arXiv subjects

Paolo Massa

Publications and source records attributed to Paolo Massa.

At least 19 recordsLinked to original sources

arXiv2025

Radio, X-ray, and EUV signatures of internal and external reconnection of an erupting flux rope

We analyse imaging (EUV, X-ray) and spectral (radio, X-ray) data obtained by ground based and space instruments on board space missions both on Earth (Fermi, Hinode, Solar Dynamics Observatory) and solar orbit (Solar Orbiter, STEREO-A), which provide a multi-directional view on the same event. The combination of EUV and X-ray images and X-ray spectra allowed us to identify hot loops in the vicinity of the filament before its eruption. We interpreted their interaction with the rising filament as a signature of an arcade-to-rope reconnection geometry. The subsequent EUV brightening within the filament revealed helical structure of the erupting rope. We explained co-temporal radio slowly positively drifting bursts as a result of beam acceleration within the magnetic rope and propagation along the helical structure. Corresponding X-ray spectra were consistent with a thermal origin. The filament rising was accompanied by co-temporal normal and reverse drift type III radio bursts. We interpreted them as a signature of a reconnection event and estimated electron density at the reconnection site. Further untwisting of the helical structure led to formation of a quasi-circular EUV structure seen from Earth and STEREO-A. Its occurrence was co-temporal with a unique tangle of radio U- and inverse U-bursts. We proposed that several accelerated beams propagate within that complex structure and generate the burst tangle. During the start of the flare hard X-ray emission was concentrated near the filament leg only suggesting predominant propagation of the beams towards its rooting. We collected multi-wavelength observations indicating interaction of the erupting magnetic flux rope with the overlying arcade and internal magnetic reconnection inside the rising flux rope.

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arXiv2025

Spectral component imaging of solar X-ray flares

Solar hard X-ray observations provide diagnostics of the hottest plasmas and of nonthermal electron populations present during solar flares and coronal mass ejections. HXR images of specific energy ranges often contain overlapping contributions of these components, complicating their interpretation. This is even more challenging as HXR imagers generally use an indirect imaging system. Our work aims to separately image individual spectral components, such as thermal loops, superhot sources, and nonthermal footpoint sources, rather than obtaining images of specific energy ranges that show a combination of all components. We introduce a new method called spectral component imaging and apply it to observations provided by the Spectrometer/Telescope for Imaging X-rays (STIX) aboard Solar Orbiter. First, the flare integrated HXR spectrum is fitted with individual spectral components to get the relative contributions of each component in each native STIX energy channel. In a second step, a set of linear equations is created based on these weights and the observed, energy-dependent STIX visibilities. The visibilities of the individual spectral components are derived by means of a linear least-squares approach and are subsequently utilized for image reconstructions. We demonstrate the effectiveness of spectral component imaging on four different flares observed by STIX. This method provides powerful diagnostics, particularly for flares with hot and superhot components, allowing us to spatially separate these two thermal components. We apply our methodology to the nonthermal peak of the X7.1 flare SOL2024-10-01, and we find that the superhot component is located 4.8 Mm away from the hot thermal loops. The thermal energy of the superhot component is approximately 20% of the energy content of the hot component, highlighting the significance of superhot components in the total flare energy budget.

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arXiv2025

PRESOL: a web-based computational setting for feature-based flare forecasting

Solar flares are the most explosive phenomena in the solar system and the main trigger of the events' chain that starts from Coronal Mass Ejections and leads to geomagnetic storms with possible impacts on the infrastructures at Earth. Data-driven solar flare forecasting relies on either deep learning approaches, which are operationally promising but with a low explainability degree, or machine learning algorithms, which can provide information on the physical descriptors that mostly impact the prediction. This paper describes a web-based technological platform for the execution of a computational pipeline of feature-based machine learning methods that provide predictions of the flare occurrence, feature ranking information, and assessment of the prediction performances.

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arXiv2025

CLEAN and multi-scale CLEAN for STIX in Solar Orbiter

CLEAN is a well-established deconvolution approach to Fourier imaging at both radio wavelwengths and hard X-ray energies. However, specifically for hard X-ray imaging, CLEAN suffers two significant drawbacks: a rather limited degree of automation, and a tendency to under-resolution. This paper introduces a multi-scale version of CLEAN specifically tailored to the reconstruction of images from measurements observed by the Spectrometer/Telescope for Imaging X-rays (STIX) on-board Solar Orbiter. Using synthetic STIX data, this study shows that multi-scale CLEAN may represent a reliable solution to the two previously mentioned CLEAN limitations. Further, this paper shows the performances of CLEAN and its multi-scale release in reconstructing experimental real scenarios characterized by complex emission morphologies.

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arXiv2025

Convergence rates for Tikhonov regularization on compact sets: application to neural networks

In this work, we consider ill-posed inverse problems in which the forward operator is continuous and weakly closed, and the sought solution belongs to a weakly closed constraint set. We propose a regularization method based on minimizing the Tikhonov functional on a sequence of compact sets which is dense in the intersection between the domain of the forward operator and the constraint set. The index of the compact sets can be interpreted as an additional regularization parameter. We prove that the proposed method is a regularization, achieving the same convergence rates as classical Tikhonov regularization and attaining the optimal convergence rate when the forward operator is linear. Moreover, we show that our methodology applies to the case where the constrained solution space is parametrized by means of neural networks (NNs), and the constraint is obtained by composing the last layer of the NN with a suitable activation function. In this case the dense compact sets are defined by taking a family of bounded weight NNs with increasing weight bound. Finally, we present some numerical experiments in the case of Computerized Tomography to compare the theoretical behavior of the reconstruction error with that obtained in a finite dimensional and non-asymptotic setting. The numerical tests also show that our NN-based regularization method is able to provide piece-wise constant solutions and to preserve the sharpness of edges, thus achieving lower reconstruction errors compared to the classical Tikhonov approach for the same level of noise in the data.

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arXiv2025

Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model Approach

The spatial properties of the solar magnetic field are crucial to decoding the physical processes in the solar interior and their interplanetary effects. However, observations from older instruments, such as the Michelson Doppler Imager (MDI), have limited spatial or temporal resolution, which hinders the ability to study small-scale solar features in detail. Super resolving these older datasets is essential for uniform analysis across different solar cycles, enabling better characterization of solar flares, active regions, and magnetic network dynamics. In this work, we introduce a novel diffusion model approach for Super-Resolution and we apply it to MDI magnetograms to match the higher-resolution capabilities of the Helioseismic and Magnetic Imager (HMI). By training a Latent Diffusion Model (LDM) with residuals on downscaled HMI data and fine-tuning it with paired MDI/HMI data, we can enhance the resolution of MDI observations from 2"/pixel to 0.5"/pixel. We evaluate the quality of the reconstructed images by means of classical metrics (e.g., PSNR, SSIM, FID and LPIPS) and we check if physical properties, such as the unsigned magnetic flux or the size of an active region, are preserved. We compare our model with different variations of LDM and Denoising Diffusion Probabilistic models (DDPMs), but also with two deterministic architectures already used in the past for performing the Super-Resolution task. Furthermore, we show with an analysis in the Fourier domain that the LDM with residuals can resolve features smaller than 2", and due to the probabilistic nature of the LDM, we can asses their reliability, in contrast with the deterministic models. Future studies aim to super-resolve the temporal scale of the solar MDI instrument so that we can also have a better overview of the dynamics of the old events.

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arXiv2025

Solar flares as electron accelerators: toward a resolution of the acceleration efficiency issue

A major open issue concerning the active Sun is the effectiveness with which magnetic reconnection accelerates electrons in flares. A paper published by {\em{Nature}} in 2022 used microwave observations to conclude that the Sun is an almost ideal accelerator, energizing nearly all electrons within a coronal volume to nonthermal energies. Shortly thereafter, a paper published in {\em{Astrophysical Journal Letters}} used hard X-ray measurements \emph{of the same event} to reach the contradictory conclusion that less than 1\% of the available electrons were accelerated. Here we address this controversy by using spatially resolved observations of hard X-ray emission and a spectral inversion method to determine the evolution of the electron spectrum throughout the flare. So we estimated the density of the medium where electrons accelerate and, from this, the ratio of accelerated to ambient electron densities. Results show that this ratio never exceeds a percent or so in the cases analyzed.

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arXiv2024

A machine learning approach for computing solar flare locations in X-rays on-board Solar Orbiter/STIX

The Spectrometer/Telescope for Imaging X-rays (STIX) on-board the ESA Solar Orbiter mission retrieves the coordinates of solar flare locations by means of a specific sub-collimator, named the Coarse Flare Locator (CFL). When a solar flare occurs on the Sun, the emitted X-ray radiation casts the shadow of a peculiar "H-shaped" tungsten grid over the CFL X-ray detector. From measurements of the areas of the detector that are illuminated by the X-ray radiation, it is possible to retrieve the $(x,y)$ coordinates of the flare location on the solar disk. In this paper, we train a neural network on a dataset of real CFL observations to estimate the coordinates of solar flare locations. Further, we apply a post-training quantization technique specifically tailored to the adopted model architecture. This technique allows all computations to be in integer arithmetic at inference time, making the model compatible with the STIX computational requirements. We show that our model outperforms the currently adopted algorithm for estimating the flare locations from CFL data regarding prediction accuracy while requiring fewer parameters. We finally discuss possible future applications of the proposed model on-board STIX.

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arXiv2024

Identifying synergies between VLBI and STIX imaging

Reconstructing an image from sparsely sampled Fourier data is an ill-posed inverse problem that occurs in a variety of subjects within science, including the data analysis for Very Long Baseline Interferometry (VLBI) and the Spectrometer/Telescope for Imaging X-rays (STIX) for solar observations. Despite ongoing parallel developments of novel imaging algorithms, synergies remain unexplored. We study the synergies between the data analysis for the STIX instrument and VLBI, compare the methodologies and evaluate their potential. In this way, we identify key trends in the performance of several algorithmic ideas and draw recommendations for the future. To this end, we organized a semi-blind imaging challenge with data sets and source structures that are typical for sparse VLBI, specifically in the context of the Event Horizon Telescope (EHT), and for STIX observations. 17 different algorithms from both communities, from 6 different imaging frameworks, participated in the challenge, marking this work the largest scale code comparisons for STIX and VLBI to date. Strong synergies between the two communities have been identified, as can be proven by the success of the imaging methods proposed for STIX in imaging VLBI data sets and vice versa. Novel imaging methods outperform the standard CLEAN algorithm significantly in every test-case. Improvements over the performance of CLEAN make deeper updates to the inverse modeling pipeline necessary, or consequently replacing inverse modeling with forward modeling. Entropy-based and Bayesian methods perform best on STIX data. The more complex imaging algorithms utilizing multiple regularization terms (recently proposed for VLBI) add little to no additional improvements for STIX, but outperform the other methods on EHT data. This work demonstrates the great synergy between the STIX and VLBI imaging efforts and the great potential for common developments.

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arXiv2024

AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data

AI-FLARES (Artificial Intelligence for the Analysis of Solar Flares Data) is a research project funded by the Agenzia Spaziale Italiana and by the Istituto Nazionale di Astrofisica within the framework of the ``Attività di Studio per la Comunità Scientifica Nazionale Sole, Sistema Solare ed Esopianeti'' program. The topic addressed by this project was the development and use of computational methods for the analysis of remote sensing space data associated to solar flare emission. This paper overviews the main results obtained by the project, with specific focus on solar flare forecasting, reconstruction of morphologies of the flaring sources, and interpretation of acceleration mechanisms triggered by solar flares.

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arXiv2023

Variation of the electron flux spectrum along a solar flare loop as inferred from STIX hard X-ray observations

Regularized imaging spectroscopy was introduced for the construction of electron flux images at different energies from count visibilities recorded by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). In this work we seek to extend this approach to data from the Spectrometer/Telescope for Imaging X-rays (STIX) on-board the Solar Orbiter mission. Our aims are to demonstrate the feasibility of regularized imaging spectroscopy as a method for analysis of STIX data, and also to show how such analysis can lead to insights into the physical processes affecting the nonthermal electrons responsible for the hard X-ray emission observed by STIX. STIX records imaging data in an intrinsically different manner from RHESSI. Rather than sweeping the angular frequency plane in a set of concentric circles (one circle per detector), STIX uses $30$ collimators, each corresponding to a specific angular frequency. In this paper we derive an appropriate modification of the previous computational approach for the analysis of the visibilities observed by STIX. This approach also allows for the observed count data to be placed into non-uniformly-spaced energy bins. We show that the regularized imaging spectroscopy approach is not only feasible for analysis of the visibilities observed by STIX, but also more reliable. Application of the regularized imaging spectroscopy technique to several well-observed flares reveals details of the variation of the electron flux spectrum throughout the flare sources. We conclude that the visibility-based regularized imaging spectroscopy approach is well-suited to analysis of STIX data. We also use STIX electron flux spectral images to track, for the first time, the behavior of the accelerated electrons during their path from the acceleration site in the solar corona toward the chromosphere

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arXiv2023

Unbiased CLEAN for STIX in Solar Orbiter

Aims: To formulate, implement, and validate a user-independent release of CLEAN for Fourier-based image reconstruction of hard X-rays flaring sources. Methods: CLEAN is an iterative deconvolution method for radio and hard X-ray solar imaging. In a specific step of its pipeline, CLEAN requires the convolution between an idealized version of the instrumental Point Spread Function (PSF), and a map collecting point sources located at positions on the solar disk from where most of the flaring radiation is emitted. This convolution step has highly heuristic motivations and the shape of the idealized PSF, which depends on the user's choice, impacts the shape of the overall reconstruction. Here we propose the use of an interpolation/extrapolation process to avoid this user-dependent step, and to realize a completely unbiased version of CLEAN. Results: Applications to observations recorded by the Spectrometer/Telescope for Imaging X-rays (STIX) on-board Solar Orbiter show that this unbiased release of CLEAN outperforms the standard version of the algorithm in terms of both automation and reconstruction reliability, with reconstructions whose accuracy is in line with the one offered by other imaging methods developed in the STIX framework. Conclusions: This unbiased version of CLEAN proposes a feasible solution to a well-known open issue concerning CLEAN, i.e., its low degree of automation. Further, this study provided the first application of an interpolation/extrapolation approach to image reconstruction from STIX experimental visibilities.

astro-ph.IM↗

arXiv2023

The data center for the Spectrometer and Telescope for Imaging X-rays (STIX) onboard Solar Orbiter

The Spectrometer and Telescope for Imaging X-rays (STIX) on board Solar Orbiter observes solar X-ray emission in the range of 4 – 150 keV and produces spectra and images of solar flares over a wide range of flare magnitudes. During nominal operation, STIX continuously generates data. A constant data flow requires fully automated data-processing pipelines to process and analyze the data, and a data platform to manage, visualize, and distribute the data products to the scientific community. The STIX Data Center has been built to fulfill these needs. In this paper, we outline its main components to help the community better understand the tools and data it provides. The STIX Data Center is operated at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW) and consists of automated processing pipelines and a data platform. The pipelines process STIX telemetry data, perform common analysis tasks, and generate data products at different processing levels. They have been designed to operate fully automatically with minimal human intervention. The data platform provides web-based user interfaces and application programmable interfaces for searching and downloading STIX data products. The STIX Data Center has been operating successfully for more than two years. The platform facilitates instrument operations and provides vital support to STIX data users.

astro-ph.SR↗

arXiv2023

Robust construction of differential emission measure profiles using a regularized maximum likelihood method

Extreme-ultraviolet (EUV) observations provide considerable insight into evolving physical conditions in the active solar atmosphere. For a prescribed density and temperature structure, it is straightforward to construct the corresponding differential emission measure profile $ξ(T)$, such that $ξ(T) \, dT$ is proportional to the emissivity from plasma in the temperature range $[T, T + dT]$. Here we study the inverse problem of obtaining a valid $ξ(T)$ profile from a set of EUV spectral line intensities observed at a pixel within a solar image. Our goal is to introduce and develop a regularized maximum likelihood (RML) algorithm designed to address the mathematically ill-posed problem of constructing differential emission measure profiles from a discrete set of EUV intensities in specified wavelength bands, specifically those observed by the Atmospheric Imaging Assembly (AIA) on the NASA Solar Dynamics Observatory. The RML method combines features of maximum likelihood and regularized approaches used by other authors. It is also guaranteed to produce a positive definite differential emission measure profile. We evaluate and compare the effectiveness of the method against other published algorithms, using both simulated data generated from parametric differential emission profile forms, and AIA data from a solar eruptive event on 2010 November 3. Similarities and differences between the differential emission measure profiles and maps reconstructed by the various algorithms are discussed. The RML inversion method is mathematically rigorous, computationally efficient, and produces acceptable measures of performance in the following three key areas: fidelity to the data, accuracy in the reconstruction, and robustness in the presence of data noise. As such, it shows considerable promise for computing differential emission measure profiles from datasets of discrete spectral lines.

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arXiv2023

STIX imaging I -- Concept

Aims. To provide a schematic mathematical description of the imaging concept of the Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter. The derived model is the fundamental starting point for both the interpretation of STIX data and the description of the data calibration process. Methods. We describe the STIX indirect imaging technique which is based on spatial modulation of the X-ray photon flux by means of tungsten grids. We show that each of 30 STIX imaging sub-collimators measures a complex Fourier component of the flaring X-ray source corresponding to a specific angular frequency. We also provide details about the count distribution model, which describes the relationship between the photon flux and the measured pixel counts. Results. We define the image reconstruction problem for STIX from both visibilities and photon counts. We provide an overview of the algorithms implemented for the solution of the imaging problem, and a comparison of the results obtained with these different methods in the case of the SOL2022-03-31T18 flaring event.

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arXiv2022

Solar flare hard X-rays from the anchor points of an eruptive filament

Context. We present an analysis of a GOES M1.8 flare with excellent observational coverage in UV, EUV, and X-ray, including observations from the instruments IRIS, SDO with AIA, Hinode/EIS, Hinode/XRT, and Solar Orbiter with the Spectrometer/Telescope for Imaging X-rays (STIX). Hard X-ray emission is often observed at the footpoints of flare loops and is occasionally observed in the corona. In this flare, four nonthermal hard X-ray sources are seen. Aim. Our aim is to understand why we can observe four individual nonthermal sources in this flare and how we can characterize the physical properties of these four sources. Methods. We used the multiwavelength approach to analyze the flare and characterize the four sources. To do this, we combined imaging at different wavelengths and spectroscopic fitting in the EUV and X-ray range. Results. The flare is eruptive with an associated coronal mass ejection, and it shows the classical flare picture of a heated flare loop seen in EUV and X-rays, and two nonthermal hard X-ray footpoints at the loop ends. In addition to the main flare sources, we observed two outer sources in the UV, EUV, and nonthermal X-ray range located away from the main flare loop to the east and west. The two outer sources are clearly correlated in time, and they are only seen during the first two minutes of the impulsive phase, which lasts a total of about four minutes. Conclusions. Based on the analysis, we determine that the outer sources are the anchor points of an erupting filament. The hard X-ray emission is interpreted as flare-accelerated electrons that are injected upward into the filament and then precipitate along the filament toward the chromosphere, producing Bremsstrahlung. While sources like this have been speculated to exist, this is the first report of their detection.

astro-ph.SR↗

arXiv2022

Forward-fitting STIX visibilities

Aima. To determine to what extent the problem of forward fitting visibilities measured by the Spectrometer/Telescope Imaging X-rays (STIX) on-board Solar Orbiter is more challenging with respect to the same problem in the case of previous hard X-ray solar imaging missions; to identify an effective optimization scheme for parametric imaging for STIX. Methods. This paper introduces a Particle Swarm Optimization (PSO) algorithm for forward fitting STIX visibilities and compares its effectiveness with respect to the standard simplex-based optimization algorithm used so far for the analysis of visibilities measured by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). This comparison is made by considering experimental visibilities measured by both RHESSI and STIX, and synthetic visibilities generated by accounting for the STIX signal formation model. Results. We found out that the parametric imaging approach based on PSO is as reliable as the one based on the simplex method in the case of RHESSI visibilities. However, PSO is significantly more robust when applied to STIX simulated and experimental visibilities. Conclusions. Standard deterministic optimization is not effective enough for forward-fitting the few visibilities sampled by STIX in the angular frequency plane. Therefore a more sofisticated optimization scheme must be introduced for parametric imaging in the case of the Solar Orbiter X-ray telescope. The forward-fitting routine based on PSO we introduced in this paper proved to be significantly robust and reliable, and could be considered as an effective candidate tool for parametric imaging in the STIX context.

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arXiv2022

First hard X-ray imaging results by Solar Orbiter STIX

Context. The Spectrometer/Telescope for Imaging X-rays (STIX) is one of 6 remote sensing instruments on-board Solar Orbiter. It provides hard X-ray imaging spectroscopy of solar flares by sampling the Fourier transform of the incoming flux. Aims. To show that the visibility amplitude and phase calibration of 24 out of 30 STIX sub-collimators is well advanced and that a set of imaging methods is able to provide the first hard X-ray images of the flaring Sun from Solar Orbiter. Methods. We applied four visibility-based image reconstruction methods and a count-based one to calibrated STIX observations. The resulting reconstructions are compared to those provided by an optimization algorithm used for fitting the amplitudes of STIX visibilities. Results. When applied to six flares with GOES class between C4 and M4 which occurred in May 2021, the five imaging methods produce results morphologically consistent with the ones provided by the Atmospheric Imaging Assembly on-board the Solar Dynamic Observatory (SDO/AIA) in UV wavelengths. The $χ^2$ values and the parameters of the reconstructed sources are comparable between methods, thus confirming their robustness. Conclusions. This paper shows that the current calibration of the main part of STIX sub-collimators has reached a satisfactory level for scientific data exploitation, and that the imaging algorithms already available in the STIX data analysis software provide reliable and robust reconstructions of the morphology of solar flares.

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