first corrections

Physics_Thesis_Template/bib-refs.bib

@@ -1,3 +1,51 @@
+@article{tess_response_curve,
+author = {George R. Ricker and Joshua N. Winn and Roland Vanderspek and David W. Latham and G{\'a}sp{\'a}r  {\'A}. Bakos and Jacob L. Bean and Zachory K. Berta-Thompson and Timothy M. Brown and Lars Buchhave and Nathaniel R. Butler and R. Paul Butler and William J. Chaplin and David B. Charbonneau and J{\o}rgen Christensen-Dalsgaard and Mark Clampin and Drake Deming and John P. Doty and Nathan De Lee and Courtney Dressing and Edward W. Dunham and Michael Endl and Fran{\c{c}}ois Fressin and Jian Ge and Thomas Henning and Matthew J. Holman and Andrew W. Howard and Shigeru Ida and Jon M. Jenkins and Garrett Jernigan and John Asher Johnson and Lisa Kaltenegger and Nobuyuki Kawai and Hans Kjeldsen and Gregory Laughlin and Alan M. Levine and Douglas Lin and Jack J. Lissauer and Phillip MacQueen and Geoffrey Marcy and Peter R. McCullough and Timothy D. Morton and Norio Narita and Martin Paegert and Enric Palle and Francesco Pepe and Joshua Pepper and Andreas Quirrenbach and Stephen A. Rinehart and Dimitar Sasselov and Bun’ei Sato and Sara Seager and Alessandro Sozzetti and Keivan G. Stassun and Peter Sullivan and Andrew Szentgyorgyi and Guillermo Torres and Stephane Udry and Joel Villasenor},
+title = {{Transiting Exoplanet Survey Satellite}},
+volume = {1},
+journal = {Journal of Astronomical Telescopes, Instruments, and Systems},
+number = {1},
+publisher = {SPIE},
+pages = {014003},
+keywords = {exoplanet, extrasolar planet, photometry, satellite, transits, Stars, Planets, Space operations, Charge-coupled devices, Cameras, Exoplanets, CCD cameras, Satellites, James Webb Space Telescope, Observatories},
+year = {2014},
+doi = {10.1117/1.JATIS.1.1.014003},
+URL = {https://doi.org/10.1117/1.JATIS.1.1.014003}
+}
+
+@INPROCEEDINGS{kepler_sensitivity,
+       author = {{Rowe}, Jason F. and {Matthews}, Jaymie M. and {Seager}, Sara and {Sasselov}, Dimitar and {Kuschnig}, Rainer and {Guenther}, David B. and {Moffat}, Anthony F.~J. and {Rucinski}, Slavek M. and {Walker}, Gordon A.~H. and {Weiss}, Werner W.},
+        title = "{Towards the Albedo of an Exoplanet: MOST Satellite Observations of Bright Transiting Exoplanetary Systems}",
+     keywords = {Astrophysics},
+    booktitle = {Transiting Planets},
+         year = 2009,
+       editor = {{Pont}, Fr{\'e}d{\'e}ric and {Sasselov}, Dimitar and {Holman}, Matthew J.},
+       series = {IAU Symposium},
+       volume = {253},
+        month = feb,
+        pages = {121-127},
+          doi = {10.1017/S1743921308026318},
+archivePrefix = {arXiv},
+       eprint = {0807.1928},
+ primaryClass = {astro-ph},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2009IAUS..253..121R},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+
+@ARTICLE{Carrington_event,
+       author = {{Carrington}, R.~C.},
+        title = "{Description of a Singular Appearance seen in the Sun on September 1, 1859}",
+      journal = {\mnras},
+         year = 1859,
+        month = nov,
+       volume = {20},
+        pages = {13-15},
+          doi = {10.1093/mnras/20.1.13},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/1859MNRAS..20...13C},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+}
+
+
+
 @ARTICLE{flares_1,
        author = {{Shibata}, Kazunari and {Magara}, Tetsuya},
         title = "{Solar Flares: Magnetohydrodynamic Processes}",

Physics_Thesis_Template/content/acknowledgement.tex

@@ -8,7 +8,7 @@
 
 % Acknowledge infrastructure and people that supported you in your thesis. This can also cover family, friends, etc.
 
-I gratefully acknowledge my supervisors \thesisFirstSupervisor and \thesisSecondSupervisor for guiding me through the process.
+I gratefully acknowledge my supervisors \thesisFirstSupervisor~and \thesisSecondSupervisor~for guiding me through the process.
 
 I thank my family and friends for supporting me.
 
@@ -40,4 +40,4 @@ This paper includes data collected with the TESS mission, obtained from the MAST
 % acknowledge FUNDING that you have received as financial support  
 
 %acknowledge sources of funding like a travel grant or a Erasmus fellowship, e.g.:
-I gratefully acknowledge the Austrian Science Fund (FWF): P30949-N36 (PI: xxx) for supporting this project. 
+I gratefully acknowledge the Austrian Science Fund (FWF): I5711-N (PI: Martin Leitzinger) for supporting this project. 

Physics_Thesis_Template/content/chapter-data.tex

@@ -3,13 +3,14 @@
 \chapter{Data and Methods}
 \label{sec:data}
 
-In this chapter the selection criteria for the data is explained in section \ref{sec:data:data_selection}. Furthermore a detailed description of the algorithm is given in section \ref{sec:data:data_reduction}.
+In this chapter the selection criteria for the data are explained in section \ref{sec:data:data_selection}. Furthermore a detailed description of the algorithm is given in section \ref{sec:data:data_reduction}.
 
 \section{Data selection}
 \label{sec:data:data_selection}
 
-This study uses a broad selection of Kepler/K2 and TESS lightcurves, which were downloaded from MAST with the help of the astroquery (\cite{astroquery}) python package. For Kepler and its continuation mission K2 short-cadence data was used. Unlike long-cadence data with a cadence of 30 minutes, this allows the resolution of shorter events too, as the duration of flares can vary between a few seconds to a few hours (\cite{flare_duration1}, ).
-The initial dataset was taken from a list of well known flaring stars from \cite{kepler_411_study}, \cite{kepler_411_210_comparison}, \cite{doyle_2018}, \cite{doyle_2019}, \cite{au_mic_flaring_spi} and \cite{flare_occurance_periodicity}. Additionally the dataset of the M to F stars of \cite{althukair_starlist} which can be found at \href{https://github.com/akthukair/AFD}{https://github.com/akthukair/AFD} was parsed to the downloader GUI. Due to not all data being available as short cadence data from Kepler/K2, only a subset of this large sample was added.
+This study uses a broad selection of Kepler/K2 and TESS lightcurves (427 for Kepler, 27 for K2, 1579 for TESS), which were downloaded from MAST with the help of the astroquery (\cite{astroquery}) python package. For Kepler and its continuation mission K2 short-cadence data were used. Unlike long-cadence data with a cadence of 30 minutes, this allows the resolution of shorter events too, as the duration of flares can vary between a few tens of seconds to a few hours (\cite{flare_duration1}).
+The initial dataset was taken from a list of well known flaring stars from \cite{kepler_411_study}, \cite{kepler_411_210_comparison}, \cite{doyle_2018}, \cite{doyle_2019}, \cite{au_mic_flaring_spi} and \cite{flare_occurance_periodicity}. These stars were selected because previous studies showed that these stars show detectable flares. This allowed for a test of the algorithm described in the next section and compare it the previous results.
+Additionally the dataset of the M to F stars of \cite{althukair_starlist} which can be found at \href{https://github.com/akthukair/AFD}{https://github.com/akthukair/AFD} was parsed to the downloader GUI. Due to not all data being available as short cadence data from Kepler/K2, only a subset of this large sample was added. The full list of stars, for which datasets were downloaded and parsed can be found in appendix \ref{chap:list_of_stars} table \ref{apA:list_of_all_stars}.
 
 \section{Data reduction algorithms}
 \label{sec:data:data_reduction}
@@ -19,30 +20,37 @@ This chapter explains the methods used in this study, split into the algorithms
 \subsection{Flare detection}
 \label{sec:data:data_reduction:flare_detection}
 
-The first step is to normalize the lightcurve. This is done to apply the same thresholds to all files in later steps. An example of this is shown in figure \ref{fig:full_gui_normal_selection_normalize_options} in chapter \ref{sec:gui:data_display}. The normalization is done via the $normalize()$ function of the $LightCurve$ class of the lightkurve api. Afterwards the lightcurves are flattened by called $flatten()$ of the $LightCurve$ objects. The resulting object is then used as the base for the detection of flares. This removes all longterm trends like brightness changes due to spot modulation or similar, while retaining short term events like flares or transits. A similar approach was used by \cite{au_mic_flaring_spi}.\\
-The next step is then to call $calculateFlareFitsForLightcurve()$ with the flattened lightcurve as well as the normalized lightcurve as parameters. It returns two lists of dictionaries with the data for the flare peak as well as a fit which is described in the following paragraphs.
-It parses the flattened lightcurve with the scipy $find\_peaks$ function. This function returns local maxima, which can be further filtered by their minimum height as well as the minimum distance of datapoints they need to be apart. The minimum distance between points is set to 1 with no minimum required height. Afterwards the found peaks are sorted by height, and the highest 100 are returned. This was found to be a good amount as the most flares per fits file found in this study were around 70 for CD-56 1032A and B.\\
-Afterwards each individual peak is checked. For this purpose every datapoint of the normalized flattened lightcurve is subtracted by 1 to move the average from 1 to 0. Additionally the star and end point of the flare are estimated. This is done by checking the datapoints before and after the peak. If it finds that the flux delta is below 0.005 for three consecutive datapoints, it stops, and assumes that the last checked point is the start/end of the flare. In the case it finds an infinite or NaN value (which can happen if there are gaps in the lightcurve data), or it reaches 100 datapoints before/after it will stop. This was found to cover most flares detected and provides enough datapoints for the following steps.\\
-Afterwards multiple checks are done. The first checking if the 1 datapoint before the peak, and 1 after the peak are above a threshold of 0.003, or if 2 datapoint after the peak after above the same threshold (which is a similar approach to \cite{kepler_411_study}). Afterwards it is checked if the datapoint at two indices before the peak is larger than the datapoint right before the registered peak. While this eliminates the positive detection of 2 flares in they case of them appearing very shortly after another, it was by visual inspection found to eliminate more false positives. Shortly after another appearing flares are still allowed, if the criteria are met, and theres atleast one more datapoint between the peaks. Then a fit of the flare is generated. The first half of the fit, till the peak, is that of a gaussian function, with the second half being an exponential decay (similar approach to \cite{au_mic_flaring_spi} and \cite{doyle_2018}). Then the residual sum of squares (RSS) between the fit and the flux of the flare, as well as the total sum of squares (TSS) are calculated. Afterwards R-squared is calculated, and if it is below 0.8, the flare is rejected as the flare would not have the typical form. In the last step, the location of the flare in the normalized and flattened lightcurve are compared. This step has been introduced, as in some rare cases the flattening algorithm can produce a large spike (values of 10 or higher when normalized).
+The first step is to normalize the lightcurve. This is done to apply the same thresholds to all files in later steps. An example of this is shown in figure \ref{fig:full_gui_normal_selection_normalize_options} in chapter \ref{sec:gui:data_display}. The normalization is done via the $normalize()$ function of the $LightCurve$ class of the lightkurve api. Afterwards the lightcurves are flattened by the function $flatten()$ of the $LightCurve$ objects. The resulting object is then used as the base for the detection of flares. This removes all longterm trends like brightness changes due to spot modulation or similar, while retaining short term events like flares or transits. A similar approach was used by \cite{au_mic_flaring_spi}.\\
+The next step is then to call $calculateFlareFitsForLightcurve()$ with the flattened lightcurve as well as the normalized lightcurve as parameters. It returns two lists of python dictionaries with the data for the flare peak as well as a fit which is described in the following paragraphs.
+It parses the flattened lightcurve with the scipy $find\_peaks$ function. This function returns local maxima, which can be further filtered by their minimum height (optional) as well as the minimum distance of datapoints (optional). Afterwards the found peaks are sorted by height, and the highest 100 are returned. This was found to be a good amount as the most flares per fits file found in this study were around 70 for CD-56 1032A and B.\\
+Afterwards each individual peak is checked. The first step is to estimate a flare starting and end point. This is done by checking the datapoints before and after the peak. If it finds that the flux delta is below 0.005 for three consecutive datapoints, it stops, and assumes that the last checked point is the start/end of the flare. In the case it finds an infinite or NaN value (which can happen if there are gaps in the lightcurve data), or it reaches 100 datapoints before/after it will stop. This was found to cover most flares detected and provides a sufficient number of datapoints for the following steps.\\
+Afterwards multiple checks are done. It first checks if the datapoints right before and after the peak are above a threshold of 0.003 above the mean flattened flux, or if the two datapoints right after the peak are above that threshold (which is a similar approach to \cite{kepler_411_study}). Afterwards it is checked if the datapoint at two indices before the peak is larger than the datapoint right before the registered peak. This eliminates possible false positives which were found by manually inspecting previously found events, but could not be guaranteed to be two seperate events. In such cases it will only count one flare. Then a fit of the flare is generated. The first half of the fit, till the peak, is that of a gaussian function, with the second half being an exponential decay (similar approach to \cite{au_mic_flaring_spi} and \cite{doyle_2018}). Then the residual sum of squares (RSS) between the fit and the flux of the flare, as well as the total sum of squares (TSS) are calculated. Afterwards R-squared is calculated, and if it is below 0.8, the flare is rejected as the flare would not have the typical form. In the last step, the locations of the flare in the normalized and flattened lightcurve are compared. This step has been introduced, as in some rare cases the flattening algorithm can produce a large artificial spike (values of 10 or higher when normalized).
 
 \subsection{Lightcurve folding}
 \label{sec:data:data_reduction:lightcurve_folding}
 
-This section will mainly describe how the $getOptimizedFold()$ function works. It takes the normalized lightcurve as well as a fit type as parameters. The fit type can either be "sine" for a sine fit, "poly" for a polynomlial fit, or "linear" for a linear fit. The default value is "sine", but can be changed for each individual star in the GUI.
+This section mainly describe how the $getOptimizedFold()$ function works. This function was written to optimize the lightcurve folding, to improve accuracy for the folding and lightcurve fitting process. It takes the normalized lightcurve as well as the preferred fitting function type (see chapter \ref{sec:gui:data_display}) as parameters. The fit type can either be "sine" for a sine fit, "poly" for a polynomlial fit, or "linear" for a linear fit. The default value is "sine", but can be changed for each individual star in the GUI.
 The function at first generates two periodograms with the lightkurve function $to\_periodogram$. The first one uses the lombscargle algorithm, while the second one uses the boxleastsquares algorithm. Afterwards the 4 highest peaks of each are taken and converted into periods (unit in days).
-Then each period found by each algorithm is compared with the periods found by the other, and in the case of a match (absolute value of the difference between the values of the two algorithms is smaller than 5\% of the larger of the two periods) this is now used as the rotational period as well as spot modulation period. If it does not find a match, it uses the period corresponding to the highest peak in the lombscargle periodogram.
-Afterwards it gets the epoch time to the first minimum in the lightcurve using numpys $argrelextrema$ function. In the following loop, which is repeated up to 30 times, it will fold the lightcurve (using the lightkurve $fold$ function) with the period set to the spot modulation, and the epoch set to the first minima in the lightcurve. Then a fit is calculated using the prefered fit method (with a polynomial fit fallback for sine fit prefered and vice versa). If the resulting fit should have two maxima, and they are further away from the edges than 10\% of the used period, the algorithm checks if there is a signal for half the used period in any of the two periodograms. If this is the case, it will now use this as the period for spot modulation. A new fold for the rotational period is then generated. Afterwards it checks the location of the minimum of the spot modulation folded lightcurve. If the minimum is within 1\% of half the phase it will stop. If not, it will shifts the epoch by the difference of the minimum to 0, which is the center of the folded lightcurves phase, and repeat the folding process.\\
-The function then returns the rotational period, the spot modulation period, the periods found by both periodograms as well as the folded lightcurve, the corresponding phase and the fit and fit type ("sine", "poly" or "linear") as well as the epoch. If the spot modulation differs from the rotational period found, it will also return the folded lightcurve, phase, fit and fit type of the rotational period folded lightcurve. The last returned value is "isValid", which is set to false if the algorithm should not break out of the loop in less than 30 tries.
+Then each period found by each algorithm is compared with the periods found by the other, and in the case of a match (absolute value of the difference between the values of the two algorithms is smaller than 5\% of the larger of the two periods) this is now used as the rotational period as well as the spot modulation period. If it does not find a match, it uses the period corresponding to the highest peak in the lombscargle periodogram.
+Afterwards it calculates the epoch time to the first minimum in the lightcurve using numpys $argrelextrema$ function. In the following loop, which is repeated up to 30 times, the lightcurve is folded (using the lightkurve $fold$ function) with the spot modulation period, and the epoch set to the first minima in the lightcurve. Then a fit is performed using the prefered fitting method. If the fitting process fails for the preferred fitting type, and it was set to "site", it will fall back to "poly" (polynomial fit), and vice versa. If the resulting fit has two maxima, and they are further away from the edges than 10\% of the used period, the algorithm checks if there is a signal for half the used period in any of the two periodograms. If this is the case, it will use this as the period for spot modulation. It will save the current folded lightcurve as folded by rotational period, and generate a new folded lightcurve with the newly found spot modulation period. Afterwards it checks the location of the minimum of the spot modulation folded lightcurve. If the minimum is within 1\% of half the phase it will stop. If not, it will shift the epoch by the difference of the minimum to 0, which is the center of the folded lightcurves phase, and repeat the folding process.\\
+The function then returns the rotational period, the spot modulation period, the periods found by both periodograms as well as the folded lightcurve, the corresponding phase and the fit and fit type ("sine", "poly" or "linear") as well as the epoch. If the spot modulation differs from the rotational period found, it will also return the folded lightcurve, phase, fit and fit type of the rotational period folded lightcurve. The last returned value is "isValid", which is set to false if the algorithm does not find a fit with its minimum at half the phase for the spot modulation period folded lightcurve within 30 iterations.
 
 \section{Spectral type identification}
 \label{sec:data:sptype_identification}
 
-After the initial download and cross checking with SIMBAD, not all stars had a spectral type assigned. For these stars magnitudes in various different bands was known though. The stars which have their magnitudes known atleast in the B and V bands are found in table \ref{tab:unknown_sptypes_bv}, while the stars which had their magnitudes known only in the J, H and C bands are in table \ref{tab:unknown_sptypes_jhc}.
-Using $B-V$ (as well as further magnitude differences, if available) have been compared to the table at \cite{spectral_type_color_table} (\href{https://www.stsci.edu/~inr/intrins.html}{https://www.stsci.edu/~inr/intrins.html}). This allowed for a rough classification of the stars in table \ref{tab:unknown_sptypes_bv}. Additionally, and to classify the stars in table \ref{tab:unknown_sptypes_jhc}, the effective temperature was taken into account from the TESS Input Catalogue (\cite{revised_tess_input_catalogue}) from Vizier (\cite{vizier}). The classification table for spectral types based on effective temperature has been taken from \cite{harvard_spectral_types_teff} (\href{https://lweb.cfa.harvard.edu/~pberlind/atlas/htmls/note.html}{https://lweb.cfa.harvard.edu/~pberlind/atlas/htmls/note.html}).\\
-The final spectral type for the stars can be found in table \ref{tab:unknown_sptypes_final_output}. If the base spectral type calculated from the effective temperature and the magnitude differences in multiple different color bands is identical, it will use that spectral type as final. In the case of those differing, like for BD-08 995, which was found to be an early K type star (K0) by the intrinsic color method but is a G type star based on the effective temperature, the latter is prefered. For the four stars from table \ref{tab:unknown_sptypes_jhc} which did not provide magnitudes in the optical range, the spectral type based on the effective temperature is taken as final.
+After the initial download and cross checking with SIMBAD, not all stars had a spectral type assigned. For these stars magnitudes in different wavelength bands was available. The stars with known magnitudes known atleast in the B and V bands are given in table \ref{tab:unknown_sptypes_bv}, while the stars with only J, H and K bands are in table \ref{tab:unknown_sptypes_jhk}.
+
+Using $B-V$ (as well as further magnitude differences, if available) have been compared to the table at \cite{spectral_type_color_table} (\href{https://www.stsci.edu/~inr/intrins.html}{https://www.stsci.edu/~inr/intrins.html}). 
+
+This allowed a rough classification of the stars in table \ref{tab:unknown_sptypes_bv}. Additionally, also the effective temperature was taken into account from the TESS Input Catalogue (\cite{revised_tess_input_catalogue}) from Vizier (\cite{vizier}). The classification table for spectral types based on effective temperature has been taken from \cite{harvard_spectral_types_teff} (\href{https://lweb.cfa.harvard.edu/~pberlind/atlas/htmls/note.html}{https://lweb.cfa.harvard.edu/~pberlind/atlas/htmls/note.html}).\\
+The final spectral type for the stars can be found in table \ref{tab:unknown_sptypes_final_output}.
+
+If the color spectral type calculated from the effective temperature and the magnitude differences in multiple different color bands is identical, it will use that spectral type as final.
+
+In the case of those differing, like for BD-08 995, which was found to be an early K type star (K0) by the intrinsic color method but being a G type star based on the effective temperature, the latter is prefered. For the four stars from table \ref{tab:unknown_sptypes_jhk} which have no B or V measurements, the spectral type based on the effective temperature is taken as final.
 
 \begin{table}
-    \caption{List of stars with no spectral type entry on SIMBAD, but available magnitudes in the B and V bands. Main Identifier according to SIMBADs "MAIN\_ID" property, as well as TESS Input Catalogue and Kepler Input Catalogue numbers.}
+    \caption{List of stars with no spectral type entry in SIMBAD, but available magnitudes in the B and V bands. Main Identifier according to SIMBADs "MAIN\_ID" property, as well as TESS Input Catalogue and Kepler Input Catalogue numbers are given.}
     \label{tab:unknown_sptypes_bv}
     \begin{tabular}{lll}
     \hline
@@ -60,8 +68,8 @@ The final spectral type for the stars can be found in table \ref{tab:unknown_spt
 
 
 \begin{table}
-    \caption{List of stars with no spectral type entry on SIMBAD, but available magnitudes in the J, H and C bands. Main Identifier according to SIMBADs "MAIN\_ID" property, as well as TESS Input Catalogue and Kepler Input Catalogue numbers.}
-    \label{tab:unknown_sptypes_jhc}
+    \caption{List of stars with no spectral type entry on SIMBAD, but available magnitudes in the J, H and K bands. Main Identifier according to SIMBADs "MAIN\_ID" property (2MASS), as well as TESS Input Catalogue and Kepler Input Catalogue numbers are given.}
+    \label{tab:unknown_sptypes_jhk}
     \begin{tabular}{lll}
     \hline
     Main Identifier & TIC & KIC \\
@@ -76,11 +84,11 @@ The final spectral type for the stars can be found in table \ref{tab:unknown_spt
 
 \begin{landscape}
 \begin{table}
-    \caption{Final estimated spectral types. Main Identifier shows the MAIN\_ID property for the star on SIMBAD. The column SIMBAD B-V contains the value of B-V with the respective magnitudes taken from SIMBAD. The columns TIC T\textsubscript{eff}, MASS and Radius contain the effective temperature, mass and radius for the star taken from the TESS Input Catalogue from Vizier. The column Spectral Type (B-V) contains the estimated spectral type based on \cite{spectral_type_color_table}, while the column Spectral Type (T\textsubscript{eff}) contains the spectral type based on the effective temperature from \cite{harvard_spectral_types_teff}. The last column contains the spectral type which is estimated and used in this study.}
+    \caption{Final determined spectral types. Main Identifier taken from SIMBAD. The column B-V contains the value of B-V calculated from the respective magnitudes taken from SIMBAD. The columns T\textsubscript{eff}, MASS and Radius contain the effective temperature, mass and radius for the star taken from the TESS Input Catalogue from Vizier. The column Spectral Type (B-V) contains the determined spectral type based on \cite{spectral_type_color_table}, while the column Spectral Type (T\textsubscript{eff}) contains the spectral type based on the effective temperature from \cite{harvard_spectral_types_teff}. The last column contains the spectral type which is used in this study.}
     \label{tab:unknown_sptypes_final_output}
     \begin{tabular}{lccccccc}
     \hline
-    Main Identifier & SIMBAD B-V & TIC T\textsubscript{eff} & TIC Mass & TIC Radius & Spectral Type (B-V) & Spectral Type (T\textsubscript{eff}) & Final Spectral Type \\
+    Main Identifier & B-V & T\textsubscript{eff} & Mass & Radius & Spectral Type (B-V) & Spectral Type (T\textsubscript{eff}) & Final Spectral Type \\
      & & [$K$] & [$M_\odot$] & [$R_\odot$ ]& & & \\
     \hline\hline
     1RXS J064643.6-770027 & 1.320000 & 4082 & 0.640 & 0.654 & K7.0 & K & K \\

Physics_Thesis_Template/content/chapter-gui.tex

@@ -1,14 +1,14 @@
 \chapter{GUI}
 \label{sec:gui}
 
-In this chapter the usage of the developed GUI application is explained. It was developed to easily download new data, as well as try various algorithms for flare detection and the usage of various functions of the lightkurve python package (\cite{lightkurve}).
+In this chapter the usage of the developed GUI application is explained. It was developed to easily download new data, as well as to try various algorithms for flare detection and the usage of various functions of the $lightkurve$ python package (\cite{lightkurve}).
 
 \section{Data download}
 \label{sec:gui:data_download}
 
-During the first startup the GUI window (e.g. in figure \ref{fig:full_gui_normal_selection}) is nearly completely empty. An empty local database will be created with SQLite3 (\cite{sqlite}). To show lightcurves, first data needs to be downloaded. For that, the "Add" button has to be clicked. A new dialog window will show. It can be seen in figure \ref{fig:download_new_star_data_gui}. This GUI uses the astroquery (\cite{astroquery}) python package to fetch metadata and download fits files from MAST (Mikulski Archive for Space Telescopes).\\
-The first step is to enter the identifier of the star(s). In case of multiple, they have to be seperated by a semicolon. Then the missions from which the data should be fetched can be selected. The supported missions are TESS and Kepler/K2. For Kepler and K2 short and/or long cadence can be selected. The differeces are described in section \ref{sec:intro:space_missions}. After the selection has been made, the fetch button needs to be pressed. The program will then request metadata matching the star identifier(s) and selected missions from the MAST archive. The found mission data is then displayed in the preview field. It can then be downloaded by pressing the "Ok" button. The program the proceeds to download the according fits-files. The filename and TESS sector or Kepler/K2 target table ID is appended to the previously fetched metadata and handed back to the main GUI.\\
-There a request to Simbad is made to fetch additional metadata. First the alternative identifiers are fetched from Simbad, which also has a MAIN\_ID attribute. This is to make sure we only have one entry in the local database per star and no duplicates. Afterwards additional data is fetched from Simbad (\cite{simbad}) like spectral type, radial velocity and distance. After the data is gathered, the main identifier, the alternative identifiers, spectral type, rotational velocity and distance (and their respective units) as well as the file path, source (TESS, Kepler or K2), and sector/target table id are saved into a local database using SQLite3 (\cite{sqlite}).
+During the first startup the GUI window (e.g. in figure \ref{fig:full_gui_normal_selection}) is nearly completely empty. An empty local database will be created with SQLite3 (\cite{sqlite}). To show lightcurves, data need to be downloaded first. For that, the "Add" button has to be clicked. A new dialog window will show. This can be seen in figure \ref{fig:download_new_star_data_gui}. This GUI uses the astroquery (\cite{astroquery}) python package to fetch metadata and download fits files from Mikulski Archive for Space Telescopes (MAST).\\
+The first step is to enter the identifier of the star(s). In case of multiple, they have to be seperated by a semicolon. Then the missions from which the data should be fetched can be selected. The supported missions are TESS and Kepler/K2. For Kepler and K2 short and/or long cadence can be selected. The differences are described in section \ref{sec:intro:space_missions}. After the selection has been made, the fetch button needs to be pressed. The program will then request metadata matching the star identifier(s) and selected missions from the MAST archive. The found mission data is then displayed in the preview field. It can then be downloaded by pressing the "Ok" button. The program then proceeds to download the corresponding fits-files. The filename and TESS sector or Kepler/K2 target table ID is appended to the previously fetched metadata and handed back to the main GUI.\\
+There a request to Simbad is made to fetch additional metadata. First the alternative identifiers are fetched from Simbad, which also have a MAIN\_ID attribute. This is to make sure we only have one entry in the local database per star and no duplicates. Afterwards additional data is fetched from Simbad (\cite{simbad}) like spectral type, radial velocity and distance. After the data is gathered, the main identifier, the alternative identifiers, spectral type, rotational velocity and distance (and their respective units) as well as the file path, source (TESS, Kepler or K2), and sector/target table id are saved into a local database using SQLite3 (\cite{sqlite}).
 
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/download_star_data_gui.png}
@@ -19,59 +19,72 @@ There a request to Simbad is made to fetch additional metadata. First the altern
 \section{Data display and manipulation}
 \label{sec:gui:data_display}
 
-Afterwards the list of stars seen in figure \ref{fig:full_gui_normal_selection} will be refreshed. It shows the via Simbad determined main identifier alphabetically sorted.\\
-When one of the stars in the list is selected, the program will show the additional saved informations. This includes all known IDs (in the Alt. IDs list), the spectral type, its rotational velocity and its distance. Additionally a fit type for the folded lightcurves which are described in section \ref{sec:data:data_reduction}. The default for this is "sine". The list to the right of the information section shows the available fit files. The formating for the list entries is "TESS - <sequence>" and "Kepler/K2 - <target table id>". The combine button allows to show multiple fit files at once if multiple are selected. Select one or combining multiple fit files, enables the plot options.\\
-The main plot options allow the user to change the type of flux thats plotted. This is either "SAP\_FLUX" (simple aperture photometry) or "PDCSAP\_FLUX" (presearch data conditioning simple aperture photometry) (\cite{lightkurve}). The PDCSAP\_FLUX has parts of its data removed depending on the quality flags (e.g. indicating systematic errors like an attitude tweak or a cosmic ray (\cite{tess_science_data_products}, \cite{kepler_archive_manual})) as well as corrected long-term brightness changes (\cite{lightkurve}). An example of a PDCSAP\_FLUX is shown in figure \ref{fig:full_gui_normal_selection}.\\
+Afterwards the list of stars seen in figure \ref{fig:full_gui_normal_selection} will be refreshed. It shows the alphabetically sorted main identifier determined from SIMBAD.\\
+When one of the stars in the list is selected, the program will show the additionally saved information. This includes all known identifiers for the star (categorized as alternative identifiers in the Alt. IDs list), the spectral type, its rotational velocity and its distance (from SIMBAD). Additionally a preferred fitting type for the folded lightcurves (which are described in section \ref{sec:data:data_reduction}) can be selected. The default value for this is "sine". The list to the right of the information section shows the available "fits" files. The formating for the list entries is "TESS - <sequence>" and "Kepler/K2 - <target table id>". The combine button allows to show multiple fit files at once if multiple are selected. Select one or combining multiple "fits" files, enables the plot options.\\
+The main plot options allow the user to change the type of flux thats plotted. This is either "SAP\_FLUX" (simple aperture photometry) or "PDCSAP\_FLUX" (presearch data conditioning simple aperture photometry) (\cite{lightkurve}) with the latter being the default option. The PDCSAP\_FLUX has parts of its data removed depending on the quality flags (e.g. indicating systematic errors like an attitude tweak or a cosmic ray (\cite{tess_science_data_products}, \cite{kepler_archive_manual})) as well as corrected long-term brightness changes (\cite{lightkurve}). An example of a PDCSAP\_FLUX is shown in figure \ref{fig:full_gui_normal_selection}.\\
 The lightkurve python package also supports normalizing (to unscaled, percent, parts per thousands (ppt) or parts per million (ppm)) which can be seen in figure \ref{fig:full_gui_normal_selection_normalize_options}. Flattened lightcurves (see figure \ref{fig:full_gui_normal_selection_flattened} as an example for $BD-08\ 995$) is used to identify flares. The "remove outliers", "remove nans/infs" and "bin" features are exposed in the GUI, but are not actively used in this thesis.\\
-The checkboxes to flatten the lightcurve (figure \ref{fig:full_gui_normal_selection_flattened}), fold the lighhtcurve (figure \ref{fig:full_gui_normal_selection_folded}) and showing the periodogram (figures \ref{fig:full_gui_normal_selection_periodogram_lombscargle} and \ref{fig:full_gui_normal_selection_periodogram_boxleastsquares}) are exclusive of each other. Only one can be used at a time.
+The checkboxes to flatten the lightcurve, meaning removing all longterm trends like spot/rotational modulation but leaving short term events intact (figure \ref{fig:full_gui_normal_selection_flattened}), fold the lightcurve (figure \ref{fig:full_gui_normal_selection_folded}) and showing the periodogram (figures \ref{fig:full_gui_normal_selection_periodogram_lombscargle} and \ref{fig:full_gui_normal_selection_periodogram_boxleastsquares}) are exclusive of each other. Only one can be used at a time. The values for "Period" and "Epoch Time" are automatically calculated and used as default for the selected lightcurve. If "Optimize" in the "Fold" options is unchecked, the "Epoch Time" represents the first found minimum in the lightcurve, and the "Period" is set to the period of the highest peak found in the lombscargle periodogram. If "Optimize" is checked, it will use the found rotational period of the optimize fold algorithm described in \ref{sec:data:data_reduction:lightcurve_folding}. If "Show Spot Modulation" is ticked, it will use the found spot modulation period instead of the rotational period.
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection.png}
-  \caption{Main GUI window. This window was designed with the Qt5 designer shipped with PyQz5 (\cite{pyqt5}). It shows a list of all available stars with their main identifier (taken from SIMBAD (\cite{simbad})) sorted alphabetically. The "Star infos" box contains additional information on the star gathered from SIMBAD. There is a list of alternative IDs, the spectral type, the roational velocity, and the distance. It also shows the prefered fit type for folding lightcurves. On the right of the information box is a list of all available lightcurves, with an option to combine multiple to plot at once. To the right of the list of available lightcurves are multiple different plot options, which utilize the different capabilities of the lightkurve python package (\cite{lightkurve}). The values for "Period" and "Epoch Time" are automatically calculated and used as default for the selected lightcurve. In this image the TESS Sector 32 lightcurve of $BD-08\ 995$ is shown. The red crosses show the peaks of the found flares, while the red overall over the lightcurve indicates the duration of the flare.}
+  \caption{Main GUI window. This window was designed with the Qt5 designer shipped with PyQt5 (\cite{pyqt5}). It shows a list of all available stars with their main identifier (taken from SIMBAD) sorted alphabetically. The "Star infos" box contains additional information on the star gathered from SIMBAD. The "Sequences/Target Table ID" box shows the list of all available lightcurves for the selected star, with an option to combine multiple to plot at once. To the right of the list of available lightcurves are different plot options, which utilize the different capabilities of the lightkurve python package (\cite{lightkurve}). In this image the TESS Sector 32 lightcurve of $BD-08\ 995$ is shown. The red crosses show the peaks of the found flares, while the red overall over the lightcurve indicates the duration estimate of the flare.}
   \label{fig:full_gui_normal_selection}
 \end{figure}
+\end{landscape}
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection_show_quality.png}
   \caption{Main GUI window. Same as in figure \ref{fig:full_gui_normal_selection}, with the difference that the data quality flag is also shown.}
   \label{fig:full_gui_normal_selection_show_quality}
 \end{figure}
+\end{landscape}
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection_normalize_options.png}
   \caption{Main GUI window. Same as in figure \ref{fig:full_gui_normal_selection}, with the difference that the lightcurve was normalized. It also shows all possible normalize options the lightkurve python package (\cite{lightkurve}) supports.}
   \label{fig:full_gui_normal_selection_normalize_options}
 \end{figure}
+\end{landscape}
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection_flattened.png}
   \caption{Main GUI window. Showing the same lightcurve as figure \ref{fig:full_gui_normal_selection}, with the difference that it is now flattened. The green line shows a fit of the flare. This is described in chapter \ref{sec:data:data_reduction}.}
   \label{fig:full_gui_normal_selection_flattened}
 \end{figure}
+\end{landscape}
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection_folded.png}
-  \caption{Main GUI window. Showing the same lightcurve as figure \ref{fig:full_gui_normal_selection}, with the difference that it is now folded with an period of ~2.697 days. Additionally vertical lines are shown which indicate the region around the minima and maxima of the folded lightcurve respectively.}
+  \caption{Main GUI window. Showing the same lightcurve as figure \ref{fig:full_gui_normal_selection}, with the difference that it is now folded with an period of ~2.697 days.}
   \label{fig:full_gui_normal_selection_folded}
 \end{figure}
+\end{landscape}
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection_periodogram_lombscargle.png}
   \caption{Main GUI window. Showing the periodogram of the lightcurve in figure \ref{fig:full_gui_normal_selection} using the lombscargle algorithm. Furthermore it shows the four highest peaks (which are atleast 100 datapoints separated). The method is explained in chapter \ref{sec:data:data_reduction}.}
   \label{fig:full_gui_normal_selection_periodogram_lombscargle}
 \end{figure}
+\end{landscape}
 
+\begin{landscape}
 \begin{figure}[pt!]
   \includegraphics[width=\linewidth]{gui/full_gui_normal_selection_periodogram_boxleastsquares.png}
   \caption{Main GUI window. Showing the periodogram of the lightcurve in figure \ref{fig:full_gui_normal_selection} using the box least square algorithm. Similarly to figure \ref{fig:full_gui_normal_selection_periodogram_lombscargle} the four highest peaks are marked with a red "x".}
   \label{fig:full_gui_normal_selection_periodogram_boxleastsquares}
 \end{figure}
+\end{landscape}
 
 \FloatBarrier
-
 \section{Data processing \label{sec:gui:data_processing}}
 
-Pressing the button "New FC" will start the processing of all fits files in the current loaded database. It will sequentially go through all files and apply the flare detection algorithms to the lightcurve, as well as generate the periodogram and optimized folded lightcurves. This is done for the PDCSAP\_FLUX. Additionally plots for each individual lightcurve and processing step are generated. The included data includes:
+Pressing the button "New FC" will start the processing of all fits files in the current loaded database. It will sequentially go through all files and apply the flare detection algorithms described in section \ref{sec:data:data_reduction} to the lightcurves, as well as generate the periodogram and optimized folded lightcurves. This is done for the PDCSAP\_FLUX. Additionally plots for each individual lightcurve and processing step are generated. The included data includes:
 
 \begin{itemize}
   \item Flares (peak, timestamp, datapoint index in the lightcurve, TESS/Kepler data quality flags)
@@ -87,9 +100,9 @@ Pressing the button "New FC" will start the processing of all fits files in the
   \item Additional boundaries around minima and maxima
 \end{itemize}
 
-And in the case the period and spot modulation of the star differs, it will seperately safe the folded lightcurves and related data for the stars period as well.
+And in the case the period and spot modulation of the star differs, it will seperately save the folded lightcurves and related data for the stars period as well.
 
-After this process is done, a new window will open. It allows to show multiple different debugging statistics like flares per file, flares per star (total, or normalized to per 7 day period) or mean periods for each star. This window can be seen in figure \ref{fig:summary_statistics_window}.
+After this process is finished, a new window will open. It allows to show multiple different debugging statistics like flares per file, flares per star (total, or normalized to per 7 day period) or mean periods for each star. This window can be seen in figure \ref{fig:summary_statistics_window}.
 The data can then be saved by clicking "File" and then "Save As", which uses the pandas (\cite{pandas}) "to\_pickle" function. Similarly it can be loaded again using the "read\_pickle" function which is called either by "File" and then "Open" in the debugging statistics window, or by clicking "Open" in the main window next to "New FC".
 
 \begin{figure}[pt!]

Physics_Thesis_Template/content/chapter-introduction.tex

@@ -2,17 +2,21 @@
 %Example chapter on Asteroseismology
 \chapter{Introduction \label{sec:intro}}
 %\cleanchapterquote{Shoot for the moon. Even if you miss, you'll land among the stars.}{Les Brown} %optional, if you want to place something here.
-This chapter gives an introduction to the goals of this study. Afterwards there will be summaries on topics related to this study, giving explanations on the various spectral types of stars, flares and spots, as well as giving an introduction to the space missions whichs data was used. Last but not least a summary of the current knowledge related to this study is given.
-
-\section{Goals and current knowledge \label{sec:intro:goals}}
-
-The goal of this study is to relate flares/superflares to the appearance of spots on the surfaces of stars of various spectral types. Flares are well studied for the sun (\cite{solar_flares_1}, \cite{solar_flares_2}, \cite{solar_flares_3}) as well as its impact on earths magnetic field (\cite{solar_flare_mag_field}). While the first stellar flares were discovered in middle of the last century (\cite{early_stellar_flares1}, \cite{early_stellar_flares2}), the topic gained a lot of traction with the launch of the likes of Kepler and the Transiting Exoplanet Survey Satellite (TESS). They allowed the survey of thousands of stars. With this, studies of flares and superflares on a large number of stars have been conducted (e.g. \cite{flare_study_1}, \cite{flare_study_2}, \cite{connection_starspots_flares_ms_kepler}, \cite{flare_occurance_periodicity}), but the origin of superflares (flares with an energy above $10^{33}$ erg) is still not clear. So far no superflare has been observed on our sun, but there have been studies focusing on the possible origin on superflares and their likelyhood to happen on our sun (\cite{superflares_on_sun}). They found that superflares on our sun would be rare events (every \textasciitilde800 years for superflares with $10^{34}$ erg).\\
+This chapter gives an introduction to the goals of this study. Afterwards there will be summaries on topics related to this study, giving explanations on the various spectral types of stars, flares and spots, as well as giving an introduction to the space missions whichs data was used. Last but not least a summary of the current knowledge related to this study is given.\\
+The goal of this study is to relate flares/superflares to the appearance of spots on the surfaces of stars of various spectral types. Flares are well studied for the sun (\cite{solar_flares_1}, \cite{solar_flares_2}, \cite{solar_flares_3}) with the first recorded event being the Carrington event from September 1859 (\cite{Carrington_event}). The same goes for the impact of stellar activity on earths magnetic field (\cite{solar_flare_mag_field}). A detailed description of spots and flares is found in section \ref{sec:intro:flares_and_spots}.
+While the first stellar flares were discovered in middle of the last century (\cite{early_stellar_flares1}, \cite{early_stellar_flares2}), the topic gained a lot of traction with the launch of the likes of Kepler and the Transiting Exoplanet Survey Satellite (TESS). They allowed the survey of thousands of stars. With this, studies of flares and superflares on a large number of stars have been conducted (e.g. \cite{flare_study_1}, \cite{flare_study_2}, \cite{connection_starspots_flares_ms_kepler}, \cite{flare_occurance_periodicity}), but the origin of superflares (flares with an energy above $10^{33}$ erg) is still not clear. So far no superflare has been observed on our sun, but there have been studies focusing on the possible origin on superflares and their likelyhood to happen on our sun (\cite{superflares_on_sun}). They found that superflares on our sun would be rare events (every \textasciitilde800 years for superflares with $10^{34}$ erg).\\
 A few proposed causes could be star-planet interaction (SPI) (\cite{au_mic_flaring_spi}, \cite{SPI_1}, \cite{SPI_2}), or just being scaled up version of normal flares which we see from our sun coming from large spots (\cite{superflares_1}, \cite{superflares_2}).\\
+
+\section{State of the art \label{sec:intro:goals}}
+
 \cite{doyle_2018} studied 34 M dwarfs from the K2 mission, using short cadence observational data. They confirmed that the stars in their dataset with a rotational period of less than 10 days showed more flares, which was already shown previously (\cite{faster_rot_stars_more_flares1}, \cite{faster_rot_stars_more_flares2}). Furthermore they found no star with a preference for when flares occured during the rotational phase (\cite{doyle_2018}). A similar study using TESS 2 minute cadence data has been conducted by \cite{doyle_2019}. In this study they used data of 167 M dwarfs and found a total of 1834 flares. Similar to the study on K2 data, they found no preference for roational phase (\cite{doyle_2019}).\\
-Further analysis on periodic flare occurance was done by \cite{flare_occurance_periodicity}, who studied lightcurves of 284 M dwarfs. They found three targets (TIC 80427281, TIC 95328477, TIC 220432563) with a confirmed flare periodicity, which correlates to their rotational period or half of it.\\
-\cite{connection_starspots_flares_ms_kepler} investigated a sample of 119 stars from spectral types M to F. They found that flares which increase the stellar flux by 1\% to 5\% appear more often while larger starspots are visible, while flares which increase the flux by more that 5\% do not seem to have this dependency (\cite{connection_starspots_flares_ms_kepler}).\\
-There have also been studies on individual stars, for example \cite{kepler_411_study} focused on Kepler-411 by investigating the relation between superflares and star spots on that star. They found a positive correlation between the energy of flares and the area of star spots (\cite{kepler_411_study}) on Kepler-411. They then compared their results for Kepler-411, which produced multiple superflares, with Kepler-210, which did not produce superflares while having the same number of spots (\cite{kepler_411_210_comparison}). They found the spots on Kepler-210 to be larger, warmer and therefor being magnetically weaker/less complex compared to Kepler-411 and concluded that the area of starspots is not the only relevant parameter for superflare occurance (\cite{kepler_411_210_comparison}). Star-planet interaction is studied by \cite{au_mic_flaring_spi} for the star AU Mic. While they found a signal in their used TESS lightcurves correlating with the orbital period of AU Mic b, they require more observation time to get a $>3\sigma$ detection (\cite{au_mic_flaring_spi}).\\
-In coclusion, many flares and superflares have been found on stars, but the origin of the later is still not clear. There are a few ongoing possible origins like star-planet interaction (or interactions with other close companions) or them coming from larger, more complex starspots. 
+\cite{connection_starspots_flares_ms_kepler} investigated a sample of 119 stars from spectral types M to F. They used a subset of the Kepler long-cadence data. They found that flares which increase the stellar flux by 1\% to 5\% appear more often while larger starspots are visible, while flares which increase the flux by more that 5\% do not seem to have this dependency (\cite{connection_starspots_flares_ms_kepler}).\\
+Further analysis on periodic flare occurance was done by \cite{flare_occurance_periodicity}, who studied TESS lightcurves of 284 cool dwarfs. They found three targets (TIC 80427281, TIC 95328477, TIC 220432563) with a confirmed flare periodicity, which correlates to their rotational period or half of it.\\
+There have also been studies on individual stars, for example \cite{kepler_411_study} focused on Kepler-411, which is a K2V dwarf, by investigating the relation between superflares and star spots on that star. They found a positive correlation between the energy of flares and the area of star spots (\cite{kepler_411_study}) on Kepler-411. They then compared their results for Kepler-411, which produced multiple superflares, with Kepler-210 (a K dwarf with two planets), which did not produce superflares while having the same number of spots (\cite{kepler_411_210_comparison}). They found the spots on Kepler-210 to be larger, warmer and therefor being magnetically weaker/less complex compared to Kepler-411 and concluded that the area of starspots is not the only relevant parameter for superflare occurance (\cite{kepler_411_210_comparison}).\\
+Star-planet interaction was studied by \cite{au_mic_flaring_spi} for the star AU Mic. While they found a signal in their used TESS lightcurves correlating with the orbital period of AU Mic b, they state that a $>3\sigma$ detection requires more observations (\cite{au_mic_flaring_spi}).\\
+In conclusion, many flares and superflares have been found on stars, but the origin of the latter is still not clear. Although it is widely accepted that superflares may be scales up normal flares, still the issue of star-planet interaction is discussed. Furthermore, the above mentioned studies could not relate flare/superflare occurrence distinctively to the spottedness of stars. With a large data set comprised of Kepler, K2 and TESS data we aim for a more distinct relation flare/superflare occurrence and spottedness of stars.
+
+There are a few ongoing possible origins like star-planet interaction (or interactions with other close companions) or them coming from larger, more complex starspots. 
 
 \section{Spectral Types \label{sec:intro:spectral_types}}
 
@@ -83,15 +87,25 @@ This section gives a short overview on the space mission from which the data was
 
 \subsection{Kepler and K2}
 
-The Kepler space telesope was named after Johannes Kepler and was launched in 2009 (\cite{nasa_kepler_in_depth}) and its primary mission lasted till May 2013 (\cite{kepler_missions_and_data_mast}). Its main scientific goal was the discovery of exoplanets, especially Earth-sized ones, in the habitable zone around their host star (\cite{kepler_missions_caltech}, \cite{Kepler_first_results}). This was done by observing transits of planets around their host star (\cite{kepler_missions_caltech}, \cite{kepler_missions_and_data_mast}, \cite{Kepler_first_results}). \\
-It provides two different types of data: short cadence (1 minute exposure) and long cadence (30 minute exposure) data (\cite{Kepler_first_results}, \cite{kepler_missions_and_data_mast}). While short cadence data provides a higher temporal resolution, it was used for fewer targets (\cite{Kepler_first_results}). It had a fixed exposure time of 6.02 seconds for its photometer with a field of view of 115 $deg^{2}$ near the cygnus constellation (\cite{Kepler_first_results}, \cite{kepler_missions_and_data_mast}). The data was then for selected targets accumulated to either short or long cadence, and then downloaded (\cite{Kepler_first_results}). The space telescope could accomondate data of around 170,000 targets with long cadence and 512 targets with short cadence (\cite{Kepler_first_results}). The resolution of each of the 42 CCDs was 4 arcseconds per pixel (\cite{doyle_2019}, \cite{kepler_mission_stellar_and_instrument_noise}).\\
-The K2 mission is the continuation mission of Kepler after the second of four of its reaction wheels broke in 2013 (\cite{nasa_kepler_in_depth}, \cite{k2_missions_and_data_mast}). Due to this, a new mission was proposed, keeping the now limited capabilities in mind (\cite{nasa_kepler_in_depth}). The mission was active from February 2014 till September 2018 when its fuel ran out (\cite{k2_missions_and_data_mast}, \cite{kepler_end_nytimes}, \cite{kepler_end_nasa_press}). It discovered a total of over 2600 planets as of 2018 (\cite{kepler_end_nytimes}, \cite{kepler_end_nasa_press}).
+The Kepler space telesope was named after Johannes Kepler and was launched in 2009\footnote{\label{fn:nasa_kepler_in_depth}\href{https://science.nasa.gov/mission/kepler/in-depth/}{https://science.nasa.gov/mission/kepler/in-depth/}} and its primary mission lasted till May 2013\footnote{\label{fn:kepler_missions_and_data_mast}\href{https://archive.stsci.edu/missions-and-data/kepler}{https://archive.stsci.edu/missions-and-data/kepler}}. Its main scientific goal was the discovery of exoplanets, especially Earth-sized ones, in the habitable zone around their host star\footnote{\label{fn:kepler_missions_caltech}\href{https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html}{https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html}} (\cite{Kepler_first_results}). This was done by observing transits of planets around their host star\cref{fn:kepler_missions_caltech}\cref{fn:kepler_missions_and_data_mast} (\cite{Kepler_first_results}).\\
+It provides two different types of data: short cadence (1 minute exposure) and long cadence (30 minute exposure) data\cref{fn:kepler_missions_and_data_mast} (\cite{Kepler_first_results}). While short cadence data provides a higher temporal resolution, it was used for fewer targets (\cite{Kepler_first_results}). It had a fixed exposure time of 6.02 seconds for its photometer with a field of view of 115 $deg^{2}$ near the cygnus constellation\cref{fn:kepler_missions_and_data_mast} (\cite{Kepler_first_results}) and is most sensitive in the visual to near infrared as seen in figure \ref{fig:kepler_bands}. The data was then for selected targets accumulated to either short or long cadence, and then downloaded (\cite{Kepler_first_results}). The space telescope could accomondate data of around 170,000 targets with long cadence and 512 targets with short cadence (\cite{Kepler_first_results}). The resolution of each of the 42 CCDs was 4 arcseconds per pixel (\cite{doyle_2019}, \cite{kepler_mission_stellar_and_instrument_noise}).\\
+The K2 mission is the continuation mission of Kepler after the second of four of its reaction wheels broke in 2013\cref{fn:nasa_kepler_in_depth} (\cite{k2_missions_and_data_mast}). Due to this, a follow-up mission was proposed, keeping the now limited capabilities in mind\cref{fn:nasa_kepler_in_depth}. The mission was active from February 2014 till September 2018 when its fuel ran out\footnote{\label{fn:k2_missions_and_data_mast}\href{https://archive.stsci.edu/missions-and-data/k2}{https://archive.stsci.edu/missions-and-data/k2}}\footnote{\label{fn:kepler_end_nytimes}\href{https://web.archive.org/web/20181030211627/https://www.nytimes.com/2018/10/30/science/nasa-kepler-exoplanet.html}{https://web.archive.org/web/20181030211627/https://www.nytimes.com/2018/10/30/science/nasa-kepler-exoplanet.html}}\footnote{\label{fn:kepler_end_nasa_press}\href{https://www.jpl.nasa.gov/news/nasa-retires-kepler-space-telescope/}{https://www.jpl.nasa.gov/news/nasa-retires-kepler-space-telescope/}}. It discovered a total of over 2600 planets as of 2018\cref{fn:kepler_end_nytimes}\cref{fn:kepler_end_nasa_press}.
+
+\begin{figure}[pt!]
+    \centering
+    \includegraphics[width=.6\linewidth]{gfx/kepler/kepler_bandpass_jason1.jpg}
+    \caption{Imagine showing the Johnson B, V, R and I response curves and comparing it to the Kepler, MOST and CoRoT missions. Image from \cite{kepler_sensitivity}.}
+    \label{fig:kepler_bands}
+\end{figure}
 
 \subsection{TESS}
 
-The Transiting Exoplanet Survey Satellite (TESS) was launched in 2018, with its primary mission lasting two years (\cite{tess_nasa}). Since 2020 TESS is in its extended missions, the first being from 2020 to 2022 (\cite{tess_extended_mission_1}), the second from 2022 to 2024 (\cite{tess_extended_mission_2}). TESS has four identical cameras, with each providing a 24 times 24 degree field of view (\cite{tess_tess}, \cite{TESS2014}). TESS's CCDs have a pixel scale of 21 arcseconds (\cite{TESS2014}, \cite{doyle_2019}). The data is provided in 2 minute cadence for individual stars and 30 minute cadence for full frame images (\cite{tess_tess}).\\
-TESS observes its targets in so called sectors. Each sector is observed for 27 days (\cite{tess_tess}). 
-
-%\section{Current knowledge \label{sec:intro:current_knowledge}}
-
+The Transiting Exoplanet Survey Satellite (TESS) was launched in 2018, with its primary mission lasting two years\footnote{\href{https://exoplanets.nasa.gov/tess/}{https://exoplanets.nasa.gov/tess/}}. Since 2020 TESS is in its extended missions, the first being from 2020 to 2022\footnote{\label{fn:tess_extended_mission_1}\href{https://archive.stsci.edu/contents/newsletters/august-2020/tess-extended-mission}{https://archive.stsci.edu/contents/newsletters/august-2020/tess-extended-mission}}, the second from 2022 to 2024\cref{fn:tess_tess}. TESS has four identical cameras, with each providing a 24 times 24 degree field of view\footnote{\label{fn:tess_tess}\href{https://tess.mit.edu/science/}{https://tess.mit.edu/science/}} (\cite{TESS2014}). TESS's CCDs have a pixel scale of 21 arcseconds (\cite{TESS2014}, \cite{doyle_2019}) and is most sensitive in the red and infrared (see figure \ref{fig:tess_bands}). The data is provided in 2 minute cadence for individual stars and 30 minute cadence for full frame images (\cite{tess_tess}).\\
+TESS observes its targets in so called sectors. Each sector is observed for 27 days\cref{fn:tess_tess}.
 
+\begin{figure}[pt!]
+    \centering
+    \includegraphics[width=.6\linewidth]{gfx/tess/The-TESS-spectral-response-function-black-line-defined-as-the-product-of-the-long-pass.png}
+    \caption{Imagine showing the Johnson V, R\textsubscript{C}, I\textsubscript{C} and SDSS z response curves and comparing it to TESS. Image from \cite{kepler_sensitivity}.}
+    \label{fig:tess_bands}
+\end{figure}

Physics_Thesis_Template/content/chapter-results.tex

@@ -1,13 +1,13 @@
 \chapter{Results \label{sec:results}}
 
-This chapter includes the main results of this study. The data for the plots were generated using the "New FC" Button from the main GUI described in section \ref{sec:gui:data_processing}.
-The results contain plots for the different spectral types M, K, G, and F as well as combined results of every possible combination. Additionally for all these possible combinations, plots with data limits, e.g. only stars with a rotational period of less than 2 days or minimal/maximal normalized flare peak limits, were also generated. Additionally plots for stars with a more detailed spectral type like M0 or G5 were created. Furthermore there is a selection of individual star results. For every plot group a CSV file is generated, which contains information about every star and flare used to generate the plot.
+This chapter includes the main results of this study. The data for the plots in this section were generated using the "New FC" Button from the main GUI described in section \ref{sec:gui:data_processing}. As every star has a different rotational/spot modulation period, the value range for the phases of the folded lightcurves do not match. To compare different stars (or spot modulation periods for the same star) with each other, the phase was normalized to $0$ to $2 \pi$.\\
+The results contain plots for the different spectral types M, K, G, and F as well as combined results of every possible combination. Additionally for all these possible combinations, plots with data limits, e.g. only stars with a rotational period of less than 2 days or minimal/maximal normalized flare peak limits, were also generated. Moreover plots for stars with a more detailed spectral type like M0 or G5 were created. Furthermore there is a selection of individual star results. For every plot group a CSV file is generated, which contains information about every star and flare used to generate the plot.
 The results also only contain the data of folded lightcurves which could be fitted with a sine function and less than 30 iterations of the fold optimization. The data which uses polynomial fits or both sine and polynomial fits as well as all plots and the accompanying CSV files are available at \href{https://drive.google.com/drive/folders/1L_F21W3WwZicVZg9052B12B2hJNuJBwK?usp=drive_link}{google drive}.
 
 \section{M dwarfs \label{sec:results:m_dwarfs}}
 
 This section shows the results for 49 M dwarfs for which flares could be detected. The list of stars can be found in table \ref{apA:list_of_m_stars}.\\
-Figures \ref{fig:M-Flarecount-10_Bins} and \ref{fig:M-Flarecount-30_Bins} show histograms, with 10 and 30 bins respectively, of the amount of flares during the normalized phase.\\
+Figures \ref{fig:M-Flarecount-10_Bins} and \ref{fig:M-Flarecount-30_Bins} show flare count histograms, with 10 and 30 phase bins respectively, of the number of flares during the normalized phase.\\
 Looking at figure \ref{fig:M-Flarecount-10_Bins} there is an even distribution within error of flares across the normalized phase, with the excepion of the bin at phase $0.5 \pi$. The bin at phase $0.5 \pi$ shows a significant dip of roughly twice the error below the surrounding bins.\\
 Looking at the same data, just with 30 instead of 10 bins (figure \ref{fig:M-Flarecount-30_Bins}), the same dip is visible. In this figure the dip spans 3 bins. Additionally there are additional dips at around phase $0.7 \pi$, $1.3 \pi$ and $1.4 \pi$. Including the error, the major dip (which was already visible in figure \ref{fig:M-Flarecount-10_Bins}) is still below the average. Similar for the dips at phases $0.7 \pi$ and $1.3 \pi$. The dip at phase $1.4 \pi$ on the other hand overlaps with its error with the errorbars of the bins at phase \textasciitilde$1.7 \pi$ and and onward, which are good assumption for an average value. Due to the dips surrounding the center, it may look like there is an increased number of flares in the center. If we look at the errorbars, it is clear that only the bin at phase \textasciitilde$1.25 \pi$ is above the average.
 

Physics_Thesis_Template/content/titlepages.tex

@@ -16,8 +16,8 @@
 \end{titlepage}
 % ------------------------------------  --> page 2 left empty on purpose
 
-\input{content/titlepageKFU} % uncomment for KFU style
-%\input{content/titlepageTU} % uncomment for TU style
+%\input{content/titlepageKFU} % uncomment for KFU style
+\input{content/titlepageTU} % uncomment for TU style
 
 % ------------------------------------  --> lower title back for single page layout
 

Physics_Thesis_Template/main.bbl-SAVE-ERROR

@@ -1230,6 +1230,38 @@
       \endverb
       \keyw{methods: data analysis,methods: miscellaneous,virtual observatory tools}
     \endentry
+    \entry{sunspot_magfieldlines_image}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=2f1e4e1c8dc4df33cefc4d3101363ca1}{%
+           family={{Australian Space Weather Forecasting Centre}},
+           familyi={A\bibinitperiod}}}%
+      }
+      \strng{namehash}{2f1e4e1c8dc4df33cefc4d3101363ca1}
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+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{title}{The Magnetic Fields around Sunspots}
+      \field{urlday}{2}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://www.sws.bom.gov.au/Educational/2/2/8
+      \endverb
+      \verb{url}
+      \verb https://www.sws.bom.gov.au/Educational/2/2/8
+      \endverb
+    \endentry
     \entry{harvard_spectral_types_teff}{misc}{}{}
       \name{author}{1}{}{%
         {{hash=c8b19cebd0d04b728df521ed9522e046}{%
@@ -1940,6 +1972,72 @@
       \endverb
       \keyw{stars: activity,stars: flare,stars: low-mass,stars: magnetic field,Astrophysics - Solar and Stellar Astrophysics}
     \endentry
+    \entry{soho_esa}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=afafc7a086f96baed3f76650e4fcdc5d}{%
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+      \field{title}{SOHO}
+      \field{urlday}{2}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://www.esa.int/Science_Exploration/Space_Science/SOHO
+      \endverb
+      \verb{url}
+      \verb https://www.esa.int/Science_Exploration/Space_Science/SOHO
+      \endverb
+    \endentry
+    \entry{sun_photosphere_mag_field_strength}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=0169748fb52d0b3b4e3fcebeb75a7cb0}{%
+           family={Fox},
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+      \field{labeltitlesource}{title}
+      \field{title}{{The Dynamic Solar Magnetic Field with Introduction}}
+      \field{urlday}{2}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://svs.gsfc.nasa.gov/4623/
+      \endverb
+      \verb{url}
+      \verb https://svs.gsfc.nasa.gov/4623/
+      \endverb
+    \endentry
     \entry{conch_shell_m_dwarfs}{article}{}{}
       \name{author}{9}{}{%
         {{hash=a5b91fc80ed0608aeab6c2bacd2fcc3c}{%
@@ -2127,7 +2225,6 @@
       \field{labeldatesource}{}
       \field{labelnamesource}{author}
       \field{labeltitlesource}{title}
-      \field{abstract}{Kepler mission results are rapidly contributing to fundamentally new discoveries in both the exoplanet and asteroseismology fields. The data returned from Kepler are unique in terms of the number of stars observed, precision of photometry for time series observations, and the temporal extent of high duty cycle observations. As the first mission to provide extensive time series measurements on thousands of stars over months to years at a level hitherto possible only for the Sun, the results from Kepler will vastly increase our knowledge of stellar variability for quiet solar-type stars. Here, we report on the stellar noise inferred on the timescale of a few hours of most interest for detection of exoplanets via transits. By design the data from moderately bright Kepler stars are expected to have roughly comparable levels of noise intrinsic to the stars and arising from a combination of fundamental limitations such as Poisson statistics and any instrument noise. The noise levels attained by Kepler on-orbit exceed by some 50% the target levels for solar-type, quiet stars. We provide a decomposition of observed noise for an ensemble of 12th magnitude stars arising from fundamental terms (Poisson and readout noise), added noise due to the instrument and that intrinsic to the stars. The largest factor in the modestly higher than anticipated noise follows from intrinsic stellar noise. We show that using stellar parameters from galactic stellar synthesis models, and projections to stellar rotation, activity, and hence noise levels reproduce the primary intrinsic stellar noise features.}
       \field{journaltitle}{The Astrophysical Journal Supplement Series}
       \field{month}{10}
       \field{number}{1}
@@ -2879,60 +2976,6 @@
       \verb 10.1086/126150
       \endverb
     \endentry
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-      \field{sortinit}{K}
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-      \field{labeltitlesource}{title}
-      \field{title}{Kepler}
-      \field{urlday}{1}
-      \field{urlmonth}{6}
-      \field{urlyear}{2025}
-      \field{urldateera}{ce}
-      \verb{urlraw}
-      \verb https://archive.stsci.edu/missions-and-data/kepler
-      \endverb
-      \verb{url}
-      \verb https://archive.stsci.edu/missions-and-data/kepler
-      \endverb
-    \endentry
-    \entry{nasa_kepler_in_depth}{misc}{}{}
-      \field{sortinit}{K}
-      \field{sortinithash}{c02bf6bff1c488450c352b40f5d853ab}
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-      \field{title}{{Kepler - In Depth}}
-      \field{urlday}{1}
-      \field{urlmonth}{6}
-      \field{urlyear}{2025}
-      \field{urldateera}{ce}
-      \verb{urlraw}
-      \verb https://science.nasa.gov/mission/kepler/in-depth/
-      \endverb
-      \verb{url}
-      \verb https://science.nasa.gov/mission/kepler/in-depth/
-      \endverb
-    \endentry
-    \entry{kepler_missions_caltech}{misc}{}{}
-      \field{sortinit}{K}
-      \field{sortinithash}{c02bf6bff1c488450c352b40f5d853ab}
-      \field{extradatescope}{labelyear}
-      \field{labeldatesource}{url}
-      \field{labeltitlesource}{title}
-      \field{title}{Kepler Mission Information}
-      \field{urlday}{1}
-      \field{urlmonth}{6}
-      \field{urlyear}{2025}
-      \field{urldateera}{ce}
-      \verb{urlraw}
-      \verb https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html
-      \endverb
-      \verb{url}
-      \verb https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html
-      \endverb
-    \endentry
     \entry{V471tau_magnetic_activity}{article}{}{}
       \name{author}{9}{}{%
         {{hash=7741bee37e2b3b818cfd6daff1bcc632}{%
@@ -3549,6 +3592,108 @@
       \endverb
       \keyw{brown dwarfs,radio continuum: stars,stars: activity,stars: low-mass,stars: magnetic field,Astrophysics - Solar and Stellar Astrophysics}
     \endentry
+    \entry{k2_missions_and_data_mast}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=2a435402df58ce0998a3896a6a9711f7}{%
+           family={{Mikulski Archive for Space Telescopes}},
+           familyi={M\bibinitperiod}}}%
+      }
+      \strng{namehash}{2a435402df58ce0998a3896a6a9711f7}
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+      \field{title}{K2}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://archive.stsci.edu/missions-and-data/k2
+      \endverb
+      \verb{url}
+      \verb https://archive.stsci.edu/missions-and-data/k2
+      \endverb
+    \endentry
+    \entry{kepler_missions_and_data_mast}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=2a435402df58ce0998a3896a6a9711f7}{%
+           family={{Mikulski Archive for Space Telescopes}},
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+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
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+      \field{title}{Kepler}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://archive.stsci.edu/missions-and-data/kepler
+      \endverb
+      \verb{url}
+      \verb https://archive.stsci.edu/missions-and-data/kepler
+      \endverb
+    \endentry
+    \entry{tess_extended_mission_1}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=2a435402df58ce0998a3896a6a9711f7}{%
+           family={{Mikulski Archive for Space Telescopes}},
+           familyi={M\bibinitperiod}}}%
+      }
+      \strng{namehash}{2a435402df58ce0998a3896a6a9711f7}
+      \strng{fullhash}{2a435402df58ce0998a3896a6a9711f7}
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+      \field{sortinit}{M}
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+      \field{extradate}{3}
+      \field{extradatescope}{labelyear}
+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{title}{{TESS Extended Mission}}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://archive.stsci.edu/contents/newsletters/august-2020/tess-extended-mission
+      \endverb
+      \verb{url}
+      \verb https://archive.stsci.edu/contents/newsletters/august-2020/tess-extended-mission
+      \endverb
+    \endentry
     \entry{faster_rot_stars_more_flares1}{article}{}{}
       \name{author}{2}{}{%
         {{hash=ce65f3b4ff48ef2a9aa3235f04763003}{%
@@ -3844,6 +3989,175 @@
       \endverb
       \keyw{binaries: eclipsing,binaries: spectroscopic,stars: abundances,stars: activity,stars: fundamental parameters,stars: individual: KOI-256,stars: late-type,stars: low-mass,stars: rotation,Astrophysics - Solar and Stellar Astrophysics}
     \endentry
+    \entry{nasa_kepler_in_depth}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=1f99771bc3e23e6097509a331544ab65}{%
+           family={NASA},
+           familyi={N\bibinitperiod}}}%
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+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{title}{{Kepler - In Depth}}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://science.nasa.gov/mission/kepler/in-depth/
+      \endverb
+      \verb{url}
+      \verb https://science.nasa.gov/mission/kepler/in-depth/
+      \endverb
+    \endentry
+    \entry{kepler_end_nasa_press}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=1f99771bc3e23e6097509a331544ab65}{%
+           family={NASA},
+           familyi={N\bibinitperiod}}}%
+      }
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+      \field{labeltitlesource}{title}
+      \field{title}{{NASA Retires Kepler Space Telescope}}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://www.jpl.nasa.gov/news/nasa-retires-kepler-space-telescope/
+      \endverb
+      \verb{url}
+      \verb https://www.jpl.nasa.gov/news/nasa-retires-kepler-space-telescope/
+      \endverb
+    \endentry
+    \entry{soho_nasa}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=1f99771bc3e23e6097509a331544ab65}{%
+           family={{NASA}},
+           familyi={N\bibinitperiod}}}%
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+      \field{title}{SOHO}
+      \field{urlday}{2}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://science.nasa.gov/mission/soho/
+      \endverb
+      \verb{url}
+      \verb https://science.nasa.gov/mission/soho/
+      \endverb
+    \endentry
+    \entry{tess_nasa}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=1f99771bc3e23e6097509a331544ab65}{%
+           family={NASA},
+           familyi={N\bibinitperiod}}}%
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+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://exoplanets.nasa.gov/tess/
+      \endverb
+      \verb{url}
+      \verb https://exoplanets.nasa.gov/tess/
+      \endverb
+    \endentry
+    \entry{kepler_missions_caltech}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=c9448cd0bc409f460f4bd29817ec24d6}{%
+           family={{NASA Exoplanet Archive}},
+           familyi={N\bibinitperiod}}}%
+      }
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+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{title}{Kepler Mission Information}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html
+      \endverb
+      \verb{url}
+      \verb https://exoplanetarchive.ipac.caltech.edu/docs/KeplerMission.html
+      \endverb
+    \endentry
     \entry{koidr25}{misc}{}{}
       \name{author}{1}{}{%
         {{hash=c9448cd0bc409f460f4bd29817ec24d6}{%
@@ -3861,6 +4175,7 @@
       \strng{authornamehash}{c9448cd0bc409f460f4bd29817ec24d6}
       \strng{authorfullhash}{c9448cd0bc409f460f4bd29817ec24d6}
       \strng{authorfullhashraw}{c9448cd0bc409f460f4bd29817ec24d6}
+      \field{extraname}{2}
       \field{sortinit}{N}
       \field{sortinithash}{22369a73d5f88983a108b63f07f37084}
       \field{extradatescope}{labelyear}
@@ -3880,6 +4195,40 @@
       \verb https://catcopy.ipac.caltech.edu/dois/doi.php?id=10.26133/NEA19
       \endverb
     \endentry
+    \entry{sunspot_mag_field_connecting_to_second}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=1baef6b0337528cce279aca5b98e272d}{%
+           family={Norton},
+           familyi={N\bibinitperiod},
+           given={Aimee},
+           giveni={A\bibinitperiod}}}%
+      }
+      \strng{namehash}{1baef6b0337528cce279aca5b98e272d}
+      \strng{fullhash}{1baef6b0337528cce279aca5b98e272d}
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+      \strng{authorbibnamehash}{1baef6b0337528cce279aca5b98e272d}
+      \strng{authornamehash}{1baef6b0337528cce279aca5b98e272d}
+      \strng{authorfullhash}{1baef6b0337528cce279aca5b98e272d}
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+      \field{sortinithash}{22369a73d5f88983a108b63f07f37084}
+      \field{extradatescope}{labelyear}
+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{title}{Unravelling magnetic knots in sunspots}
+      \field{urlday}{2}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://kipac.stanford.edu/highlights/unravelling-magnetic-knots-sunspots
+      \endverb
+      \verb{url}
+      \verb https://kipac.stanford.edu/highlights/unravelling-magnetic-knots-sunspots
+      \endverb
+    \endentry
     \entry{superflares_1}{article}{}{}
       \name{author}{9}{}{%
         {{hash=e21242c02073dce96845c446abd3ec2b}{%
@@ -3985,6 +4334,40 @@
       \verb 10.26093/cds/vizier
       \endverb
     \endentry
+    \entry{kepler_end_nytimes}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=28fa3a4b2d1f73568f4678f12dc01b72}{%
+           family={Overbye},
+           familyi={O\bibinitperiod},
+           given={Dennis},
+           giveni={D\bibinitperiod}}}%
+      }
+      \strng{namehash}{28fa3a4b2d1f73568f4678f12dc01b72}
+      \strng{fullhash}{28fa3a4b2d1f73568f4678f12dc01b72}
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+      \strng{authornamehash}{28fa3a4b2d1f73568f4678f12dc01b72}
+      \strng{authorfullhash}{28fa3a4b2d1f73568f4678f12dc01b72}
+      \strng{authorfullhashraw}{28fa3a4b2d1f73568f4678f12dc01b72}
+      \field{sortinit}{O}
+      \field{sortinithash}{2cd7140a07aea5341f9e2771efe90aae}
+      \field{extradatescope}{labelyear}
+      \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{title}{{Kepler, the Little NASA Spacecraft That Could, No Longer Can}}
+      \field{urlday}{1}
+      \field{urlmonth}{6}
+      \field{urlyear}{2025}
+      \field{urldateera}{ce}
+      \verb{urlraw}
+      \verb https://web.archive.org/web/20181030211627/https://www.nytimes.com/2018/10/30/science/nasa-kepler-exoplanet.html
+      \endverb
+      \verb{url}
+      \verb https://web.archive.org/web/20181030211627/https://www.nytimes.com/2018/10/30/science/nasa-kepler-exoplanet.html
+      \endverb
+    \endentry
     \entry{spectral_lines_temperature_correlation}{thesis}{}{}
       \name{author}{1}{}{%
         {{hash=e471a925addd85057d30b91b20d2aaae}{%
@@ -4344,8 +4727,10 @@
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       \strng{authorfullhash}{4967872d6bac0a0a27e46c2b9a493ba5}
       \strng{authorfullhashraw}{4967872d6bac0a0a27e46c2b9a493ba5}
+      \field{extraname}{1}
       \field{sortinit}{S}
       \field{sortinithash}{b164b07b29984b41daf1e85279fbc5ab}
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       \field{extradatescope}{labelyear}
       \field{labeldatesource}{}
       \field{labelnamesource}{author}
@@ -4364,6 +4749,84 @@
       \endverb
       \keyw{magnetic reconnection,particle acceleration,CMEs,plasmoid ejection,MHD,flux emergence,current sheet,space weather,Flares,waves,radiation,Flare,Current Sheet,Magnetic Reconnection,Flux Tube,Flux Rope}
     \endentry
+    \entry{flares_1}{article}{}{}
+      \name{author}{2}{}{%
+        {{hash=f1b717a188c0398fdf0b2eb36a34f93b}{%
+           family={{Shibata}},
+           familyi={S\bibinitperiod},
+           given={Kazunari},
+           giveni={K\bibinitperiod}}}%
+        {{hash=58170e9eae61386696b858a7dbc9b66e}{%
+           family={{Magara}},
+           familyi={M\bibinitperiod},
+           given={Tetsuya},
+           giveni={T\bibinitperiod}}}%
+      }
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+      \strng{bibnamehash}{4967872d6bac0a0a27e46c2b9a493ba5}
+      \strng{authorbibnamehash}{4967872d6bac0a0a27e46c2b9a493ba5}
+      \strng{authornamehash}{4967872d6bac0a0a27e46c2b9a493ba5}
+      \strng{authorfullhash}{4967872d6bac0a0a27e46c2b9a493ba5}
+      \strng{authorfullhashraw}{4967872d6bac0a0a27e46c2b9a493ba5}
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+      \field{extradatescope}{labelyear}
+      \field{labeldatesource}{}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{eid}{6}
+      \field{journaltitle}{Living Reviews in Solar Physics}
+      \field{month}{12}
+      \field{number}{1}
+      \field{title}{{Solar Flares: Magnetohydrodynamic Processes}}
+      \field{volume}{8}
+      \field{year}{2011}
+      \field{pages}{6}
+      \range{pages}{1}
+      \verb{doi}
+      \verb 10.12942/lrsp-2011-6
+      \endverb
+      \keyw{magnetic reconnection,particle acceleration,CMEs,plasmoid ejection,MHD,flux emergence,current sheet,space weather,Flares,waves,radiation,Flare,Current Sheet,Magnetic Reconnection,Flux Tube,Flux Rope}
+    \endentry
+    \entry{sunspots_overview}{article}{}{}
+      \name{author}{1}{}{%
+        {{hash=fc5ac166461d1d3e616007966bfc338e}{%
+           family={{Solanki}},
+           familyi={S\bibinitperiod},
+           given={Sami\bibnamedelima K.},
+           giveni={S\bibinitperiod\bibinitdelim K\bibinitperiod}}}%
+      }
+      \strng{namehash}{fc5ac166461d1d3e616007966bfc338e}
+      \strng{fullhash}{fc5ac166461d1d3e616007966bfc338e}
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+      \strng{authornamehash}{fc5ac166461d1d3e616007966bfc338e}
+      \strng{authorfullhash}{fc5ac166461d1d3e616007966bfc338e}
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+      \field{sortinithash}{b164b07b29984b41daf1e85279fbc5ab}
+      \field{extradatescope}{labelyear}
+      \field{labeldatesource}{}
+      \field{labelnamesource}{author}
+      \field{labeltitlesource}{title}
+      \field{journaltitle}{\aapr}
+      \field{month}{1}
+      \field{number}{2-3}
+      \field{title}{{Sunspots: An overview}}
+      \field{volume}{11}
+      \field{year}{2003}
+      \field{pages}{153\bibrangedash 286}
+      \range{pages}{134}
+      \verb{doi}
+      \verb 10.1007/s00159-003-0018-4
+      \endverb
+      \keyw{Sunspots,Sun: magnetic field,Sun: active regions,Sun: activity}
+    \endentry
     \entry{sqlite}{misc}{}{}
       \name{author}{1}{}{%
         {{hash=9a9ab6daa89d3a40e1d166986df843e3}{%
@@ -4703,30 +5166,27 @@
       \verb https://doi.org/10.5281/zenodo.3509134
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-      \field{urlyear}{2025}
-      \field{urldateera}{ce}
-      \verb{urlraw}
-      \verb https://exoplanets.nasa.gov/tess/
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-      \verb{url}
-      \verb https://exoplanets.nasa.gov/tess/
-      \endverb
-    \endentry
     \entry{tess_extended_mission_2}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=90d5b4d5a3c669a15509bd79657a5dcd}{%
+           family={TESS},
+           familyi={T\bibinitperiod}}}%
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       \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
       \field{labeltitlesource}{title}
       \field{title}{{TESS begins its second extended mission}}
       \field{urlday}{1}
@@ -4741,11 +5201,26 @@
       \endverb
     \endentry
     \entry{tess_tess}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=90d5b4d5a3c669a15509bd79657a5dcd}{%
+           family={TESS},
+           familyi={T\bibinitperiod}}}%
+      }
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+      \strng{fullhash}{90d5b4d5a3c669a15509bd79657a5dcd}
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       \field{labeldatesource}{url}
+      \field{labelnamesource}{author}
       \field{labeltitlesource}{title}
       \field{title}{{TESS begins its second extended mission}}
       \field{urlday}{1}
@@ -4759,22 +5234,36 @@
       \verb https://tess.mit.edu/science/
       \endverb
     \endentry
-    \entry{tess_extended_mission_1}{misc}{}{}
+    \entry{soho_project_page}{misc}{}{}
+      \name{author}{1}{}{%
+        {{hash=b51b77a277cdec6daf1cfafbc5c3a3fa}{%
+           family={{The SOHO Team}},
+           familyi={T\bibinitperiod}}}%
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-      \field{title}{{TESS Extended Mission}}
-      \field{urlday}{1}
+      \field{title}{SOHO}
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       \field{urlmonth}{6}
       \field{urlyear}{2025}
       \field{urldateera}{ce}
       \verb{urlraw}
-      \verb https://archive.stsci.edu/contents/newsletters/august-2020/tess-extended-mission
+      \verb https://soho.nascom.nasa.gov/
       \endverb
       \verb{url}
-      \verb https://archive.stsci.edu/contents/newsletters/august-2020/tess-extended-mission
+      \verb https://soho.nascom.nasa.gov/
       \endverb
     \endentry
     \entry{kepler_archive_manual}{article}{}{}

Physics_Thesis_Template/main.tex

@@ -35,7 +35,7 @@
 
 \newcommand{\thesisTitle}{Relating spot and flare/superflare occurrence on dwarf stars}
 \newcommand{\thesisSubtitle}{}
-\newcommand{\thesisName}{Markus Ornik}
+\newcommand{\thesisName}{Markus Ornik, BSc}
 \newcommand{\thesisSubject}{Master's Thesis}
 \newcommand{\thesisDegree}{Master of Science $-$ MSc}
 \newcommand{\thesisDate}{\today}
@@ -162,6 +162,8 @@
 % Load and Configure Packages
 % **************************************************
 \usepackage{amsmath,amssymb}
+\usepackage{cleveref}
+\crefformat{footnote}{#2\footnotemark[#1]#3}
 \usepackage{pdfpages}
 \usepackage[utf8]{inputenc}		% defines file's character encoding
 \usepackage[T1]{fontenc}
@@ -267,14 +269,16 @@
 \thesisauthor[Firstname Lastname]{\thesisName}
 \thesistitle[Short Thesis Title]{\thesisTitle \\ \thesisSubtitle}
 \thesisdate[ ]{\thesisDate}
-\supervisortitle{{Supervisors}} %Select singular/plural
+\supervisortitle{{Supervisor}} %Select singular/plural
 
 % Supervisor info
 \supervisor{%
   \thesisFirstSupervisor\\
-
+  \thesisUniversityInstitute, \thesisUniversity
+}
+\cosupervisor{
   \thesisSecondSupervisor\\
-
+  \thesisUniversityInstitute, \thesisUniversity
 }
 \academicdegree{Master of Science}
 \curriculum{Physics} %Degree programme

Physics_Thesis_Template/tugrazthesis.sty

@@ -67,6 +67,18 @@
   (set with \texttt{\textbackslash supervisor\{\}})
 }
 \newcommand{\supervisor}[1]{\def\@supervisor{#1}}
+\def\@cosupervisortitle{Co-Supervisor}
+\newcommand{\cosupervisortitle}[1]{\def\@cosupervisortitle{#1}}
+\def\@cosupervisor{%
+  Firstname Lastname, academic degrees of supervisor\\
+  up to 2 lines
+  \par
+  Institute's name\\
+  up to 2 lines
+  \par
+  (set with \texttt{\textbackslash cosupervisor\{\}})
+}
+\newcommand{\cosupervisor}[1]{\def\@cosupervisor{#1}}
 \def\@location{Graz}
 \newcommand{\location}[1]{\def\@location{#1}}
 
@@ -83,6 +95,8 @@
     \linespread{1.2}%
     \iftugraz@nawi
       \noindent
+      \unigrazlogoscaled[17mm]
+      \hfill
       \nawilogoscaled[46mm]
       \hfill
       \tuglogoscaled[29mm]
@@ -132,6 +146,11 @@
     {\bfseries\tugraz@titlefont\fontsize{10pt}{12pt}\selectfont \@supervisortitle \par}
 
     {\fontsize{10pt}{12pt}\selectfont \@supervisor \par}
+    %\iftugraz@individual\vskip1.2cm\else\vskip1.4cm\fi
+
+    {\bfseries\tugraz@titlefont\fontsize{10pt}{12pt}\selectfont \@cosupervisortitle \par}
+
+    {\fontsize{10pt}{12pt}\selectfont \@cosupervisor \par}
     \iftugraz@individual\vskip1.2cm\else\vskip1.4cm\fi
 
     {\fontsize{8pt}{11pt}\selectfont \@location, \@thesisdate \par}
@@ -692,4 +711,26 @@
 
   \end{tikzpicture}
 }
+
+\providecommand{\unigrazlogoscaled}[1][12.1mm]{\resizebox{#1}{!}{\unigrazlogo}}
+
+\definecolor{cbdbcbc}{RGB}{189,188,188}
+\definecolor{cfcd205}{RGB}{252,210,5}
+\definecolor{c231f20}{RGB}{35,31,32}
+\def \globalscale {1.000000}
+
+\providecommand{\unigrazlogo}{%
+  \begin{tikzpicture}[y=1cm, x=1cm, yscale=\globalscale,xscale=\globalscale, every node/.append style={scale=\globalscale}, inner sep=0pt, outer sep=0pt]
+    \path[fill=cbdbcbc,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (3.8676, -0.3366) -- (25.9137, -0.3366) -- (25.9137, -19.0866) -- (3.8676, -19.0866) -- (3.8676, -0.3366);
+    \path[fill=cfcd205,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (11.4061, -18.1196) -- (24.9469, -18.1196) -- (24.9469, -4.5385) -- (11.4061, -4.5385) -- (11.4061, -18.1196);
+    \path[fill=c231f20,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (19.3098, -6.3147) -- (19.3098, -8.2839) -- (18.3296, -8.2839) -- (18.3296, -6.4598).. controls (18.3296, -6.028) and (18.0722, -5.74) .. (17.6987, -5.7395).. controls (17.3249, -5.7395) and (17.0662, -6.0093) .. (17.0662, -6.4598) -- (17.0662, -8.2839) -- (16.0931, -8.2837) -- (16.0931, -6.3143).. controls (16.0931, -5.4516) and (16.8403, -4.7959) .. (17.7027, -4.7964).. controls (18.5648, -4.7973) and (19.3098, -5.4526) .. (19.3098, -6.3147);
+    \path[fill=c231f20,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (22.5141, -4.8177) -- (22.8117, -4.8177) -- (22.8117, -8.2849) -- (21.842, -8.2849) -- (21.842, -6.7388) -- (20.0633, -8.3481) -- (19.789, -8.3481) -- (19.787, -4.8629) -- (20.7612, -4.8624) -- (20.7612, -6.4072) -- (22.5141, -4.8177);
+    \path[fill=c231f20,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (23.337, -4.8629) -- (24.3103, -4.8629) -- (24.3103, -8.2839) -- (23.337, -8.2839) -- (23.337, -4.8629);
+    \path[fill=c231f20,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (24.9469, -4.5385) -- (11.4061, -4.5385) -- (11.4061, -1.3036) -- (24.9469, -1.3036) -- (24.9469, -4.5385);
+    \path[fill=white,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (4.8343, -18.1196) -- (11.4061, -18.1196) -- (11.4061, -1.3036) -- (4.8343, -1.3036) -- (4.8343, -18.1196);
+    \path[fill=cfcd205,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (24.3103, -2.2816) -- (22.6547, -2.2816) -- (22.6547, -2.4354) -- (23.5178, -3.798) -- (22.6679, -3.798) -- (22.6679, -4.2653) -- (24.3103, -4.2653) -- (24.3103, -4.1519) -- (23.4101, -2.7489) -- (24.3103, -2.7489) -- (24.3103, -2.2816);
+    \path[fill=cfcd205,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (21.5042, -4.2839) -- (21.3747, -4.2839) -- (20.3445, -2.3374) -- (19.8742, -3.0039).. controls (20.1051, -3.1003) and (20.2217, -3.2955) .. (20.2217, -3.5641).. controls (20.2217, -3.9589) and (19.9301, -4.2653) .. (19.4861, -4.2653) -- (18.5392, -4.2653) -- (18.5392, -2.2816) -- (19.0926, -2.2816) -- (19.0926, -2.8598) -- (19.3921, -2.8598) -- (19.7755, -2.2816) -- (20.895, -2.2816) -- (21.0598, -2.6259) -- (21.7922, -2.6259) -- (21.9568, -2.2816) -- (22.5339, -2.2816) -- cycle(19.4339, -3.3271) -- (19.0926, -3.3271) -- (19.0926, -3.798) -- (19.4339, -3.798).. controls (19.6461, -3.798) and (19.7096, -3.6931) .. (19.7096, -3.5641).. controls (19.7096, -3.4309) and (19.6461, -3.3271) .. (19.4339, -3.3271) -- cycle(21.2044, -3.0324) -- (21.428, -3.551) -- (21.6444, -3.0324) -- cycle;
+    \path[fill=cfcd205,nonzero rule,cm={ 0.1333,-0.0,-0.0,-0.1333,(0.0, 0.4708)}] (18.1531, -3.1954).. controls (18.1549, -3.0232) and (18.135, -2.8575) .. (18.0652, -2.7243).. controls (17.9083, -2.4218) and (17.5461, -2.244) .. (17.1637, -2.244).. controls (16.5398, -2.244) and (16.1137, -2.7044) .. (16.1137, -3.2725).. controls (16.1137, -3.8404) and (16.5935, -4.3007) .. (17.1637, -4.3007).. controls (17.506, -4.3007) and (17.8088, -4.1351) .. (17.9965, -3.8801) -- (17.5928, -3.5941).. controls (17.4864, -3.7385) and (17.3572, -3.8206) .. (17.1637, -3.8206).. controls (16.8391, -3.8206) and (16.6218, -3.5957) .. (16.6218, -3.2725).. controls (16.6218, -2.9496) and (16.846, -2.7377) .. (17.1709, -2.7377).. controls (17.4527, -2.7377) and (17.6086, -2.8531) .. (17.6467, -2.9976) -- (17.31, -2.9976) -- (17.31, -3.3595) -- (18.1526, -3.3595) -- (18.1531, -3.1954);
+  \end{tikzpicture}
+}
 %}}}