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Register a new userDifferential Emission Measures from the Regularized Inversion of Hinode and SDO data
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We develop and apply an enhanced regularization algorithm, used in RHESSI X-ray spectral analysis, to constrain the ill-posed inverse problem that is determining the DEM from solar observations. We demonstrate this computationally fast technique applied to a range of DEM models simulating broadband imaging data from SDO/AIA and high resolution line spectra from Hinode/EIS, as well as actual active region observations with Hinode/EIS and XRT. As this regularization method naturally provides both vertical and horizontal (temperature resolution) error bars we are able to test the role of uncertainties in the data and response functions. The regularization method is able to successfully recover the DEM from simulated data of a variety of model DEMs (single Gaussian, multiple Gaussians and CHIANTI DEM models). It is able to do this, at best, to over four orders of magnitude in DEM space but typically over two orders of magnitude from peak emission. The combination of horizontal and vertical error bars and the regularized solution matrix allows us to easily determine the accuracy and robustness of the regularized DEM. We find that the typical range for the horizontal errors is $Delta$log$Tapprox 0.1 -0.5$ and this is dependent on the observed signal to noise, uncertainty in the response functions as well as the source model and temperature. With Hinode/EIS an uncertainty of 20% greatly broadens the regularized DEMs for both Gaussian and CHIANTI models although information about the underlying DEMs is still recoverable. When applied to real active region observations with Hinode/EIS and XRT the regularization method is able to recover a DEM similar to that found via a MCMC method but in considerably less computational time.
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To solve a number of problems in solar physics related to mechanisms of energy release in solar corona parameters of hot coronal plasma are required, such as energy distribution, emission measure, differential emission measure, and their evolution with time. Of special interest is the distribution of solar plasma by energies, which can evolve from a nearly Maxwellian distribution to a distribution with a more complex structure during a solar flare. The exact form of this distribution for low-energy particles, which receive the bulk of flare energy, is still poorly known; therefore, detailed investigations are required. We present a developed method of simultaneous fitting of data from two spacecrafts Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) and Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), using a differential emission measure and a thin target model for the August 14, 2010 flare event.
To elucidate the flare trigger mechanism, we have analyzed several flare events which were observed by Hinode/Solar Optical Telescope (SOT), in our previous study. Because of the limitation of SOT field of view, however, only four events in the Hinode data sets have been utilizable. Therefore, increasing the number of events is required for evaluating the flare trigger models. We investigated the applicability of data obtained by the Solar Dynamics Observatory (SDO) to increase the data sample for a statistical analysis of the flare trigger process. SDO regularly observes the full disk of the sun and all flares although its spatial resolution is lower than that of Hinode. We investigated the M6.6 flare which occurred on 13 February 2011 and compared the analyzed data of SDO with the results of our previous study using Hinode/SOT data. Filter and vector magnetograms obtained by the Helioseismic and Magnetic Imager (HMI) and filtergrams from the Atmospheric Imaging Assembly (AIA) 1600A were employed. From the comparison of small-scale magnetic configurations and chromospheric emission prior to the flare onset, we confirmed that the trigger region is detectable with the SDO data. We also measured the magnetic shear angles of the active region and the azimuth and strength of the flare-trigger field. The results were consistent with our previous study. We concluded that statistical studies of the flare trigger process are feasible with SDO as well as Hinode data. We also investigated the temporal evolution of the magnetic field before the flare onset with SDO.
We report on observations of recurrent jets by instruments onboard the Interface Region Imaging Spectrograph (IRIS), Solar Dynamics Observatory (SDO) and Hinode spacecrafts. Over a 4-hour period on July 21st 2013, recurrent coronal jets were observed to emanate from NOAA Active Region 11793. FUV spectra probing plasma at transition region temperatures show evidence of oppositely directed flows with components reaching Doppler velocities of +/- 100 km/s. Raster Doppler maps using a Si IV transition region line show all four jets to have helical motion of the same sense. Simultaneous observations of the region by SDO and Hinode show that the jets emanate from a source region comprising a pore embedded in the interior of a supergranule. The parasitic pore has opposite polarity flux compared to the surrounding network field. This leads to a spine-fan magnetic topology in the coronal field that is amenable to jet formation. Time-dependent data-driven simulations are used to investigate the underlying drivers for the jets. These numerical experiments show that the emergence of current-carrying magnetic field in the vicinity of the pore supplies the magnetic twist needed for recurrent helical jet formation.
Deriving a well-constrained differential emission measure (DEM) distribution for solar flares has historically been difficult, primarily because no single instrument is sensitive to the full range of coronal temperatures observed in flares, from $lesssim$2 to $gtrsim$50 MK. We present a new technique, combining extreme ultraviolet (EUV) spectra from the EUV Variability Experiment (EVE) onboard the Solar Dynamics Observatory with X-ray spectra from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), to derive, for the first time, a self-consistent, well-constrained DEM for jointly-observed solar flares. EVE is sensitive to ~2-25 MK thermal plasma emission, and RHESSI to $gtrsim$10 MK; together, the two instruments cover the full range of flare coronal plasma temperatures. We have validated the new technique on artificial test data, and apply it to two X-class flares from solar cycle 24 to determine the flare DEM and its temporal evolution; the constraints on the thermal emission derived from the EVE data also constrain the low-energy cutoff of the non-thermal electrons, a crucial parameter for flare energetics. The DEM analysis can also be used to predict the soft X-ray flux in the poorly-observed ~0.4-5 nm range, with important applications for geospace science.
Both NASAs Solar Dynamics Observatory (SDO) and the JAXA/NASA Hinode mission include spectropolarimetric instruments designed to measure the photospheric magnetic field. SDOs Helioseismic and Magnetic Imager (HMI) emphasizes full-disk high-cadence and good spatial resolution data acquisition while Hinodes Solar Optical Telescope Spectro-Polarimeter (SOT-SP) focuses on high spatial resolution and spectral sampling at the cost of a limited field of view and slower temporal cadence. This work introduces a deep-learning system named SynthIA (Synthetic Inversion Approximation), that can enhance both missions by capturing the best of each instruments characteristics. We use SynthIA to produce a new magnetogram data product, SynodeP (Synthetic Hinode Pipeline), that mimics magnetograms from the higher spectral resolution Hinode/SOT-SP pipeline, but is derived from full-disk, high-cadence, and lower spectral-resolution SDO/HMI Stokes observations. Results on held-out data show that SynodeP has good agreement with the Hinode/SOT-SP pipeline
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