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The heart of the Large Magellanic Cloud, 30 Doradus, is a complex region with a clear core-halo structure. Feedback from the stellar cluster R$\,$136 has been shown to be the main source of energy creating multiple pc-scale expanding-shells in the outer region, and carving a nebula core in the proximity of the ionization source. We present the morphology and strength of the magnetic fields (B-fields) of 30 Doradus inferred from the far-infrared polarimetric observations by SOFIA/HAWC+ at 89, 154, and 214$\,\mu$m. The B-field morphology is complex, showing bending structures around R$\,$136. In addition, we use high spectral and angular resolution [\textsc{CII}] observations from SOFIA/GREAT and CO(2-1) from APEX. The kinematic structure of the region correlates with the B-field morphology and shows evidence of multiple expanding shells. Our B-field strength maps, estimated using the Davis-Chandrasekhar-Fermi method and structure-function, show variations across the cloud within a maximum of 600, 450, and 350$\,\mu$G at 89, 154, and 214$\,\mu$m, respectively. We estimated that the majority of the 30 Doradus clouds are sub-critical and sub-Alfv\'enic. The probability distribution function of the gas density shows that the turbulence is mainly compressively driven, while the plasma beta parameter indicates supersonic turbulence. We show that the B-field is sufficient to hold the cloud structure integrity under feedback from R$\,$136. We suggest that supersonic compressive turbulence enables the local gravitational collapse and triggers a new generation of stars to form. The velocity gradient technique (VGT) using [\textsc{CII}] and CO(2-1) is likely to confirm these results., Comment: 26 pages, 17 figures, 3 tables, accepted to ApJ

The EU funded the FLARECAST project, that ran from Jan 2015 until Feb 2018. FLARECAST had a R2O focus, and introduced several innovations into the discipline of solar flare forecasting. FLARECAST innovations were: first, the treatment of hundreds of physical properties viewed as promising flare predictors on equal footing, extending multiple previous works; second, the use of fourteen (14) different ML techniques, also on equal footing, to optimize the immense Big Data parameter space created by these many predictors; third, the establishment of a robust, three-pronged communication effort oriented toward policy makers, space-weather stakeholders and the wider public. FLARECAST pledged to make all its data, codes and infrastructure openly available worldwide. The combined use of 170+ properties (a total of 209 predictors are now available) in multiple ML algorithms, some of which were designed exclusively for the project, gave rise to changing sets of best-performing predictors for the forecasting of different flaring levels. At the same time, FLARECAST reaffirmed the importance of rigorous training and testing practices to avoid overly optimistic pre-operational prediction performance. In addition, the project has (a) tested new and revisited physically intuitive flare predictors and (b) provided meaningful clues toward the transition from flares to eruptive flares, namely, events associated with coronal mass ejections (CMEs). These leads, along with the FLARECAST data, algorithms and infrastructure, could help facilitate integrated space-weather forecasting efforts that take steps to avoid effort duplication. In spite of being one of the most intensive and systematic flare forecasting efforts to-date, FLARECAST has not managed to convincingly lift the barrier of stochasticity in solar flare occurrence and forecasting: solar flare prediction thus remains inherently probabilistic., Comment: 67 pages, 14 figures; submitted

Far-infrared (FIR) dust polarimetry enables the study of interstellar magnetic fields via tracing of the polarized emission from dust grains that are partially aligned with the direction of the field. The advent of high quality polarimetric data has permitted the use of statistical methods to extract both the direction and magnitude of the magnetic field. In this work, the Davis-Chandrasekhar-Fermi technique is used to make maps of the plane-of-sky (POS) component of the magnetic field in the Orion Molecular Cloud (OMC-1) by combining polarization maps at 53, 89, 154 and 214 \micron\ from HAWC+/SOFIA with maps of density and velocity dispersion. In addition, maps of the local dispersion of polarization angles are used in conjuction with Zeeman measurements to estimate a map of the strength of the line-of-sight (LOS) component of the field. Combining these maps, information about the three-dimensional magnetic field configuration (integrated along the line-of-sight) is inferred over the OMC-1 region. POS magnetic field strengths of up to 2 mG are observed near the BN/KL object, while the OMC-1 bar shows strengths of up to a few hundred $\mu$G. These estimates of the magnetic field components are used to produce maps of the mass-to-magnetic flux ratio ($M/\Phi$) -- a metric for probing the conditions for star formation in molecular clouds -- and determine regions of sub- and super-criticality in OMC-1. Such maps can provide invaluable input and comparison to MHD simulations of star formation processes in filamentary structures of molecular clouds., Comment: Accepted for publication in ApJ

One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are substantially better than climatological forecasts. Space weather researchers are increasingly looking towards methods used by the terrestrial weather community to improve current forecasting techniques. Ensemble forecasting has been used in numerical weather prediction for many years as a way to combine different predictions in order to obtain a more accurate result. Here we construct ensemble forecasts for major solar flares by linearly combining the full-disk probabilistic forecasts from a group of operational forecasting methods (ASAP, ASSA, MAG4, MOSWOC, NOAA, and MCSTAT). Forecasts from each method are weighted by a factor that accounts for the method's ability to predict previous events, and several performance metrics (both probabilistic and categorical) are considered. It is found that most ensembles achieve a better skill metric (between 5\% and 15\%) than any of the members alone. Moreover, over 90\% of ensembles perform better (as measured by forecast attributes) than a simple equal-weights average. Finally, ensemble uncertainties are highly dependent on the internal metric being optimized and they are estimated to be less than 20\% for probabilities greater than 0.2. This simple multi-model, linear ensemble technique can provide operational space weather centres with the basis for constructing a versatile ensemble forecasting system -- an improved starting point to their forecasts that can be tailored to different end-user needs., Comment: Accepted for publication in the Journal of Space Weather and Space Climate

We investigate the relation between characteristics of coronal mass ejections and parameterizations of the eruptive capability of solar active regions widely used in solar flare prediction schemes. These parameters, some of which are explored for the first time, are properties related to topological features, namely, magnetic polarity inversion lines (MPILs) that indicate large amounts of stored non-potential (i.e. free) magnetic energy. We utilize the Space Weather Database of Notifications, Knowledge, Information (DONKI) and the Large Angle and Spectrometric Coronograph (LASCO) databases to find flare-associated coronal mass ejections and their kinematic characteristics while properties of MPILs are extracted from Helioseismic and Magnetic Imager (HMI) vector magnetic-field observations of active regions to extract the properties of source-region MPILs. The correlation between all properties and the characteristics of CMEs ranges from moderate to very strong. More significant correlations hold particularly for fast CMEs, which are most important in terms of adverse space-weather manifestations. Non-neutralized currents and the length of the main MPIL exhibit significantly stronger correlations than the rest of the properties. This finding supports a causal relationship between coronal mass ejections and non-neutralized electric currents in highly sheared, conspicuous MPILs. In addition, non-neutralized currents and MPIL length carry distinct, independent information as to the eruptive potential of active regions. The combined total amount of non-neutralized electric currents and the length of the main polarity inversion line, therefore, reflect more efficiently than other parameters the eruptive capacity of solar active regions and the CME kinematic characteristics stemming from these regions., 31 pages, 14 figures

We report on polarimetric maps made with HAWC+/SOFIA toward Rho Oph A, the densest portion of the Rho Ophiuchi molecular complex. We employed HAWC+ bands C (89 $��$m) and D (154 $��$m). The slope of the polarization spectrum was investigated by defining the quantity R_DC = p_D/p_C, where p_C and p_D represent polarization degrees in bands C and D, respectively. We find a clear correlation between R_DC and the molecular hydrogen column density across the cloud. A positive slope (R_DC > 1) dominates the lower density and well illuminated portions of the cloud, that are heated by the high mass star Oph S1, whereas a transition to a negative slope (R_DC < 1) is observed toward the denser and less evenly illuminated cloud core. We interpret the trends as due to a combination of: (1) Warm grains at the cloud outskirts, which are efficiently aligned by the abundant exposure to radiation from Oph S1, as proposed in the radiative torques theory; and (2) Cold grains deep in the cloud core, which are poorly aligned due to shielding from external radiation. To assess this interpretation, we developed a very simple toy model using a spherically symmetric cloud core based on Herschel data, and verified that the predicted variation of R_DC is consistent with the observations. This result introduces a new method that can be used to probe the grain alignment efficiency in molecular clouds, based on the analysis of trends in the far-infrared polarization spectrum., Accepted by ApJ (July 18 2019)

Galactic outflows driven by starbursts can modify the galactic magnetic fields and drive them away from the galactic planes. Here, we quantify how these fields may magnetize the intergalactic medium. We estimate the strength and structure of the fields in the starburst galaxy M82 using thermal polarized emission observations from SOFIA/HAWC+ and a potential field extrapolation commonly used in solar physics. We modified the Davis-Chandrasekhar-Fermi method to account for the large-scale flow and the turbulent field. Results show that the observed magnetic fields arise from the combination of a large-scale ordered potential field associated with the outflow and a small-scale turbulent field associated with bow-shock-like features. Within the central $900$ pc radius, the large-scale field accounts for $53\pm4$% of the observed turbulent magnetic energy with a median field strength of $305\pm15$ $\mu$G, while small-scale turbulent magnetic fields account for the remaining $40\pm5$% with a median field strength of $222\pm19$ $\mu$G. We estimate that the turbulent kinetic and turbulent magnetic energies are in close equipartition up to $\sim2$ kpc (measured), while the turbulent kinetic energy dominates at $\sim7$ kpc (extrapolated). We conclude that the fields are frozen into the ionized outflowing medium and driven away kinetically. The magnetic field lines in the galactic wind of M82 are `open,' providing a direct channel between the starburst core and the intergalactic medium. Our novel approach offers the tools needed to quantify the effects of outflows on galactic magnetic fields as well as their influence on the intergalactic medium and evolution of energetic particles., Comment: 17 pages, 9 figures, Accepted for publication in ApJ

We report the first detection of galactic spiral structure by means of thermal emission from magnetically aligned dust grains. Our 89 $��$m polarimetric imaging of NGC 1068 with the High-resolution Airborne Wideband Camera/Polarimeter (HAWC+) on NASA's Stratospheric Observatory for Infrared Astronomy (SOFIA) also sheds light on magnetic field structure in the vicinity of the galaxy's inner-bar and active galactic nucleus (AGN). We find correlations between the 89 $��$m magnetic field vectors and other tracers of spiral arms, and a symmetric polarization pattern as a function of the azimuthal angle arising from the projection and inclination of the disk field component in the plane of the sky. The observations can be fit with a logarithmic spiral model with pitch angle of $16.9^{+2.7}_{-2.8}$$^{\circ}$ and a disk inclination of $48\pm2^{\circ}$. We infer that the bulk of the interstellar medium from which the polarized dust emission originates is threaded by a magnetic field that closely follows the spiral arms. Inside the central starburst disk ($, 13 pages, 7 figures, Accepted for publication by ApJ

High-resolution Airborne Wide-band Camera (HAWC[Formula: see text]) is the facility far-infrared imager and polarimeter for SOFIA, NASA’s Stratospheric Observatory for Infrared Astronomy. It is designed to cover the portion of the infrared spectrum that is completely inaccessible to ground-based observatories and which is essential for studies of astronomical sources with temperatures between tens and hundreds of degrees Kelvin. Its ability to make polarimetric measurements of aligned dust grains provides a unique new capability for studying interstellar magnetic fields. HAWC[Formula: see text] began commissioning flights in April 2016 and was accepted as a facility instrument in early 2018. In this paper, we describe the instrument, its operational procedures, and its performance on the observatory.

Solar active regions (ARs) that produce major flares typically exhibit strong plasma shear flows around photospheric magnetic polarity inversion lines (MPILs). It is therefore important to quantitatively measure such photospheric shear flows in ARs for a better understanding of their relation to flare occurrence. Photospheric flow fields were determined by applying the Differential Affine Velocity Estimator for Vector Magnetograms (DAVE4VM) method to a large data set of 2,548 co-aligned pairs of AR vector magnetograms with 12-min separation over the period 2012-2016. From each AR flow-field map, three shear-flow parameters were derived corresponding to the mean (), maximum (S_max) and integral (S_sum) shear-flow speeds along strong-gradient, strong-field MPIL segments. We calculated flaring rates within 24 hr as a function of each shear-flow parameter, and also investigated the relation between the parameters and the waiting time ({\tau}) until the next major flare (class M1.0 or above) after the parameter observation. In general, it is found that the larger S_sum an AR has, the more likely it is for the AR to produce flares within 24 hr. It is also found that among ARs which produce major flares, if one has a larger value of S_sum then {\tau} generally gets shorter. These results suggest that large ARs with widespread and/or strong shear flows along MPILs tend to not only be more flare productive, but also produce major flares within 24 hr or less., Comment: 19 pages, 8 figures, accepted for publication in Solar Physics

Efficient prediction of solar flares relies on parameters that quantify the eruptive capability of solar active regions. Several such quantitative predictors have been proposed in the literature, inferred mostly from photospheric magnetograms and/or white-light observations. Two of them are the Ising energy and the sum of the total horizontal magnetic field gradient. The former has been developed from line-of-sight magnetograms, while the latter uses sunspot detections and characteristics, based on continuum images. Aiming to include these parameters in an automated prediction scheme, we test their applicability on regular photospheric magnetic field observations provided by the Helioseismic and Magnetic Imager (HMI) instrument onboard the Solar Dynamics Observatory (SDO). We test their efficiency as predictors of flaring activity on a representative sample of active regions and investigate possible modifications of these quantities. The Ising energy appears to be an efficient predictor, and the efficiency is even improved if it is modified to describe interacting magnetic partitions or sunspot umbrae. The sum of the horizontal magnetic field gradient appears to be slightly more promising than the three variations of the Ising energy we implement in this article. The new predictors are also compared with two very promising predictors: the effective connected magnetic field strength and the total unsigned non-neutralized current. Our analysis shows that the efficiency of morphological predictors depends on projection effects in a nontrivial way. All four new predictors are found useful for inclusion in an automated flare forecasting facility, such as the Flare Likelihood and Region Eruption Forecasting (FLARECAST), but their utility, among others, will ultimately be determined by the validation effort underway in the framework of the FLARECAST project.

We present the results from the first ensemble prediction model for major solar flares (M and X classes). The primary aim of this investigation is to explore the construction of an ensemble for an initial prototyping of this new concept. Using the probabilistic forecasts from three models hosted at the Community Coordinated Modeling Center (NASA-GSFC) and the NOAA forecasts, we developed an ensemble forecast by linearly combining the flaring probabilities from all four methods. Performance-based combination weights were calculated using a Monte Carlo-type algorithm that applies a decision threshold Pth to the combined probabilities and maximizing the Heidke Skill Score (HSS). Using the data for 13 recent solar active regions between years 2012 and 2014, we found that linear combination methods can improve the overall probabilistic prediction and improve the categorical prediction for certain values of decision thresholds. Combination weights vary with the applied threshold and none of the tested individual forecasting models seem to provide more accurate predictions than the others for all values of Pth. According to the maximum values of HSS, a performance-based weights calculated by averaging over the sample, performed similarly to a equally weighted model. The values Pth for which the ensemble forecast performs the best are 25% for M-class flares and 15% for X-class flares. When the human-adjusted probabilities from NOAA are excluded from the ensemble, the ensemble performance in terms of the Heidke score is reduced.

The effect of using two representations of the normal-to-surface magnetic field to calculate photospheric measures that are related to the active region (AR) potential for flaring is presented. Several AR properties were computed using line-of-sight ( $B_{\mathrm{los}}$ ) and spherical-radial ( $B_{r}$ ) magnetograms from the Space-weather HMI Active Region Patch (SHARP) products of the Solar Dynamics Observatory, characterizing the presence and features of magnetic polarity inversion lines, fractality, and magnetic connectivity of the AR photospheric field. The data analyzed correspond to ${\approx\,}4{,}000$ AR observations, achieved by randomly selecting 25% of days between September 2012 and May 2016 for analysis at 6-hr cadence. Results from this statistical study include: i) the $B_{r}$ component results in a slight upwards shift of property values in a manner consistent with a field-strength underestimation by the $B_{\mathrm{los}}$ component; ii) using the $B_{r}$ component results in significantly lower inter-property correlation in one-third of the cases, implying more independent information as regards the state of the AR photospheric magnetic field; iii) flaring rates for each property vary between the field components in a manner consistent with the differences in property-value ranges resulting from the components; iv) flaring rates generally increase for higher values of properties, except the Fourier spectral power index that has flare rates peaking around a value of $5/3$ . These findings indicate that there may be advantages in using $B_{r}$ rather than $B_{\mathrm{los}}$ in calculating flare-related AR magnetic properties, especially for regions located far from central meridian.

We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Space-weather HMI Active Region Patches (SHARP) product that facilitates cut-out magnetograms of solar active regions (AR) in the Sun in near-real-time (NRT), taken over a five-year interval (2012 - 2016). Our approach utilizes a set of thirteen predictors, which are not included in the SHARP metadata, extracted from line-of-sight and vector photospheric magnetograms. We exploit several Machine Learning (ML) and Conventional Statistics techniques to predict flares of peak magnitude >M1 and >C1, within a 24 h forecast window. The ML methods used are multi-layer perceptrons (MLP), support vector machines (SVM) and random forests (RF). We conclude that random forests could be the prediction technique of choice for our sample, with the second best method being multi-layer perceptrons, subject to an entropy objective function. A Monte Carlo simulation showed that the best performing method gives accuracy ACC=0.93(0.00), true skill statistic TSS=0.74(0.02) and Heidke skill score HSS=0.49(0.01) for >M1 flare prediction with probability threshold 15% and ACC=0.84(0.00), TSS=0.60(0.01) and HSS=0.59(0.01) for >C1 flare prediction with probability threshold 35%., Accepted for publication by Solar Physics

We report new polarimetric and photometric maps of the massive star-forming region OMC-1 using the HAWC+ instrument on the Stratospheric Observatory for Infrared Astronomy (SOFIA). We present continuum polarimetric and photometric measurements of this region at 53, 89, 154, and 214 microns at angular resolutions of 5.1, 7.9, 14.0, and 18.7 arcseconds for the four bands, respectively. The photometric maps enable the computation of improved SEDs for the region. We find that at the longer wavelengths, the inferred magnetic field configuration matches the `hourglass' configuration seen in previous studies, indicating magnetically-regulated star formation. The field morphology differs at the shorter wavelengths. The magnetic field inferred at these wavelengths traces the bipolar structure of the explosive Becklin-Neugebauer (BN)/Kleinman-Low (KL) outflow emerging from OMC-1 behind the Orion Nebula. Using statistical methods to estimate the field strength in the region, we find that the explosion dominates the magnetic field near the center of the feature. Farther out, the magnetic field is close to energetic equilibrium with the ejecta and may be providing confinement to the explosion. The correlation between polarization fraction and the local polarization angle dispersion indicates that the depolarization as a function of unpolarized intensity is a result of intrinsic field geometry as opposed to decreases in grain alignment efficiency in denser regions., Comment: 28 pages, 14 figures, ApJ, accepted

We use linear analysis to simulate the evolution of a coronal loop in response to a localized impulsive event. The disturbance is modeled by injecting a narrow Gaussian velocity pulse near one footpoint of a loop in equilibrium. Three different damping mechanisms, namely viscosity, thermal conduction, and optically thin radiation, are included in the loop calculations. We consider homogeneous and gravitationally stratified, isothermal loops of varying length (50≤L≤400 Mm) and temperature (2≤T≤10 MK). We find that a localized pulse can effectively excite slow magnetoacoustic waves that propagate up along the loop. The amplitudes of the oscillations increase with decreasing loop temperature and increasing loop length and size of the pulse width. At T≥4 MK, the waves are dissipated by the combined effects of viscosity and thermal conduction, whereas at temperatures of 2 MK, or lower, wave dissipation is governed by radiative cooling. We predict periods in the range of 4.6 – 41.6 minutes. The wave periods remain unaltered by variations of the pulse size, decrease with the loop temperature, and increase almost linearly with the loop length. In addition, gravitational stratification results in a small reduction of the periods and amplification of the waves as they propagate up along the loop.

We study the linear evolution of a Gaussian pulse injected at different locations along a one-dimensional (1D), hot (T ≥ 6.3 MK) coronal loop, including the dissipative effects of thermal conduction, viscosity, heating, and radiative cooling. We consider both homogeneous and stratified loops of different lengths (50 ≤ L ≤ 400 Mm) and values of the pulse width (or standard deviation, βg/L) between 0.005 and 0.02. We find that a Gaussian velocity pulse can generate propagating waves whose amplitudes increase with increasing width of the pulse. The shape of the waves is quite irregular owing to the superposition of the several harmonics composing the Gaussian pulse. Wave damping due to the combined effects of thermal conduction and viscosity is faster in the shortest and hottest loops. The decay times and periods of the waves are within the observed values of decaying modes of hot SUMER loop oscillations.

Recent observations indicate that coronal plumes are the preferred channels for the propagation of slow magnetosonic waves from the Sun’s poles to the corona. This problem is of relevance in solar physics because polar plumes are well observed exactly at the heights of the solar wind acceleration. In this chapter, we study the effects of the basal geometric spreading of polar plumes on the propagation of slow-mode waves up to \(r=5R_{\odot }\) by means of a non-linear analysis of the equations of hydrodynamics. We find that super-radial expansion at the base of the flux tube induces a strong dilution of the wave energy flux close to the solar surface, implying a steep decrease of the wave amplitude from the very beginning. Slow waves with periods of 7–25 min diffuse out at heights between \({\approx } {1.6}\) and \(2.4R_{\odot }\) owing to dissipation. This result is in good agreement with recent observations.

We explore the association of non-neutralized currents with solar flare occurrence in a sizable sample of observations, aiming to show the potential of such currents in solar flare prediction. We used the high-quality vector magnetograms that are regularly produced by the Helioseismic Magnetic Imager, and more specifically, the Space weather HMI Active Region Patches (SHARP). Through a newly established method that incorporates detailed error analysis, we calculated the non-neutralized currents contained in active regions (AR). Two predictors were produced, namely the total and the maximum unsigned non-neutralized current. Both were tested in AR time-series and a representative sample of point-in-time observations during the interval 2012 – 2016. The average values of non-neutralized currents in flaring active regions are higher by more than an order of magnitude than in non-flaring regions and correlate very well with the corresponding flare index. The temporal evolution of these parameters appears to be connected to physical processes, such as flux emergence and/or magnetic polarity inversion line formation, that are associated with increased solar flare activity. Using Bayesian inference of flaring probabilities, we show that the total unsigned non-neutralized current significantly outperforms the total unsigned magnetic flux and other well-established current-related predictors. It therefore shows good prospects for inclusion in an operational flare-forecasting service. We plan to use the new predictor in the framework of the FLARECAST project along with other highly performing predictors.