This work develops a new approach that constrains the PFSS model using 3D coronal loop information, improving agreement with observations while keeping efficiency. The model is based on PFSS field constraints from photospheric data but allows magnetic field deviations from the potential state within loop-influenced regions, maintaining control over divergence and force-freeness. We adapted NLFFF optimization to the PFSS framework, enabling multiple physical constraints. Our functional includes up to three terms: divergence-free, loop geometry, and force-free. The resulting Python algorithm was tested with synthetic loops, using Carrington rotation 2284 as the lower boundary. This method yields magnetic field solutions that better match the geometry of included loops and controls divergence and force-freeness. Our results show that 3D coronal loop information can be incorporated into PFSS, largely preserving computational efficiency even with many loops. This approach lets PFSS better reflect observed coronal structures without significant computational cost.

astro-ph.SR↗

arXiv2023

Machine learning in solar physics

The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field.

astro-ph.SR↗

arXiv2022

Coronal magnetic field evolution over the cycle 24

The photospheric magnetic field vector is continuously derived from measurements, while reconstruction of the three-dimensional (3D) coronal magnetic field requires modelling with photospheric measurements as a boundary condition. For decades the cycle variation of the magnetic field in the photosphere has been investigated. To present, there is no study to show the evolution of the coronal magnetic flux in the corona, nor the evolution of solar cycle magnetic free energy. The paper aims to analyze the temporal variation of the magnetic field and free magnetic energy in the solar corona for the solar cycle 24 and how the magnetic field behaves in the two hemispheres. We investigate if we can obtain better estimates of the magnetic field at Earth using the nonlinear force-free field (NLFFF) extrapolation method. To model the magnetic field over cycle 24 we apply the NLFFF optimization method to the synoptic vector magnetic maps derived from the observations of Heliospheric and Magnetic Imager (HMI) onboard Solar Dynamic Observatory (SDO). We found that during the solar cycle 24, the maximum of the Sun's dynamics is different from the sunspot number (SSN) maximum peak. The major contribution to the total unsigned flux is provided by the flux coming from the magnetic field structures other than sunspots (MSOS) within latitudes between -30 and +30 degrees. The magnetic flux variation during the solar cycle 24 shows a different evolution in the corona than in the photosphere. We found a correlation value of 0.8 between the derived magnetic energy from our model and the flare energy index derived from observations. On average, cycle 24 had a higher number of sunspots in the northern hemisphere (NH) but stronger flux in the southern hemisphere (SH) which could more effectively reach the higher layers of the atmosphere. The coupling between the hemispheres increases with height.

astro-ph.SR↗

arXiv2012

Study of a Prominence Eruption using PROBA2/SWAP and STEREO/EUVI Data

Observations of the early rise and propagation phases of solar eruptive prominences can provide clues about the forces acting on them through the behavior of their acceleration with height. We have analyzed such an event, observed on 13 April 2010 by SWAP on PROBA2 and EUVI on STEREO. A feature at the top of the erupting prominence was identified and tracked in images from the three spacecraft. The triangulation technique was used to derive the true direction of propagation of this feature. The reconstructed points were fitted with two mathematical models: i) a power-law polynomial function and ii) a cubic smoothing spline, in order to derive the accelerations. The first model is characterized by five degrees of freedom while the second one is characterized by ten degrees of freedom. The results show that the acceleration increases smoothly and it is continuously increasing with height. We conclude that the prominence is not accelerated immediately by local reconnection but rather is swept away as part of a large-scale relaxation of the coronal magnetic field.

astro-ph.SR↗

arXiv2011

Low polarized emission from the core of coronal mass ejections

In white-light coronagraph images, cool prominence material is sometimes observed as bright patches in the core of coronal mass ejections (CMEs). If, as generally assumed, this emission is caused by Thomson-scattered light from the solar surface, it should be strongly polarised tangentially to the solar limb. However, the observations of a CME made with the SECCHI/STEREO coronagraphs on 31 August 2007 show that the emission from these bright core patches is exceptionally low polarised. We used the polarisation ratio method of Moran and Davila (2004) to localise the barycentre of the CME cloud. By analysing the data from both STEREO spacecraft we could resolve the plane-of-the-sky ambiguity this method usually suffers from. Stereoscopic triangulation was used to independently localise the low-polarisation patch relative to the cloud. We demonstrated for the first time that the bright core material is located close to the centre of the CME cloud. We show that the major part of the CME core emission, more than 85% in our case, is H$α$ radiation and only a small fraction is Thomson-scattered light. Recent calculations also imply that the plasma density in the patch is 8 10$^8$ cm$^{-3}$ or more compared to 2.6 10$^6$ cm$^{-3}$ for the Thomson-scattering CME environment surrounding the core material.

astro-ph.SR↗