QUEST(QUiet-sun Event STatistics)

QUEST LOGO

The QUEST project aims to characterise quiet-sun events involving the small-scale magnetic field using statistical analysis of multi-wavelength and spatially and temporally diverse data sets. Our goal is to follow, for e.g., magnetic flux emergence, flux cancellation, and magnetic intensification events (for e.g., Fischer et al. 2009) in the photospheric quiet-sun and study its respective imprints on the higher atmospheric layers. By using a large database of calibrated observational data and building up statistics of the transient events we plan to expose different aspects of the quiet-sun magnetic field.

Work Packages

Definitions for event tracing. Click to enlarge

Work Package I- Compiling the level 2 data base

The data base for the QUEST project will be built by retrieving suitable combination of time series data from existing publicly available archives, such as Hinode-IRIS archive of satellite data. In addition, multi-instrument time series data from observations of the QUEST group recorded at ground-based facilities such as the GREGOR telescope will be used. This so-called level 2 database will contain the physical parameters inferred from the data, such as velocities, magnetic field vector and so on.

Work Package II- Codes for identification, dynamic mapping, and event tracking

The magnetic field elements undergoing the physical processes need to be spatially located, characterized, and tracked in time (for e.g., as in Kaithakkal et al. 2017). The necessary codes will not all have to be written from scratch, but some will be obtained by adapting available tools.

Work Package III- Synthesized Sun

We will use 3-D MHD simulations to synthesize spectral profiles, which will then be degraded to the resolution of the concerned telescope to generate realistic data sets. This is essential to understand details of underlying physical processes and the degraded data then will demonstrate the residual observable signature.This also provides the opportunity to test the modified codes developed in Work Package II.

Work Package IV-Event statistics and parameter correlation

Here, we aim to formulate statistics of events and statistics of correlation between physical parameters. We also plan to obtain limits for the physical parameters which can then go into theoretical models as constraints.

Team

Collaborators

Dr. Juan Manuel Borrero

Dr. Juan Manuel Borrero from the KIS (Germany) is the author of the Stokes Inversion program VFISV (Borrero et al. 2011) and has vast experience in spectropolarimetric data analysis. He will advise the group on Stokes Inversions as well as perform Stokes Inversions on selected data sets.

Dr. Ryoko Ishikawa

Dr. Ryoko Ishikawa from NAOJ (Japan) is part of the Hinode data science team hosting the Hinode data archive and advanced data products. She has used multi-instrument and spectropolarimetric Hinode data extensively in her research (Ishikawa et al. 2008, 2009, 2010a, 2010b, 2011 ) and will advise the group on Hinode data products for the assembly of the level 2 data base as well as test the codes collected and written in work package II together with the QUEST team on Hinode data.

Dr. Serena Criscuoli

Dr. Serena Criscuoli from the NSO (US) combines experience in studying high-resolution observations (see e.g., Criscuoli et al. 2012) with the analysis of synthetic data and models of quiet and magnetic features, such as magnetic flux tubes. In her study of the correlation of quiet-sun G- band bright points and magnetic field strength she used, for example, synthetic data to demonstrate the influence of the observations analysis method on the obtained results (Criscuoli et al. 2014).

Dr. Nikola Vitas

Dr. Nikola Vitas from the IAC (Spain) is an expert in 3-D solar simulations. He is a member of the "Partial Ionization: 2-Fluid Approach" group, a team lead by Dr. Elena Khomenko. Their 3-D MHD simulations span from below the photosphere to the corona.

Dr. Reza Rezaei

Dr. Reza Rezaei from the IAC (Spain) is one of the few experts in analyzing chromospheric and transition region lines (see e.g. Rezaei et al. 2015, Rezaei et al 2008) and has written a publicly available data analysis tool (MOSiC, Rezaei 2017) for data obtained with the NASA IRIS satellite. He will provide the group with analyzed data from co-observed data sets of the IRIS satellite and assist with the interpretation of chromospheric data.

References

Borrero, J. M., Tomczyk, S., Kubo, M., et al. 2010, Sol. Phys., 35

Criscuoli, S., Del Moro, D., Giannattasio, F., et al. 2012, A&A, 546, A26

Criscuoli, S. & Uitenbroek, H. 2014, A&A, 562, L1

Fischer, C. E., de Wijn, A. G., Centeno, R., Lites, B. W., & Keller, C. U. 2009, A&A, 504, 583

Ishikawa, R., Tsuneta, S., Ichimoto, K., et al. 2008, A&A, 481, 25

Ishikawa, R. & Tsuneta, S. 2009, A&A, 495, 607

Ishikawa, R., Tsuneta, S., & Jurcˇák J. 2010a, ApJ, 713, 1310

Ishikawa, R. & Tsuneta, S. 2010b, ApJ, 718, L171

Ishikawa, R. & Tsuneta, S. 2011, ApJ, 735, 74

Kaithakkal, A., Riethmüller, T., Solanki, S. K., et al. 2017, ApJS, 229, 13

Rezaei, R. 2017, ArXiv e-prints, arXiv:1701.04421

Rezaei, R. & Beck, C. 2015, A&A, 582, A104

Rezaei, R., Bruls, J. H. M. J., Schmidt, W., et al. 2008, A&A, 484, 503