The project provided new knowledge on solar flares obtained using multi-wavelength data analysis and data-constrained three-dimensional (3D) modeling. 3D models of several solar flares have been created. New computer codes and simulation tools have been created. The project outcome is documented in more than 40 publications, including more than 25 journal articles in scientific journals, and more than 10 conference contributions, which have garnered more than 100 citations.

Intellectual merit. Significant efforts were dedicated to enhancing the 3D modeling tool, GX simulator. This includes a more accurate treatment of the FOV maps and CEA maps from which the magnetic data cubes are extrapolated. A new volume rendering method has been implemented, which allows rendering of the model data cube from any perspective even if the height scale is nonuniform. New efficient tools have been developed to automatically create nonlinear force-free field (NLFFF) extrapolations and 3D modeling cubes based on such extrapolations. The NLFFF tools have been carefully tested and validated using a full-fledged MHD model snapshot as a proxy of the solar atmosphere. The automated ‘3D model creation pipeline’ has been added to the GX Simulator and freely available via SSW repository.

Coronal magnetic data cubes created using NLFFF extrapolation technique have been used to create 3D models for a number of solar flares and study the processes of particle acceleration and transport, plasma heating, and energy partitions. This modeling facilitated addressing such fundamental questions of solar flares as disentangling the trapped and escaping distributions of electron accelerated in flares and overall morphology of the solar flare (e.g., how many distinct loops are needed to reproduce emission observed from a solar flare): in most cases we have found that from two to four loops were needed to fully reproduce the observed properties of the studied flares.

In particular, we investigated events with unusually narrow microwave spectra observed with OVSA. A subset of these flares was also observed with RHESSI. We performed a comprehensive statistical analysis of these flares. We found that the timing of nonthermal electrons in these events was driven by the acceleration process itself, rather than by magnetic trapping or escape. This implies that we detected emission coming from the acceleration region directly. We applied the microwave forward fit to derive evolution of the key physical parameters of the acceleration region, primarily, the magnetic field. From the analysis we found that the acceleration regions have a relatively strong magnetic field, high density, and low temperature. In contrast, the thermal X-ray emission comes from a distinct loop with a smaller magnetic field, lower density, but higher temperature. Therefore, these flares likely occurred due to interaction between two (or more) magnetic loops.

Broader impacts. The project team has been closely involved in activities dedicated to regular solar observations with ALMA starting October, 2016 (ALMA cycle IV). We submitted a number of proposals requesting ALMA observing time, three of them were selected (one with the priority A and with the priority B), which is a significant accomplishment given that the total of only 15 solar proposals were selected. We continue to take active part in the international network SSALMON (Solar Simulation for ALMA) as well as in solar ALMA commissioning effort and participated in two solar ALMA reference papers.

The 3D modeling tool is being used by a number of other research groups and individuals all over the world. During the project, the PI and co-PIs on the project supervised a few graduate students at NJIT and organized RHESSI 14 workshop at NJIT in August, 2015, where Working Groups 1-4 were directly relevant to this project. We are making use of the NSF assets such as VLA and NST. We actively disseminate the project outcome by giving invited review talks and by updating and distributing our modeling and analysis tools (e.g., GX Simulator, Wimagr) via SSW repository. In Spring-Summer 2016 and we supervised twelve high school students, who worked as summer interns at CSTR/NJIT and gained invaluable experience in data analysis and modeling.

Last Modified: 07/30/2018
Modified by: Gregory D Fleishman