diff --git a/presentation/backmatter/discussion.tex b/presentation/backmatter/discussion.tex
index 17f279a13878da78f6d18359d1725941e068f56f..75d500bd380533598cb1c281342dfc5604deff90 100644
--- a/presentation/backmatter/discussion.tex
+++ b/presentation/backmatter/discussion.tex
@@ -11,7 +11,7 @@
% KKR theory slide from mavropoulous dft20 kkr lecture; backup slides
{
\setbeamercolor{background canvas}{bg=}
- \includepdf[pages={15,17,19,27-28,30-31}]{../resources/fig/external/presentations/rwth-dft20/lecture-20-kkr/Lecture20_KKRGF-Method.pdf}
+ \includepdf[pages={15,17,19,27-28,29,31}]{../resources/fig/external/presentations/rwth-dft20/lecture-20-kkr/Lecture20_KKRGF-Method.pdf}
}
diff --git a/presentation/frontmatter/slides-repo.tex b/presentation/frontmatter/slides-repo.tex
index 831fae45350bee3ef8e778c06f6beeed5b8711f2..9bb73ff6134b5acd68b299c496a78beb46f9fa8c 100644
--- a/presentation/frontmatter/slides-repo.tex
+++ b/presentation/frontmatter/slides-repo.tex
@@ -3,7 +3,7 @@
% \frametitle{Slides metadata}
\begin{center}
- Talk held at hzdr-casus group meeting for ongoing collaboration project via
+ Talk held at HZDR-CASUS \href{https://sites.google.com/view/mlmd}{MLMD} group meeting for ongoing collaboration project via
HIDA Trainee Network.
\vspace*{2em}
diff --git a/presentation/mainmatter/introduction.tex b/presentation/mainmatter/introduction.tex
index 1068d96adc473cc53f7493f0ac6a2a33c6eb4e90..b77e4cd35ab372d15b6ceb84cb39ae5df21b69d3 100644
--- a/presentation/mainmatter/introduction.tex
+++ b/presentation/mainmatter/introduction.tex
@@ -48,6 +48,76 @@
\end{columns}
\end{frame}
+% Slide funding % Section introduction
+\begin{frame}[c,plain]
+ \frametitle{My funding}
+ % \framesubtitle{HIDA, HDSLEE, AIDAS, DAEMON}
+ \vspace*{0em}
+ \begin{columns}[c]
+ \begin{column}{0.3\linewidth}
+ \textbf{\color{fzjblue}{This research visit}}
+
+ {\small HIDA Trainee Network}
+
+ \vspace*{1em}
+
+ \begin{center}
+ \hspace*{-2em}\includegraphics[width=0.8\textwidth]{../resources/fig/logos/hida/HiDA_Logo_RGB_kompakt-cropped.png}\vspace*{1em}
+ % \hspace*{-2em}\includegraphics[width=0.8\textwidth]{../resources/fig/logos/hds-lee/adapted/HDS_LEE_Logo_Solo_RGB_cropped.pdf}\vspace*{1em}
+ % \hspace*{-2em}\includegraphics[width=0.8\textwidth]{../resources/fig/logos/hds-lee/adapted/HDS_LEE_Logo_Text_RGB_cropped.pdf}
+ \end{center}
+
+ \vspace*{1em}\hrule{}\vspace*{2em}
+
+ \textbf{\color{fzjblue}{My PhD}}
+
+ {\small HIDA Grad School HDSLEE \&}
+
+ {\small EU Joint Virtual Lab}
+
+ \vspace*{1em}
+
+ \includegraphics[width=0.8\textwidth]{../resources/fig/logos/aidas/AIDAS-72dpi-no-bg.png}%
+ % {\color{fzjblue}{on Artificial Intelligence, Data Analytics and Scalable Simulation}}
+
+ \end{column}
+ \vrule{}\hspace*{2em}
+ \begin{column}{0.6\linewidth}
+ % left side. DAEMON Network
+ \begin{columns}[c]
+ \begin{column}{0.35\linewidth}
+ \vspace*{3em}
+ \begin{center}
+ % \includegraphics[width=0.7\textwidth]{../resources/fig/github/best-of-aml-thumbnail-2023-09-05.png}%
+ \includegraphics[width=1.0\textwidth]{../resources/fig/cost-daemon/daemon-working-groups-circle.png}%
+ \vspace*{1em}
+ Join via \\\large{\href{https://cost-daemon.eu/}{cost-daemon.eu}}
+ \end{center}
+ \end{column}
+
+ \begin{column}{0.6\linewidth}
+ \begin{center}
+ \includegraphics[width=0.45\textwidth]{../resources/fig/logos/cost-daemon/cost-daemon-logo-2025.png}%
+ \hspace*{1em}
+ \includegraphics[width=0.3\textwidth]{../resources/fig/logos/cost-eu/cost-eu-logo-no-bg.png}%
+ \end{center}
+ \emph{European network for data-driven materials science}\vspace*{1em}
+ {\footnotesize
+ \begin{itemize}
+ % \setlength\itemsep{1em}
+ \item[\textbf{\faPlay{} WG1:}] Community standards: data, workflows and codes for materials design.
+ \item[\textbf{\faPlay{} WG2:}] Representations and algorithms for materials design for “single-modality†use.
+ \item[\textbf{WG3:}] Multi-modal machine learning methods for advanced materials design.
+ \item[\textbf{WG4:}] Process-structure-property relationships in materials. Novel insights and applications.
+ \item[\textbf{WG5:}] Training, Dissemination, Exploitation, Outreach
+ \end{itemize}
+ }
+ \end{column}
+ \end{columns}
+ \end{column}
+ \end{columns}
+\end{frame}
+
% Slide my research group % Section introduction
@@ -155,83 +225,25 @@
\end{columns}
\vspace*{0em}
- {\large \faGithub{} \href{https://github.com/JuDFTteam}{JuDFTteam}}
+ {\large \href{http://judft.de}{judft.de} \quad \textbf{//} \quad \faGithub{} \href{https://github.com/JuDFTteam}{JuDFTteam}}
+ % {\large \faGithub{} \href{https://github.com/JuDFTteam}{JuDFTteam}}
\end{center}
\end{frame}
-
-% Slide funding % Section introduction
+% Slide all-electron DFT % Section phd-project
\begin{frame}[c,plain]
- \frametitle{My funding}
- % \framesubtitle{HIDA, HDSLEE, AIDAS, DAEMON}
- \vspace*{0em}
- \begin{columns}[c]
- \begin{column}{0.3\linewidth}
- \textbf{\color{fzjblue}{This research visit}}
-
- {\small HIDA Trainee Network}
-
- \vspace*{1em}
-
- \begin{center}
- \hspace*{-2em}\includegraphics[width=0.8\textwidth]{../resources/fig/logos/hida/HiDA_Logo_RGB_kompakt-cropped.png}\vspace*{1em}
- % \hspace*{-2em}\includegraphics[width=0.8\textwidth]{../resources/fig/logos/hds-lee/adapted/HDS_LEE_Logo_Solo_RGB_cropped.pdf}\vspace*{1em}
- % \hspace*{-2em}\includegraphics[width=0.8\textwidth]{../resources/fig/logos/hds-lee/adapted/HDS_LEE_Logo_Text_RGB_cropped.pdf}
- \end{center}
-
- \vspace*{1em}\hrule{}\vspace*{2em}
-
- \textbf{\color{fzjblue}{My PhD}}
-
- {\small HIDA Grad School HDSLEE \&}
-
- {\small EU Joint Virtual Lab}
-
- \vspace*{1em}
+ \frametitle{JuDFT codes accuracy}
+ % frametitle notes: PhD project flowchart
- \includegraphics[width=0.8\textwidth]{../resources/fig/logos/aidas/AIDAS-72dpi-no-bg.png}%
- % {\color{fzjblue}{on Artificial Intelligence, Data Analytics and Scalable Simulation}}
+ FLEUR and JuKKR are all-electron, full-potential open-source codes.
+ \vspace*{0em}
- \end{column}
- \vrule{}\hspace*{2em}
- \begin{column}{0.6\linewidth}
- % left side. DAEMON Network
- \begin{columns}[c]
- \begin{column}{0.35\linewidth}
- \vspace*{3em}
- \begin{center}
- % \includegraphics[width=0.7\textwidth]{../resources/fig/github/best-of-aml-thumbnail-2023-09-05.png}%
- \includegraphics[width=1.0\textwidth]{../resources/fig/cost-daemon/daemon-working-groups-circle.png}%
- \vspace*{1em}
- Join via \\\large{\href{https://cost-daemon.eu/}{cost-daemon.eu}}
- \end{center}
- \end{column}
+ \includegraphics[width=0.8\textwidth]{../resources/fig/external/papers/bosoniHowVerifyPrecision2024/fig4-clip1.pdf}\footcite{bosoniHowVerifyPrecision2024}
- \begin{column}{0.6\linewidth}
- \begin{center}
- \includegraphics[width=0.45\textwidth]{../resources/fig/logos/cost-daemon/cost-daemon-logo-2025.png}%
- \hspace*{1em}
- \includegraphics[width=0.3\textwidth]{../resources/fig/logos/cost-eu/cost-eu-logo-no-bg.png}%
- \end{center}
- \emph{European network for data-driven materials science}\vspace*{1em}
- {\footnotesize
- \begin{itemize}
- % \setlength\itemsep{1em}
- \item[\textbf{\faPlay{} WG1:}] Community standards: data, workflows and codes for materials design.
- \item[\textbf{\faPlay{} WG2:}] Representations and algorithms for materials design for “single-modality†use.
- \item[\textbf{WG3:}] Multi-modal machine learning methods for advanced materials design.
- \item[\textbf{WG4:}] Process-structure-property relationships in materials. Novel insights and applications.
- \item[\textbf{WG5:}] Training, Dissemination, Exploitation, Outreach
- \end{itemize}
- }
- \end{column}
- \end{columns}
- \end{column}
- \end{columns}
+ \vspace*{0em}
\end{frame}
-
% Slide AiiDA engine % Section introduction
\begin{frame}[plain,c]
% \frametitle{{\small AiiDA}}
@@ -281,45 +293,6 @@
\end{frame}
-
-% Slide PhD project flowchart % Section phd-project
-\begin{frame}
- \frametitle{My PhD project}
- % frametitle notes: PhD project flowchart
- \framesubtitle{\href{https://go.fzj.de/wasmer}{go.fzj.de/wasmer}}
- \vspace*{0em}
-
- \includegraphics[width=1.0\textwidth]{../resources/fig/presentation-2023-02/atomistic-ml/classification-of-atomistic-ml_presentation-2023-02_02-emph-both_ktikz.pdf}
-
- \vspace*{2em}
- \begin{columns}[t]
- \hspace{1em}
- \begin{column}{0.6\linewidth}
- \begin{center}
- Electronic structure emulator
-
- for fast SCF convergence
- \end{center}
- \end{column}
- \vrule{}
- \hspace{1em}
- \begin{column}{0.39\linewidth}
- \begin{center}
- Magnetic property prediction
-
- for spin dynamics simulation
- \end{center}
- \end{column}
- \end{columns}
-\end{frame}
-
-% Slide MTIs (magnetic topological insulators) % Section co-doping
-{
- \setbeamercolor{background canvas}{bg=}
- \includepdf[pages=1]{../resources/fig/presentation-2023-03/ruess/ruess-TIs.pdf}
-}
-
-
%%% Local Variables:
%%% mode: latex
%%% TeX-master: "../presentation"
diff --git a/presentation/mainmatter/jij-prediction.tex b/presentation/mainmatter/jij-prediction.tex
new file mode 100644
index 0000000000000000000000000000000000000000..8c1dbb4f0aaebadcdf4fb5baedae2641e687a0d6
--- /dev/null
+++ b/presentation/mainmatter/jij-prediction.tex
@@ -0,0 +1,263 @@
+\section{Machine learning exchange interactions}
+\label{sec:ml-exc-inter}
+
+% Slide PhD project flowchart % Section phd-project
+\begin{frame}
+ \frametitle{Vision: Electronic structure learning}
+ % frametitle notes: PhD project flowchart
+ \framesubtitle{as integrated, high-level multiscale workflows}
+ \vspace*{0em}
+
+ \includegraphics[width=1.0\textwidth]{../resources/fig/presentation-2023-02/atomistic-ml/classification-of-atomistic-ml_presentation-2023-02_02-emph-both_ktikz.pdf}
+
+ \vspace*{2em}
+ \begin{columns}[t]
+ \hspace{1em}
+ \begin{column}{0.6\linewidth}
+ \begin{center}
+ Better \enquote{initial guess}
+
+ for fast SCF convergence
+ \end{center}
+ \end{column}
+ \vrule{}
+ \hspace{1em}
+ \begin{column}{0.39\linewidth}
+ \begin{center}
+ Magnetic property prediction
+
+ (ML-Exc) for spin dynamics
+ \end{center}
+ \end{column}
+ \end{columns}
+\end{frame}
+
+
+% Slide MTIs (magnetic topological insulators) % Section co-doping
+{
+ \setbeamercolor{background canvas}{bg=}
+ \includepdf[pages=1]{../resources/fig/presentation-2023-03/ruess/ruess-TIs.pdf}
+}
+
+% Slide study design % Section co-doping
+\begin{frame}[plain,c]
+ \frametitle{Project \enquote{ML-Exc}}
+ \framesubtitle{Magnetic co-doping of topological insulators}
+
+ \hspace*{1em} \ce{Bi2Te3} \hspace*{3em} Dimer clusters of \(3d\), \(4d\) transition
+ metal defects\vspace*{-1em}
+
+ \begin{columns}[c]
+ \hspace*{1em}
+ \begin{column}{0.6\textwidth}
+ \begin{center}
+ \includegraphics[width=0.35\textheight]{../resources/fig/external/papers/mozumderHighthroughputMagneticCodoping2024/processed/Fig1-a.pdf}%
+ \hspace*{-0.5em}
+ \includegraphics[width=0.80\textwidth]{../resources/fig/external/papers/mozumderHighthroughputMagneticCodoping2024/processed/FigA3-extract-6.pdf}%
+ \end{center}
+ \end{column}
+ \hspace*{3em}
+ \begin{column}{0.4\textwidth}
+ {\small
+ Single-impurity dabase, N=2'000.
+ \href{https://go.fzj.de/judit}{go.fzj.de/judit}\vspace*{1em}
+
+ Dimer database, N=2'000\footcite{mozumderHighthroughputMagneticCodoping2024}.\vspace*{3em}
+
+ Co-doping can help to control
+
+ \begin{itemize}
+ \item critical \(T_c\) of QAHE
+ \item exchange splitting \(\Delta_{xc}\)
+ \item long-range magnetic ordering
+ \end{itemize}\vspace*{1em}
+
+ for applications in spintronics and
+
+ fault-tolerant quantum computing.
+ }
+ \end{column}
+ \end{columns}
+\end{frame}
+
+% Slide AiiDA-KKR workflows % Section co-doping
+\begin{frame}[plain,c]
+ \frametitle{Project \enquote{ML-Exc}}
+ \framesubtitle{\logoAiida{}-KKR workflows\footcite{russmannAiiDAKKRPluginIts2021}}
+ \vspace*{-1em}
+ \begin{columns}[t]
+ \hspace*{-2em}
+ \begin{column}{0.3\linewidth}
+ % {\footnotesize Single impurity}
+ \begin{center}
+ \includegraphics[width=0.8\linewidth]{../resources/fig/presentation-2023-03/ruess/ruess-aiida-kkr-paper-workflow-c.pdf}
+ \end{center}
+ \end{column}
+ \begin{column}{0.5\linewidth}
+ \hspace*{-3em}
+ \begin{center}
+ % {\footnotesize \(N+1\) impurities}
+ \includegraphics[width=0.8\linewidth]{../resources/fig/external/papers/mozumderHighthroughputMagneticCodoping2024/processed/FigA2-no-subfigure-labels.pdf}%
+ \end{center}
+ \end{column}
+ \end{columns}
+ \vspace*{-0em}
+ \begin{flushright}
+ Extended Heisenberg Hamiltonian.
+ \(H = -\frac{1}{2}\sum_{i,j}J_{ij} \, \vec{S}_i \cdot \vec{S}_j
+ -\frac{1}{2}\sum_{i,j}\vec{D}_{ij} \cdot \left( \vec{S}_i \times \vec{S}_j \right)
+ \)
+
+ Exchange constants from method of infinitesimal rotations\footcite{liechtensteinLocalSpinDensity1987}.
+ \( % Liechtenstein infinitesimal roation Jij from KKR-GF
+ \mathcal{J}_{ij} = -\frac{1}{\pi} \operatorname{Im} \int_{-\infty}^{E_F}
+ \mathrm{d} E \operatorname{Tr}[\delta t_i G_{ij} \delta t_j G_{ji}]
+ \)
+ \end{flushright}
+\end{frame}
+
+% Slide results Jijs 1 % Section co-doping
+{
+ \setbeamercolor{background canvas}{bg=}
+ \includepdf[pages=1]{../resources/fig/external/papers/mozumderHighthroughputMagneticCodoping2024/originals/Fig4.pdf}
+}
+
+% Slide AiiDA-Spirit workflows % Section jij-prediction
+\begin{frame}[plain,c]
+ \frametitle{Spin dynamics with \logoAiida{}-\raisebox{-0.4em}{\logoSpiritWithText{}}\footcite{russmannAiiDASpiritPluginAutomated2022}}
+ \vspace*{-2em}
+ \begin{columns}[t]
+ \begin{column}{0.4\linewidth}
+ \begin{center}
+ \includegraphics[width=1.0\linewidth]{../resources/fig/external/papers/mozumderHighthroughputMagneticCodoping2024/processed/FigA2-no-subfigure-labels.pdf}%
+ % \includegraphics[width=1.0\linewidth]{../resources/fig/presentation-2023-03/ruess/ruess-aiida-kkr-paper-workflow-c.pdf}\footcite{russmannAiiDAKKRPluginIts2021}
+
+ \vspace*{1em}
+ Liechtenstein formula
+ \[
+ \mathcal{J}_{ij} = -\frac{1}{\pi} \operatorname{Im} \int_{-\infty}^{E_F}
+ \mathrm{d} E \operatorname{Tr}[\delta t_i G_{ij} \delta t_j G_{ji}]
+ \]
+
+ ML-IAP approach. \(E_k = \sum_k E_k \longrightarrow J_{ij} =
+ \sum_k \left( J_{ij} \right)_k\)
+
+
+ \end{center}
+ \end{column}
+ \begin{column}{0.55\linewidth}
+ \begin{center}
+ \includegraphics[width=1.0\linewidth]{../resources/fig/presentation-2023-03/ruess/ruess-aiida-spirit-paper-workflow.pdf}%
+
+ Landau-Lifshitz-Gilbert equation
+ \[
+ \frac{\partial \vec{S}_i}{\partial t}=-\gamma^{\prime} \vec{S}_i \times \vec{B}_i^{\text {eff }}-\lambda \vec{S}_i \times\left(\vec{S}_i \times \vec{B}_i^{\text {eff }}\right)
+ \]
+
+ % \vspace*{2em}
+ \normalsize{\href{https://juspin.de}{juspin.de}}
+ \end{center}
+ \end{column}
+ \end{columns}
+\end{frame}
+
+
+
+
+
+
+% Slide project design % Section jij-prediction
+\begin{frame}[plain,c]
+ \frametitle{Project \enquote{ML-Exc}}
+ \framesubtitle{Model selection}
+
+ \begin{table}[H]
+ \resizebox{\columnwidth}{!}{%
+ \centering
+ \input{../resources/table/jij-prediction-model-selection}%
+ % \caption[short caption]{Long caption.}
+ % \label{tab:model-selection}
+ }
+ \end{table}
+\end{frame}
+
+
+% Slide exc-int tensor prediction % Section jij-prediction
+\begin{frame}
+ \frametitle{Project \enquote{ML-Exc}}
+ \framesubtitle{Tensorial interaction}
+ Heisenberg Hamiltonian in tensor form.
+
+ \[\mathcal{H}_H=-\sum_{j>i} \vec{m}_i \cdot \mathcal{J}_{i j} \vec{m}_j\]
+
+ Tensor components: isotropic, anti-symmetric (DMI) and anisotropic or
+ traceless symmetric part (neglected so far).
+
+ \[\mathcal{J}_{i j}=J_{i j} \mathbb{1} + \mathcal{J}_{i j}^A+\mathcal{J}_{i
+ j}^S\]
+
+ with \(J_{i j}^{x x}=J_{i j}^{y y}=J_{i j}^{z z}=\frac{1}{3} J_{i j}\) and
+
+ \[\mathcal{J}_{i j}^A=\left[\begin{array}{ccc}
+ 0 & J_{i j}^{x y} & J_{i j}^{x z} \\
+ J_{i j}^{y x} & 0 & J_{i j}^{y z} \\
+ J_{i j}^{z x} & J_{i j}^{z y} & 0
+ \end{array}\right]=\left[\begin{array}{ccc}
+ 0 & J_{i j}^{x y} & -J_{i j}^{z x} \\
+ -J_{i j}^{x y} & 0 & J_{i j}^{y z} \\
+ J_{i j}^{z x} & -J_{i j}^{y z} & 0
+ \end{array}\right]=\left[\begin{array}{ccc}
+ 0 & -D_{i j}^z & D_{i j}^y \\
+ D_{i j}^z & 0 & -D_{i j}^x \\
+ -D_{i j}^y & D_{i j}^x & 0
+ \end{array}\right]\]
+
+\end{frame}
+
+% Slide higher-order exchange interactions
+{
+ \setbeamercolor{background canvas}{bg=}
+ \includepdf[pages=1]{../resources/fig/external/presentations/spinqx23/hkatsumoto/spinqx23-hkatsumoto-page24.pdf}
+}
+
+% Slide relativistic exchange interactions
+{
+ \setbeamercolor{background canvas}{bg=}
+ \includepdf[pages=1]{../resources/fig/external/presentations/spinqx23/hkatsumoto/spinqx23-hkatsumoto-page25.pdf}
+}
+
+
+% Slide best-of-aml % Section odds-and-ends
+\begin{frame}[plain,c]
+ \frametitle{Community resources}
+ \framesubtitle{Best of atomistic machine learning}
+ \vspace*{-4em}
+ \begin{columns}[c]
+ \begin{column}{0.5\linewidth}
+ \vspace*{3em}
+ \begin{center}
+ % \includegraphics[width=0.7\textwidth]{../resources/fig/github/best-of-aml-thumbnail-2023-09-05.png}%
+ \includegraphics[width=0.9\textwidth]{../resources/fig/github/best-of-aml-thumbnail-2024-07-08.png}%
+
+ Largest list of atomistic ML tools on the web (400+), auto-ranked,
+ regular updates\footcite{wasmerBestAtomisticMachine2023}
+
+ \vspace*{2em}
+ \Large{\href{https://go.fzj.de/best-of-aml}{go.fzj.de/baml}}
+ \end{center}
+
+ \end{column}
+
+ \begin{column}{0.4\linewidth}
+ \includegraphics[width=0.85\textwidth]{../resources/fig/github/best-of-aml-contents-2024-07-08.png}%
+ \end{column}
+ \end{columns}
+\end{frame}
+
+
+%%% Local Variables:
+%%% mode: latex
+%%% TeX-master: "../presentation"
+%%% mode: flyspell
+%%% ispell-local-dictionary: "english"
+%%% End:
diff --git a/presentation/mainmatter/kkr-jlcdm.tex b/presentation/mainmatter/kkr-jlcdm.tex
index 5aea89a9f3b025be30a3627e442ab390e378aa61..378446a47b912ff0e80e9e07829de2a72132cd2d 100644
--- a/presentation/mainmatter/kkr-jlcdm.tex
+++ b/presentation/mainmatter/kkr-jlcdm.tex
@@ -1,35 +1,88 @@
-\section{KKR-JLCDM}
+\section{Better initial guess}
\label{sec:kkr-jlcdm}
-% Slide outlook vimp-prediction % Section odds-and-ends
+% Slide PhD project flowchart % Section phd-project
+\begin{frame}
+ \frametitle{Vision: Electronic structure learning}
+ % frametitle notes: PhD project flowchart
+ \framesubtitle{as integrated, high-level multiscale workflows}
+ \vspace*{0em}
+
+ \includegraphics[width=1.0\textwidth]{../resources/fig/presentation-2023-02/atomistic-ml/classification-of-atomistic-ml_presentation-2023-02_02-emph-both_ktikz.pdf}
+
+ \vspace*{2em}
+ \begin{columns}[t]
+ \hspace{1em}
+ \begin{column}{0.6\linewidth}
+ \begin{center}
+ Better \enquote{initial guess}
+
+ for fast SCF convergence
+ \end{center}
+ \end{column}
+ \vrule{}
+ \hspace{1em}
+ \begin{column}{0.39\linewidth}
+ \begin{center}
+ Magnetic property prediction
+
+ (ML-Exc) for spin dynamics
+ \end{center}
+ \end{column}
+ \end{columns}
+\end{frame}
+
+% Slide AiiDA-KKR workflows % kkr-theory
+\begin{frame}[plain,c]
+ \frametitle{Project \enquote{Better initial guess}}
+ \framesubtitle{\logoAiida{}-KKR workflows}
+ \vspace*{0em}
+ \begin{columns}[t]
+ \vspace*{-1em}
+ \begin{column}{0.3\linewidth}
+ % {\footnotesize Single impurity}
+ \begin{center}
+ \includegraphics[width=0.95\linewidth]{../resources/fig/presentation-2023-03/ruess/ruess-aiida-kkr-paper-workflow-c.pdf}\footcite{russmannAiiDAKKRPluginIts2021}
+ \end{center}
+ \end{column}
+ \begin{column}{0.5\linewidth}
+ \vspace*{-2em}
+ \begin{center}
+ \includegraphics[width=0.75\textheight]{../resources/fig/aiida-kkr/graph//kkr_imp_wc.pdf}%
+ \end{center}
+ % \framezoom<1><2>(3.5cm,0.5cm)(4.5cm,3.25cm) % upper part, kkr_scf workflow
+ % \framezoom<1><3>(4.5cm,3.5cm)(4.5cm,5.25cm) % lower part, kkr_imp workflow
+ \end{column}
+\end{columns}
+\vspace*{-0em}
+\end{frame}
+
+
+% Slide dataset generation (single-impurity-database)
\begin{frame}[plain]
- \frametitle{Electronic structure emulator}
+ \frametitle{Project \enquote{Better initial guess}}
+ \framesubtitle{Data generation}
% frametitle notes: Vimp-prediction qnd
\begin{columns}[c]
\begin{column}{0.45\linewidth}
{\small
- \textbf{Task} Predict electron potential difference \(\Delta
- V_{imp}(\vec{r})\) \& use as initial guess for \logoAiida -KKR\logoKKRimpCircled{}\vspace{0.5em}
-
- \textbf{Data} 10'000 single impurity in elemental crystal combinations
- (\(60 \times 40\) elements) from DFT\vspace{0.5em}
-
- \textbf{Challenges}
- \begin{itemize}
- \item[\textcolor{fzjblue}{\faFlag}] \textbf{Collaboration} Adapt the linear Jacobi-Legendre Charge Density
- Model (JLCDM)\footcite{focassioLinearJacobiLegendreExpansion2023a} to
- all-electron DFT
- \item Large chemical feature space
- \item From radial to full equivariant potential
- \item Intermediate SCF results
- \item Should be code-agnostic
- \item From collinear to noco magnetism
- \end{itemize}\vspace{0.5em}
+ \textbf{Data} 10'000 impurity embeddings into elemental crystals\vspace{0.5em}
+ \textbf{Target} Electron potential difference \(\Delta
+ V_{imp}(\vec{r})\) \vspace{0.5em}
}
+
+ \includegraphics[width=1.0\linewidth]{../resources/fig/aiida-kkr-ml/da/conv_heatmap_scale-factor_count_linscale_annot.pdf}%
+
+ \begin{center}
+ {\footnotesize \textcolor{fzjgray50}{Dataset map. Rows: Element of host crystal,
+ columns: impurity atom, color: num. calculations.}}
+ \end{center}
\end{column}
+
\begin{column}{0.55\linewidth}
+ \vspace*{-2em}
\begin{columns}
\begin{column}{0.25\linewidth}
\hspace*{2.0em}
@@ -57,22 +110,47 @@
{\footnotesize \textcolor{fzjgray50}{Spherical impurity potentials in first Voronoi cell of \ce{Hg}:\ce{X}
embeddings,\\left upper to bottom right: \(V\), \(V\!-\!V^0\), \(|V|\), \(|V\!-\!V^0|\).}}
\end{center}
-
- % \includegraphics[width=0.8\linewidth]{../resources/fig/aiida-kkr-ml/da/conv_heatmap_scale-factor_count_linscale.pdf}%
\end{column}
\end{columns}
\end{frame}
-\begin{frame}[plain]
- % \frametitle{Dataset analysis}
- % \framesubtitle{}
- \emph{Single-impurity database} \(\boldsymbol{\vert}\) Charge doping
- \vspace{-1em}
- \begin{center}
- \includegraphics[width=0.88\textwidth]{../resources/fig/aiida-kkr-ml/da/conv_heatmap_charge-neutrality-imp_linscale.pdf}%
- \end{center}
+% Slide Jacobi-Legendre framework
+\begin{frame}[plain,c]
+ \frametitle{The Jacobi-Legendre framework\footcite{dominaJacobiLegendreFrameworkMachine2024}}
+ \framesubtitle{for electronic structure representation}
+ \vspace*{0em}
+ \begin{columns}[c]
+ \begin{column}{0.68\linewidth}
+ \begin{center}
+ % \includegraphics[width=1.0\linewidth]{../resources/fig/external/papers/dominaJacobiLegendreFrameworkMachine2024/processed/fig5.1-with-polynomials.png}%
+
+ \includegraphics[width=0.9\linewidth]{../resources/fig/external/papers/dominaJacobiLegendreFrameworkMachine2024/originals/fig4.1.pdf}%
+ \vspace*{0.0em}
+ \includegraphics[width=0.9\linewidth]{../resources/fig/external/papers/dominaJacobiLegendreFrameworkMachine2024/processed/fig-5.1-first-row-only.png}%
+ \end{center}
+ \end{column}
+ \vrule{} % vertical separator line
+ \hspace*{1em}
+ \begin{column}{0.32\linewidth}
+ \vspace*{0em}
+
+ \includegraphics[width=0.75\linewidth]{../resources/fig/external/papers/dominaJacobiLegendreFrameworkMachine2024/processed/fig6.2-300dpi-narrower-1.png}%
+ \end{column}
+ \end{columns}
+ \vspace*{0em}
\end{frame}
+
+% \begin{frame}[plain]
+% % \frametitle{Dataset analysis}
+% % \framesubtitle{}
+% \emph{Single-impurity database} \(\boldsymbol{\vert}\) Charge doping
+% \vspace{-1em}
+% \begin{center}
+% \includegraphics[width=0.88\textwidth]{../resources/fig/aiida-kkr-ml/da/conv_heatmap_charge-neutrality-imp_linscale.pdf}%
+% \end{center}
+% \end{frame}
+
\begin{frame}[plain]
\frametitle{Atom-based JLCDM}
diff --git a/presentation/mainmatter/kkr-theory.tex b/presentation/mainmatter/kkr-theory.tex
index ecbb168e84db7ff4f4ce58a76b312750af98a00a..cc9b5547aae466903a41934dbdbcbea9dab5aed2 100644
--- a/presentation/mainmatter/kkr-theory.tex
+++ b/presentation/mainmatter/kkr-theory.tex
@@ -16,33 +16,9 @@
% KKR theory slide from mavropoulous dft20 kkr lecture
{
\setbeamercolor{background canvas}{bg=}
- \includepdf[pages={5-8,10-14,18,21-22}]{../resources/fig/external/presentations/rwth-dft20/lecture-20-kkr/Lecture20_KKRGF-Method.pdf}
+ \includepdf[pages={5-8,10-14,18,21-22,24,30}]{../resources/fig/external/presentations/rwth-dft20/lecture-20-kkr/Lecture20_KKRGF-Method.pdf}
}
-% Slide AiiDA-KKR workflows % kkr-theory
-\begin{frame}[plain,c]
- % \frametitle{\logoAiida{}-KKR workflows\footcite{russmannAiiDAKKRPluginIts2021}}
- \frametitle{\logoAiida{}-KKR workflows}
- \vspace*{0em}
- \begin{columns}[t]
- \vspace*{-1em}
- \begin{column}{0.3\linewidth}
- % {\footnotesize Single impurity}
- \begin{center}
- \includegraphics[width=0.95\linewidth]{../resources/fig/presentation-2023-03/ruess/ruess-aiida-kkr-paper-workflow-c.pdf}\footcite{russmannAiiDAKKRPluginIts2021}
- \end{center}
- \end{column}
- \begin{column}{0.5\linewidth}
- \vspace*{-2em}
- \begin{center}
- \includegraphics[width=0.8\textheight]{../resources/fig/aiida-kkr/graph//kkr_imp_wc.pdf}%
- \end{center}
- % \framezoom<1><2>(3.5cm,0.5cm)(4.5cm,3.25cm) % upper part, kkr_scf workflow
- % \framezoom<1><3>(4.5cm,3.5cm)(4.5cm,5.25cm) % lower part, kkr_imp workflow
- \end{column}
-\end{columns}
-\vspace*{-0em}
-\end{frame}
%%% Local Variables:
diff --git a/presentation/presentation.tex b/presentation/presentation.tex
index 21b2805a557e26c7bbd17ec5a802857aa5791a63..249bca6d1f7588b2b764d3fd5d123461a6e34881 100644
--- a/presentation/presentation.tex
+++ b/presentation/presentation.tex
@@ -180,6 +180,7 @@
\input{mainmatter/introduction}
\input{mainmatter/kkr-theory}
\input{mainmatter/kkr-jlcdm}
+\input{mainmatter/jij-prediction}
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% BACKMATTER