Yes / The launch of the Solar Dynamics Observatory (SDO) in early 2010 has provided the solar physics community with the most detailed view of the Sun to date. However, this presents new challenges for the analysis of solar data. Currently, SDO sends over 1 terabyte of data per day back to Earth and methods for fast and reliable analysis are more important than ever. This article details four algorithms developed separately at the Universities of Bradford and Glasgow, the Royal Observatory of Belgium and Trinity College Dublin for the purposes of automated detection of solar active regions (ARs) and sunspots at different levels of the solar atmosphere.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第24421号 / 理博第4920号 / 新制||理||1703(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 一本 潔, 准教授 浅井 歩, 教授 横山 央明 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

The effects on image formation through a tilted interference filter in a converging beam are investigated and an adequate compensation procedure is established. A method that compensates for small-scale seeing distortions is also developed with the aim of co-aligning non-simultaneous solar images from different passbands. These techniques are applied to data acquired with a narrow tiltable filter at the Swedish 1-meter Solar Telescope. Tilting provides a way to scan the wing of the Ca II H line. The resulting images are used to map the temperature stratification and vertical temperature gradients in a solar active region containing a sunspot at a resolution approaching 0''10. The data are compared with hydro-dynamical quiet sun models and magneto-hydrodynamic models of plage. The comparison gives credence to the observational techniques, the analysis methods, and the simulations. Vertical temperature gradients are lower in magnetic structures than in non-magnetic. Line-of-sight velocities and magnetic field properties in the penumbra of the same sunspot are estimated using the CRISP imaging spectropolarimeter and straylight compensation adequate for the data. These reveal a pattern of upflows and downflows throughout the entire penumbra including the interior penumbra. A correlation with intensity positively identifies these flows as convective in origin. The vertical convective signatures are observed everywhere, but the horizontal Evershed flow is observed to be confined to areas of nearly horizontal magnetic field.  The relation between temperature gradient and total circular polarization in magnetically sensitive lines is investigated in different structures of the penumbra. Penumbral dark cores are prominent in total circular polarization and temperature gradient maps. These become longer and more contiguous with increasing height. Dark fibril structures over bright regions are observed in the Ca II H line core, above both the umbra and penumbra. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p>

Yes / Novel machine-learning and feature-selection algorithms have been developed to study: (i) the flare prediction capability of magnetic feature (MF) properties generated by the recently developed Solar Monitor Active Region Tracker (SMART); (ii) SMART's MF properties that are most significantly related to flare occurrence. Spatio-temporal association algorithms are developed to associate MFs with flares from April 1996 to December 2010 in order to differentiate flaring and non-flaring MFs and enable the application of machine learning and feature selection algorithms. A machine-learning algorithm is applied to the associated datasets to determine the flare prediction capability of all 21 SMART MF properties. The prediction performance is assessed using standard forecast verification measures and compared with the prediction measures of one of the industry's standard technologies for flare prediction that is also based on machine learning - Automated Solar Activity Prediction (ASAP). The comparison shows that the combination of SMART MFs with machine learning has the potential to achieve more accurate flare prediction than ASAP. Feature selection algorithms are then applied to determine the MF properties that are most related to flare occurrence. It is found that a reduced set of 6 MF properties can achieve a similar degree of prediction accuracy as the full set of 21 SMART MF properties.

Yes / In this paper, we introduce two novel models for processing real-life satellite images to quantify and then visualise their magnetic structures in 3D. We believe this multidisciplinary work is a real convergence between image processing, 3D visualization and solar physics. The first model aims to calculate the value of the magnetic complexity in active regions and the solar disk. A series of experiments are carried out using this model and a relationship has been indentified between the calculated magnetic complexity values and solar flare events. The second model aims to visualise the calculated magnetic complexities in 3D colour maps in order to identify the locations of eruptive regions on the Sun. Both models demonstrate promising results and they can be potentially used in the fields of solar imaging, space weather and solar flare prediction and forecasting.

Space weather has become an international issue due to the catastrophic impact it can have on modern societies. Solar flares are one of the major solar activities that drive space weather and yet their occurrence is not fully understood. Research is required to yield a better understanding of flare occurrence and enable the development of an accurate flare prediction system, which can warn industries most at risk to take preventative measures to mitigate or avoid the effects of space weather. This thesis introduces novel technologies developed by combining advances in statistical physics, image processing, machine learning, and feature selection algorithms, with advances in solar physics in order to extract valuable knowledge from historical solar data, related to active regions and flares. The aim of this thesis is to achieve the followings: i) The design of a new measurement, inspired by the physical Ising model, to estimate the magnetic complexity in active regions using solar images and an investigation of this measurement in relation to flare occurrence. The proposed name of the measurement is the Ising Magnetic Complexity (IMC). ii) Determination of the flare prediction capability of active region properties generated by the new active region detection system SMART (Solar Monitor Active Region Tracking) to enable the design of a new flare prediction system. iii) Determination of the active region properties that are most related to flare occurrence in order to enhance understanding of the underlying physics behind flare occurrence. The achieved results can be summarised as follows: i) The new active region measurement (IMC) appears to be related to flare occurrence and it has a potential use in predicting flare occurrence and location. ii) Combining machine learning with SMART¿s active region properties has the potential to provide more accurate flare predictions than the current flare prediction systems i.e. ASAP (Automated Solar Activity Prediction). iii) Reduced set of 6 active region properties seems to be the most significant properties related to flare occurrence and they can achieve similar degree of flare prediction accuracy as the full 21 SMART active region properties. The developed technologies and the findings achieved in this thesis will work as a corner stone to enhance the accuracy of flare prediction; develop efficient flare prediction systems; and enhance our understanding of flare occurrence. The algorithms, implementation, results, and future work are explained in this thesis.

Magnetic flux emergence is the subject of how magnetic fields from the solar interior can rise and expand into the atmosphere to produce active regions. It is the link that joins dynamics in the convection zone with dynamics in the atmosphere. In this thesis, we study many aspects of magnetic flux emergence through mathematical modelling and computer simulations. Our primary aim is to understand the key physical processes that lie behind emergence. The first chapter introduces flux emergence and the theoretical framework, magnetohydrodynamics (MHD), that describes it. In the second chapter, we discuss the numerical techniques used to solve the highly non-linear problems that arise from flux emergence. The third chapter summarizes the current literature. In the fourth chapter, we consider how changing the geometry and parameter values of the initial magnetic field can affect the dynamic evolution of the emerging magnetic field. For an initial toroidal magnetic field, it is found that its axis can emerge to the corona if the tube’s initial field strength is large enough. The fifth chapter describes how flux emergence models can produce large-scale solar eruptions. A 2.5D model of the breakout model, using only dynamic flux emergence, fails to produce any large scale eruptions. A 3D model of toroidal emergence with an overlying magnetic field does, however, produce multiple large-scale eruptions and the form of these is related to the breakout model. The sixth chapter is concerned with signatures of flux emergence and how to identify emerging twisted magnetic structures correctly. Here, a flux emergence model produces signatures found in observations. The signatures from the model, however, have different underlying physical mechanisms to the original interpretations of the observations. The thesis concludes with some final thoughts on current trends in theoretical magnetic flux emergence and possible future directions.

Space weather has become an international issue due to the catastrophic impact it can have on modern societies. Solar flares are one of the major solar activities that drive space weather and yet their occurrence is not fully understood. Research is required to yield a better understanding of flare occurrence and enable the development of an accurate flare prediction system, which can warn industries most at risk to take preventative measures to mitigate or avoid the effects of space weather. This thesis introduces novel technologies developed by combining advances in statistical physics, image processing, machine learning, and feature selection algorithms, with advances in solar physics in order to extract valuable knowledge from historical solar data, related to active regions and flares. The aim of this thesis is to achieve the followings: i) The design of a new measurement, inspired by the physical Ising model, to estimate the magnetic complexity in active regions using solar images and an investigation of this measurement in relation to flare occurrence. The proposed name of the measurement is the Ising Magnetic Complexity (IMC). ii) Determination of the flare prediction capability of active region properties generated by the new active region detection system SMART (Solar Monitor Active Region Tracking) to enable the design of a new flare prediction system. iii) Determination of the active region properties that are most related to flare occurrence in order to enhance understanding of the underlying physics behind flare occurrence. The achieved results can be summarised as follows: i) The new active region measurement (IMC) appears to be related to flare occurrence and it has a potential use in predicting flare occurrence and location. ii) Combining machine learning with SMART's active region properties has the potential to provide more accurate flare predictions than the current flare prediction systems i.e. ASAP (Automated Solar Activity Prediction). iii) Reduced set of 6 active region properties seems to be the most significant properties related to flare occurrence and they can achieve similar degree of flare prediction accuracy as the full 21 SMART active region properties. The developed technologies and the findings achieved in this thesis will work as a corner stone to enhance the accuracy of flare prediction; develop efficient flare prediction systems; and enhance our understanding of flare occurrence. The algorithms, implementation, results, and future work are explained in this thesis.

We present observational and numerical evidence supporting the theory of impulsive heating of the solar corona. We have run numerical simulations solving the hydrodynamic equations for plasma confined to a magnetic flux tube, for the two distinct cases of steady and impulsive heating. We find that steady heating cannot explain the observed amount of low-temperature plasma in active regions on the sun. The results for impulsive heating closely match those of the observations. The ratio of heating time to cooling time predominantly determines the observed temperature distribution of the plasma. We have also identified an observational bias in calculating intensities of spectral lines in previous studies, which causes an under-estimation of low-temperature plasma. We predict Doppler shifts in the observed line emission that are in agreement with observations, and which may serve as a diagnostic of the strength of heating. We conclude that impulsive heating of active region coronal loops is more likely than steady heating.

Made available in DSpace on 2016-03-15T19:35:54Z (GMT). No. of bitstreams: 1 MARIA VICTORIA GUTIERREZ ESCATE.pdf: 5448060 bytes, checksum: e181f68864eaef84743b2ff0d9d12abe (MD5) Previous issue date: 2015-06-18 / Fundação de Amparo a Pesquisa do Estado de São Paulo / Sympathetic solar flares are events occurring nearly simultaneously at distinct active regions with physical connection between them. Two flares that occurred on March 8, 2011 in active regions NOAA (National Oceanic and Atmospheric Administration) 11163 (N17W91) and AR 11165 (S20W91) is being studied. The larger flare occurred in the Southern region and was preceded by a smaller flare in the Northern region, about 5 minutes before. Both events were observed by RHESSI. The first explosion was detected by SST in the AR of north hemisphere, in two stages. There are also EUV SDO high cadence images that exhibit a distinct rapid flash coinciding with the SST burst as well as clear large scale magnetic connections between the two active regions. Three possible flare triggering agents from the Northern region towards the Southern region are being investigated: (a) hydrodynamic waves along the large coronal interconnecting magnetic structure, (b) surface Moreton-like shock waves, (c) plasma echoes. / Explosões solares simpatéticas são eventos que ocorrem quase simultaneamente, em regiões ativas distintas. Este trabalho apresenta o estudo de duas explosões solares que ocorreram no dia 8 de março de 2011, nas regiões ativas NOAA 11163 (N17W91) e 11165 (S20W91), entendidas como um evento simpatético característico. A maior explosão ocorreu na região sul, precedida por uma explosão menor na região norte, 5 minutos antes. Ambas detecções foram observadas em raios-X duros pelo satélite RHESSI. A primeira explosão também foi detectada pelo SST na RA do hemisfério norte. Imagens do SDO/AIA em EUV de alta cadência exibem um flash rápido e distinto, coincidente com a detecção do SST. As observações mostram que existem conexões magnéticas em grande escala entre as duas regiões ativas. Isso nos permitiu estudar três possíveis agentes de ativação entre as duas regiões ativas, sendo investigados, então, os seguinte mecanismos de ativação: (i) ondas hidrodinâmicas, ao longo da grande estrutura magnética coronal; (ii) ondas de choque do tipo Moreton, e, (iii) eco de plasma.