arXiv subjects

Dario Del Moro

Publications and source records attributed to Dario Del Moro.

18 recordsLinked to original sources

arXiv2025

On the Temporal Variability in the Magnetic Dichotomy of Late M Dwarf Stars

Rapidly rotating late M dwarfs are observed in two different branches of magnetic activity, although they operate in the same stellar parameter range. Current empirical evidence indicates that M dwarfs with spectral types ranging from M3 / M4 to late-type M dwarfs, stellar masses smaller than 0.15 M$_\odot$, and rotational period shorter than four days display either a stable dipolar magnetic field or magnetic structures with significant time variability. The magnetic activity of fully convective M dwarfs is known to be regulated by a mechanism named the $α^2$ dynamo. To further constrain the physics of this mechanism, we use a low-dimensional model for thermally driven magnetoconvection producing an $α^2$ dynamo, specifically a modified magnetohydrodynamic (MHD) shell model. Although the model neglects density stratification, it captures the essential nonlinear dynamics of an $α^2$ dynamo. Therefore, the results should be interpreted in a qualitative sense, highlighting possible trends rather than providing direct quantitative predictions for fully convective stars. The model is validated by comparing the statistical properties of magnetic polarity reversals with paleomagnetic data, since the geodynamo provides the only natural $α^2$ dynamo with sufficiently rich reversal statistics. Our findings reveal that increased convective heat transport correlates with more frequent magnetic-polarity reversals, resulting in enhanced magnetic variability. This suggests that the observed magnetic dichotomy in late M dwarfs could be interpreted in terms of differences in global heat transport efficiency. However, additional models and observations of M dwarfs are needed to further constrain this interpretation.

astro-ph.SR↗

arXiv2025

Investigating the Temperature Sensitivity of UV Line Ratios in the 280 nm Region of Solar-like Stars

Stellar UV spectra are fundamental diagnostics of physical and magnetic properties of stars. For instance, lines like Mg II at 280 nm serve as valuable indicators of stellar activity, providing insights into the activity levels of Sun-like stars and their potential influence on the atmospheres of orbiting planets. On the other hand, the effective temperature (Teff) is a fundamental stellar parameter, critical for determining stellar properties such as mass, age, composition and evolutionary status. In this study, we investigate the temperature sensitivity of three lines in the mid-ultraviolet range (i.e., Mg II 280.00 nm, Mg I 285.20 nm, and Si I 286.15 nm). Using spectra from the International Ultraviolet Explorer (IUE), we analyze the behavior of the ratios of their corresponding indices (core/continuum) for a sample of calibrating solar-like stars, and find that the ration R = Mg II/Mg I best traces Teff through a log-log relation. The Teff estimated using this relation on a test-sample of solar-like stars agree with the Teff from the literature at the 95% confidence level. The observed results are interpreted making use of Response Functions as diagnostics. This study extends the well-established use of line depth ratio-temperature relationships, traditionally applied in the visible and near-infrared ranges, to the mid-UV spectrum. With the growing interest in stellar UV spectroscopy, results presented in this paper are potentially relevant for future missions as HWO, MANTIS and UVEX.

astro-ph.SR↗

arXiv2024

Generative Simulations of The Solar Corona Evolution With Denoising Diffusion : Proof of Concept

The solar magnetized corona is responsible for various manifestations with a space weather impact, such as flares, coronal mass ejections (CMEs) and, naturally, the solar wind. Modeling the corona's dynamics and evolution is therefore critical for improving our ability to predict space weather In this work, we demonstrate that generative deep learning methods, such as Denoising Diffusion Probabilistic Models (DDPM), can be successfully applied to simulate future evolutions of the corona as observed in Extreme Ultraviolet (EUV) wavelengths. Our model takes a 12-hour video of an Active Region (AR) as input and simulate the potential evolution of the AR over the subsequent 12 hours, with a time-resolution of two hours. We propose a light UNet backbone architecture adapted to our problem by adding 1D temporal convolutions after each classical 2D spatial ones, and spatio-temporal attention in the bottleneck part. The model not only produce visually realistic outputs but also captures the inherent stochasticity of the system's evolution. Notably, the simulations enable the generation of reliable confidence intervals for key predictive metrics such as the EUV peak flux and fluence of the ARs, paving the way for probabilistic and interpretable space weather forecasting. Future studies will focus on shorter forecasting horizons with increased spatial and temporal resolution, aiming at reducing the uncertainty of the simulations and providing practical applications for space weather forecasting. The code used for this study is available at the following link: https://github.com/gfrancisco20/video_diffusion

astro-ph.SR↗

arXiv2024

Multimodal Flare Forecasting with Deep Learning

Solar flare forecasting mainly relies on photospheric magnetograms and associated physical features to predict forthcoming flares. However, it is believed that flare initiation mechanisms often originate in the chromosphere and the lower corona. In this study, we employ deep learning as a purely data-driven approach to compare the predictive capabilities of chromospheric and coronal UV and EUV emissions across different wavelengths with those of photospheric line-of-sight magnetograms. Our findings indicate that individual EUV wavelengths can provide discriminatory power comparable or better to that of line-of-sight magnetograms. Moreover, we identify simple multimodal neural network architectures that consistently outperform single-input models, showing complementarity between the flare precursors that can be extracted from the distinct layers of the solar atmosphere. To mitigate potential biases from known misattributions in Active Region flare catalogs, our models are trained and evaluated using full-disk images and a comprehensive flare event catalog at the full-disk level. We introduce a deep-learning architecture suited for extracting temporal features from full-disk videos.

astro-ph.SR↗

arXiv2023

CAESAR: Space Weather archive prototype for ASPIS

The project CAESAR (Comprehensive spAce wEather Studies for the ASPIS prototype Realization) is aimed to tackle all the relevant aspects of Space Weather (SWE) and realize the prototype of the scientific data centre for Space Weather of the Italian Space Agency (ASI) called ASPIS (ASI SPace Weather InfraStructure). This contribution is meant to bring attention upon the first steps in the development of the CAESAR prototype for ASPIS and will focus on the activities of the Node 2000 of CAESAR, the set of Work Packages dedicated to the technical design and implementation of the CAESAR ASPIS archive prototype. The product specifications of the intended resources that will form the archive, functional and system requirements gathered as first steps to seed the design of the prototype infrastructure, and evaluation of existing frameworks, tools and standards, will be presented as well as the status of the project in its initial stage.

astro-ph.IM↗

arXiv2023

The exoplanetary magnetosphere extension in Sun-like stars based on the solar wind -- solar UV relation

The Earth's magnetosphere extension is controlled by the solar activity level via solar wind properties. Understanding such a relation in the Solar System is important for predicting also the condition of exoplanetary magnetospheres near Sun-like stars. We use measurements of a chromospheric proxy, the Ca II K index, and solar wind OMNI parameters to connect the solar activity variations, on the decennial time scales, to the solar wind properties. The data span over the time interval 1965-2021, which almost entirely covers the last 5 solar cycles. Using both cross-correlation and mutual information analysis, a 3.2-year lag of the solar wind speed with respect to the Ca II K index is found. Analogously, a 3.6-year lag is found once considering the dynamic pressure. A correlation between the solar wind dynamic pressure and the solar UV emission is found and used to derive the Earth's magnetopause standoff distance. Moreover, the advantage of using a chromospheric proxy, such as the Ca II K index, opens the possibility to extend the relation found for the Sun to Sun-like stars, by linking stellar variability to stellar wind properties. The model is applied to a sample of Sun-like stars as a case study, where we assume the presence of an Earth-like exoplanet at 1 AU. Finally, we compare our results with previous estimates of the magnetosphere extension for the same set of Sun-like stars.

astro-ph.SR↗

arXiv2022

A new catalogue of solar flare events from soft x-ray GOES signal in the period 1986-2020

Solar flares, along with other sun-originated events such as Coronal Mass Ejections, fast solar wind streams, and solar energetic particles are among the most relevant events in Space Weather. Moreover, solar flares are the most energetic processes that occur in our solar system. The in-depth study of their occurrence statistics, both over extended periods or during individual solar cycles, allows us to improve and constrain the basic physical models of their origin. Increasing the number of detected events, especially those of lower intensity, and the number of physical parameters that describe the detected flares is, therefore, a mandatory goal. In this paper, we present a computationally efficient algorithm for the detection of solar flares in the soft-X solar flux provided by the GOES (NASA/NOAA) satellite constellation. Our code produces a new flare catalogue increasing the number of events with respect to the official GOES list. In addition to increasing the number of identified events, the catalogue contains information such as: an estimate of the total energy released, start and end time of the event, possible overlap with other events, background level of the GOES X-ray emission close to the revealed event. After a detailed description of the detection algorithm, we carry out a preliminary analysis of the flares reported in our catalogue and compare our results with the official list of GOES for the period from 1998 to 2020.

astro-ph.SR↗

arXiv2022

Parameter Distributions for the Drag-Based Modeling of CME Propagation

In recent years, ensemble modeling has been widely employed in space weather to estimate uncertainties in forecasts. We here focus on the ensemble modeling of CME arrival times and arrival velocities using a drag-based model, which is well-suited for this purpose due to its simplicity and low computational cost. Although ensemble techniques have previously been applied to the drag-based model, it is still not clear how to best determine distributions for its input parameters, namely the drag parameter and the solar wind speed. The aim of this work is to evaluate statistical distributions for these model parameters starting from a list of past CME-ICME events. We employ LASCO coronagraph observations to measure initial CME position and speed, and in situ data to associate them with an arrival date and arrival speed. For each event we ran a statistical procedure to invert the model equations, producing parameters distributions as output. Our results indicate that the distributions employed in previous works were appropriately selected, even though they were based on restricted samples and heuristic considerations. On the other hand, possible refinements to the current method are also identified, such as the dependence of the drag parameter distribution on the CME being accelerated or decelerated by the solar wind, which deserve further investigation.

physics.space-ph↗

arXiv2021

Flare Forecasting Algorithms Based on High-Gradient Polarity Inversion Lines in Active Regions

Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable precursors of intense flares is an extremely challenging task in the space weather field. In this work, we focus on two metrics as flare precursors, the unsigned flux R, tested on MDI/SOHO data and one of the most used parameters for flare forecasting applications, and a novel topological parameter D representing the complexity of a solar active region. More in detail, we propose an algorithm for the computation of the R value which exploits the higher spatial resolution of HMI maps. This algorithm leads to a differently computed R value, whose functionality is tested on a set of cycle 24th solar flares. Furthermore, we introduce a topological parameter based on the automatic recognition of magnetic polarity-inversion lines in identified active regions, and able to evaluate its magnetic topological complexity. We use both a heuristic approach and a supervised machine learning method to validate the effectiveness of these two descriptors to predict the occurrence of X- or M- class flares in a given solar active region during the following 24 hours period. Our feature ranking analysis shows that both parameters play a significant role in prediction performances. Moreover, the analysis demonstrates that the new topological parameter D is the only one, among 173 overall predictors, which is always present for all test subsets and is systematically ranked within the top-ten positions in all tests concerning the computation of the weighs with which each predictor impacts the flare forecasting.

astro-ph.SR↗

arXiv2019

High-resolution spectropolarimetric observations of the temporal evolution of magnetic fields in photospheric bright points

Context. Magnetic bright points (MBPs) are dynamic, small-scale magnetic elements often found with field strengths of the order of a kilogauss within intergranular lanes in the photosphere. Aims. Here we study the evolution of various physical properties inferred from inverting high-resolution full Stokes spectropolarimetry data obtained from ground-based observations of the quiet Sun at disc centre. Methods. Using automated feature-tracking algorithms, we studied 300 MBPs and analysed their temporal evolution as they evolved to kilogauss field strengths. These properties were inferred using both the NICOLE and SIR Stokes inversion codes. We employ similar techniques to study radiative magnetohydrodynamical simulations for comparison with our observations. Results. Evidence was found for fast (~30 - 100s) amplification of magnetic field strength (by a factor of 2 on average) in MBPs during their evolution in our observations. Similar evidence for the amplification of fields is seen in our simulated data. Conclusions. Several reasons for the amplifications were established, namely, strong downflows preceding the amplification (convective collapse), compression due to granular expansion and mergers with neighbouring MBPs. Similar amplification of the fields and interpretations were found in our simulations, as well as amplification due to vorticity. Such a fast amplification will have implications for a wide array of topics related to small-scale fields in the lower atmosphere, particularly with regard to propagating wave phenomena in MBPs.

astro-ph.SR↗

arXiv2019

The magnetic properties of photospheric magnetic bright points with high resolution spectropolarimetry

Magnetic bright points are small-scale magnetic elements ubiquitous across the solar disk, with the prevailing theory suggesting that they form due to the process of convective collapse. Employing a unique full Stokes spectropolarimetric data set of a quiet Sun region close to disk centre obtained with the Swedish Solar Telescope, we look at general trends in the properties of magnetic bright points. In total we track 300 MBPs in the data set and we employ NICOLE inversions to ascertain various parameters for the bright points such as line-of-sight magnetic field strength and line-of-sight velocity, for comparison. We observe a bimodal distribution in terms of maximum magnetic field strength in the bright points with peaks at ~480 G and ~1700 G, although we cannot attribute the kilogauss fields in this distribution solely to the process of convective collapse. Analysis of MURaM simulations does not return the same bimodal distribution. However, the simulations provide strong evidence that the emergence of new flux and diffusion of this new flux play a significant role in generating the weak bright point distribution seen in our observations.

astro-ph.SR↗

arXiv2018

Speckle statistics in adaptive optics images at visible wavelengths

Residual speckles in adaptive optics (AO) images represent a well-known limitation on the achievement of the contrast needed for faint source detection. Speckles in AO imagery can be the result of either residual atmospheric aberrations, not corrected by the AO, or slowly evolving aberrations induced by the optical system. We take advantage of the high temporal cadence (1 ms) of the data acquired by the System for Coronagraphy with High-order Adaptive Optics from R to K bands-VIS forerunner experiment at the Large Binocular Telescope to characterize the AO residual speckles at visible wavelengths. An accurate knowledge of the speckle pattern and its dynamics is of paramount importance for the application of methods aimed at their mitigation. By means of both an automatic identification software and information theory, we study the main statistical properties of AO residuals and their dynamics. We therefore provide a speckle characterization that can be incorporated into numerical simulations to increase their realism and to optimize the performances of both real-time and postprocessing techniques aimed at the reduction of the speckle noise.

astro-ph.IM↗

arXiv2018

A Probabilistic Approach to the Drag-Based Model

The forecast of the time of arrival of a coronal mass ejection (CME) to Earth is of critical importance for our high-technology society and for any future manned exploration of the Solar System. As critical as the forecast accuracy is the knowledge of its precision, i.e. the error associated to the estimate. We propose a statistical approach for the computation of the time of arrival using the drag-based model by introducing the probability distributions, rather than exact values, as input parameters, thus allowing the evaluation of the uncertainty on the forecast. We test this approach using a set of CMEs whose transit times are known, and obtain extremely promising results: the average value of the absolute differences between measure and forecast is 9.1h, and half of these residuals are within the estimated errors. These results suggest that this approach deserves further investigation. We are working to realize a real-time implementation which ingests the outputs of automated CME tracking algorithms as inputs to create a database of events useful for a further validation of the approach.

physics.space-ph↗

arXiv2017

JP3D compression of solar data-cubes: photospheric imaging and spectropolarimetry

Hyperspectral imaging is an ubiquitous technique in solar physics observations and the recent advances in solar instrumentation enabled us to acquire and record data at an unprecedented rate. The huge amount of data which will be archived in the upcoming solar observatories press us to compress the data in order to reduce the storage space and transfer times. The correlation present over all dimensions, spatial, temporal and spectral, of solar data-sets suggests the use of a 3D base wavelet decomposition, to achieve higher compression rates. In this work, we evaluate the performance of the recent JPEG2000 Part 10 standard, known as JP3D, for the lossless compression of several types of solar data-cubes. We explore the differences in: a) The compressibility of broad-band or narrow-band time-sequence; I or V stokes profiles in spectropolarimetric data-sets; b) Compressing data in [x,y,$λ$] packages at different times or data in [x,y,t] packages of different wavelength; c) Compressing a single large data-cube or several smaller data-cubes; d) Compressing data which is under-sampled or super-sampled with respect to the diffraction cut-off.

astro-ph.IM↗

arXiv2016

N-body model of magnetic flux tubes reconnecting in the solar atmosphere

The investigation of dynamics of the small scale magnetic field on the Sun photosphere is necessary to understand the physical processes occurring in the higher layers of solar atmosphere due to the magnetic coupling between the photosphere and the corona. We present a simulation able to address these phenomena investigating the statistics of magnetic loops reconnections. The simulation is based on N-body model approach and is divided in two computational layers. We simplify the convection problem, interpreting the larger convective scale, mesogranulation, as the result of the collective interaction of convective downflow of granular scale. The N-body advection model is the base to generate a synthetic time series of nanoflares produced by interacting magnetic loops. The reconnection of magnetic field lines is the result of the advection of the magnetic footpoints following the velocity field generated by the interacting downflows. The model gives a quantitative idea of how much energy is expected to be released by the reconfiguration of magnetic loops in the quiet Sun.

astro-ph.SR↗

arXiv2014

Magnetic pattern at supergranulation scale: the Void Size Distribution

The large-scale magnetic pattern of the quiet sun is dominated by the magnetic network. This network, created by photospheric magnetic fields swept into convective downflows, delineates the boundaries of large scale cells of overturning plasma and exhibits voids in magnetic organization. Such voids include internetwork fields, a mixed-polarity sparse field that populate the inner part of network cells. To single out voids and to quantify their intrinsic pattern a fast circle packing based algorithm is applied to 511 SOHO/MDI high resolution magnetograms acquired during the outstanding solar activity minimum between 23 and 24 cycles. The computed Void Distribution Function shows a quasi-exponential decay behavior in the range 10-60 Mm. The lack of distinct flow scales in such a range corroborates the hypothesis of multi-scale motion flows at the solar surface. In addition to the quasi-exponential decay we have found that the voids reveal departure from a simple exponential decay around 35 Mm.

astro-ph.SR↗

arXiv2010

Multiple field-of-view MCAO for a Large Solar Telescope: LOST simulations

In the framework of a 4m class Solar Telescope we studied the performance of the MCAO using the LOST simulation package. In particular, in this work we focus on two different methods to reduce the time delay error which is particularly critical in solar adaptive optics: a) the optimization of the wavefront reconstruction by reordering the modal base on the basis of the Mutual Information and b) the possibility of forecasting the wavefront correction through different approaches. We evaluate these techniques underlining pros and cons of their usage in different control conditions by analyzing the results of the simulations and make some preliminary tests on real data.

astro-ph.IM↗

arXiv2007

3D photospheric velocity field of a Supergranular cell

We investigate the plasma flow properties inside a Supergranular (SG) cell, in particular its interaction with small scale magnetic field structures. The SG cell has been identified using the magnetic network (CaII wing brightness) as proxy, applying the Two-Level Structure Tracking (TST) to high spatial, spectral and temporal resolution observations obtained by IBIS. The full 3D velocity vector field for the SG has been reconstructed at two different photospheric heights. In order to strengthen our findings, we also computed the mean radial flow of the SG by means of cork tracing. We also studied the behaviour of the horizontal and Line of Sight plasma flow cospatial with cluster of bright CaII structures of magnetic origin to better understand the interaction between photospheric convection and small scale magnetic features. The SG cell we investigated seems to be organized with an almost radial flow from its centre to the border. The large scale divergence structure is probably created by a compact region of constant up-flow close to the cell centre. On the edge of the SG, isolated regions of strong convergent flow are nearby or cospatial with extended clusters of bright CaII wing features forming the knots of the magnetic network.

astro-ph↗