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\documentclass{presentation}
\title{Development of \\ Frequency-Domain Multidimensional Spectroscopy}
\subtitle{---Beyond Two Dimensions---}
\author{Blaise Thompson}
\institute{University of Wisconsin--Madison}
\date{2018-04-23}
\begin{document}
\maketitle
\begin{frame}{Introduction to CMDS}
\begin{columns}
\begin{column}{0.6\textwidth}
\includegraphics[width=\textwidth]{presentation/SK_PhDThesis_fsTable-Overview}
\end{column}
\begin{column}{0.4\textwidth}
\includegraphics[width=\textwidth]{"literature/BrownEmilyJ1999a_1"}
\centering
\\
\vspace{2\baselineskip}
$\vec{k_{\text{sig}}} = \vec{k_a} - \vec{k_b} + \vec{k_c}$
\vspace{2\baselineskip} \\
\tiny \raggedright
Figure: \\
Brown, E., Zhang, Q. and Dantus, M. (1999). \\
The Journal of Chemical Physics, 110(12), pp.5772-5788.
\end{column}
\end{columns}
\end{frame}
\begin{frame}{Introduction to CMDS}
\adjincludegraphics[width=\textwidth]{"mixed_domain/simulation overview"}
\end{frame}
\begin{frame}{Diversity}
Great diversity of experimental strategies.
\vspace{\baselineskip} \\
Different phase matching conditions...
\begin{itemize}
\item transient grating $\vec{k_a} - \vec{k_b} + \vec{k_c}$
\item transient absorption
\item DOVE
% TODO: darien's experiments
\end{itemize}
But also different color combinations and dimensions explored.
% SAY: based on the same basic ability to scan pulses in frequency, delay etc
\end{frame}
\begin{frame}{Pipeline}
\adjincludegraphics[width=0.5\textwidth]{presentation/pipe}
What does the ``pipeline'' of MR-CMDS data acquisition and processing look like in the Wright
Group?
\vspace{\baselineskip} \\
How to increase data throughput and quality, while decreasing frustration of experimentalists? %
\end{frame}
\begin{frame}{MR-CMDS development}
[SUMMARY SLIDE FOR REMAINDER OF PRESENTATION]
\end{frame}
\section{Tunability} % ===========================================================================
\begin{frame}{Tunability}
\centering \huge
Control and Calibration of \\
Optical Parametric Amplifiers
\end{frame}
\begin{frame}{Two strategies for CMDS}
Two strategies for collecting multidimensional spectra:
\vspace{\baselineskip} \\
\begin{columns}
\begin{column}{0.4\textwidth}
Time Domain
\begin{itemize}
\item broadband pulses
\item resolve spectra interferometrically
\item fast (even single shot)
\item robust
\end{itemize}
\end{column}
\begin{column}{0.4\textwidth}
Frequency Domain
\begin{itemize}
\item narrowband pulses
\item resolve spectra by tuning OPAs directly
\item slow (lots of motor motion)
\item fragile
\end{itemize}
\end{column}
\end{columns}
\end{frame}
\begin{frame}{Two strategies for CMDS}
\begin{columns}
\begin{column}{0.5\textwidth}
Time Domain
\includegraphics[width=\textwidth]{"literature/SinghAkshay2014a_2"}
\tiny
Figure: \\
Singh, A., Moody, G., Wu, S., Wu, Y., Ghimire, N., Yan, J., Mandrus, D., Xu, X. and Li, X.
(2014).
Coherent Electronic Coupling in Atomically Thin MoSe$_2$. Physical Review Letters, 112(21).
\end{column}
\begin{column}{0.5\textwidth}
Frequency Domain
\adjincludegraphics[width=\textwidth]{presentation/singh_czech}
More \hl{bandwidth}.
Crucial for electronic states, band structure.
\end{column}
\end{columns}
\end{frame}
\begin{frame}{Bandwidth}
A lot more bandwidth... through the usage of OPAs
\adjincludegraphics[width=\textwidth]{opa/OPA_ranges}
\end{frame}
\begin{frame}{TOPAS-C}
\includegraphics[width=\textwidth]{opa/TOPAS-C}
Two ``stages'', each with two motorized optics.
\end{frame}
\begin{frame}{Automation}
\begin{columns}
\begin{column}{0.5\textwidth}
\adjincludegraphics[width=\textwidth]{opa/autotune_preamp}
\end{column}
\begin{column}{0.5\textwidth}
Fully automated OPA tuning
\begin{itemize}
\item less than 1 hour per OPA
\item can be scheduled for odd times
\item high quality from global analysis
\item reproducible
\item unambiguous representations automatically generated
\end{itemize}
\vspace{\baselineskip}
Other calibration steps also automated.
\end{column}
\end{columns}
\end{frame}
\section{Acquisition} % ==========================================================================
\begin{frame}{Acquisition}
\centering \huge
Control of the MR-CMDS \\
Instrument
\end{frame}
\begin{frame}{The instrument}
Many kinds of component hardware
\begin{itemize}
\item monochromators
\item delay stages
\item filters
\item OPAs
\end{itemize}
$\sim10$ settable devices, $\sim25$ motors, multiple detectors.
\end{frame}
\begin{frame}{Acquisition}
PyCMDS---unified software for controlling hardware and collecting data.
\adjincludegraphics[width=\textwidth]{acquisition/screenshots/000}
\end{frame}
\begin{frame}{Central loop}
At its core, PyCMDS does something very simple...
\vspace{\baselineskip} \\
Set, wait, read, wait, repeat. % TODO: better figure
\vspace{\baselineskip} \\
Everything is multi-threaded (simultaneous motion, simultaneous read).
\begin{itemize}
\item decrease scan time by up to $\sim2\times$, more for complex experiments
\end{itemize}
\end{frame}
\subsection{Extensibility} % ---------------------------------------------------------------------
\begin{frame}{Extensibility}
\begin{columns}
\begin{column}{0.25\textwidth}
\adjincludegraphics[width=\textwidth]{presentation/hardware}
\end{column}
\begin{column}{0.75\textwidth}
A modular hardware system that can be easily added to
\begin{itemize}
\item When a new OPA was installed on the picosecond system, PyCMDS was back in action the
next day.
\item Darien inherited a new delay stage from the Crim Group, and added it to PyCMDS in
less than two days.
\item New \emph{kinds} of hardware also possible to add, although this is more difficult.
\end{itemize}
just need to copy a script and modify...
% PoyntinTune
\vfill
\end{column}
\end{columns}
\end{frame}
\subsection{Queue} % -----------------------------------------------------------------------------
% TODO: consider cropping, making into one slide
\begin{frame}{Queue}
\adjincludegraphics[width=\textwidth]{acquisition/screenshots/004}
\end{frame}
\begin{frame}{Queue}
This strategy can be incredibly productive!
\begin{itemize}
\item Soon after the queue was first implemented, we collected more pixels in two weeks than
had been collected over the previous three years.
\end{itemize}
\end{frame}
\section{Artifacts} % ============================================================================
\begin{frame}{Acquisition}
\centering \huge
Artifact Rejection
\end{frame}
\begin{frame}{Shots Processing}
[DIGITAL SHOTS PROCESSING---NO MORE BOXCARS]
\end{frame}
\section{Processing} % ===========================================================================
\begin{frame}{Processing}
\centering \huge
Data Processing
\end{frame}
\begin{frame}{Dimensionality}
\begin{columns}
\begin{column}{0.4\textwidth}
\adjincludegraphics[width=\textwidth]{presentation/TOC}
\end{column}
\begin{column}{0.6\textwidth}
TEST
\end{column}
\end{columns}
\end{frame}
\begin{frame}{Flexible data model}
Flexibility to transform into any desired ``projection'' on component variables.
\adjincludegraphics[width=\textwidth]{processing/fringes_transform}
% mention: including expressions
\end{frame}
\begin{frame}{Universal format}
WrightTools defines a \emph{universal file format} for CMDS.
\begin{itemize}
\item store multiple multidimensional arrays
\item metadata
\end{itemize}
Import data from a variety of sources.
\begin{itemize}
\item previous Wright Group acquisition software
\item commercial instruments (JASCO, Shimadzu, Ocean Optics)
\end{itemize}
\end{frame}
\section{Conclusion} % ===========================================================================
\begin{frame}{Conclusion}
[CONCLUSION]
\end{frame}
\begin{frame}{Acknowledgments}
\begin{columns}
\begin{column}{0.5\textwidth}
Wright Group
\begin{itemize}
\item Kyle Sunden
\item Natalia Spitha
\item Darien Morrow
\item Jonathan Handali
\item Nathan Neff-Mallon
\item Kyle Czech
\item Dan Kohler
\item Erin Boyle
\item Paul Hebert
\item Skye Kain
\item John
\item (and more...)
\end{itemize}
\end{column}
\begin{column}{0.5\textwidth}
Committee
\begin{itemize}
\item Kyoung-Shin Choi
\item Randall Goldsmith
\item Tim Bertram
\end{itemize}
\vspace{\baselineskip}
UW-Madison Chemistry Department
\begin{itemize}
\item Rob McClain
\item Pam Doolittle
\item Bill Goebel
\item Steve Myers
\end{itemize}
\vspace{\baselineskip}
You, the audience!
\hl{Questions?}
\end{column}
\end{columns}
\end{frame}
\section{Supplement} % ===========================================================================
\begin{frame}{Tuning}
% TODO: curve plot?
Tuning curves---recorded correspondence between motor positions and output color.
\vspace{\baselineskip} \\
Exquisite sensitivity to alignment and lab conditions---tuning required roughly once a week.
\vspace{\baselineskip} \\
Manual tuning is difficult...
\begin{itemize}
\item high dimensional motor space
\item difficult to asses overall quality
\item several hours of work per OPA (sometimes, an entire day for one OPA)
\end{itemize}
\end{frame}
\begin{frame}{Preamp}
\includegraphics[width=\textwidth]{opa/preamp}
\end{frame}
\begin{frame}{Modular hardware model}
\adjincludegraphics[scale=0.25]{acquisition/hardware_inheritance}
\end{frame}
\begin{frame}{Modular sensor model}
Can have as many sensors as needed.
\vspace{\baselineskip} \\
Each sensor contributes one or more channels.
\vspace{\baselineskip} \\
Sensors with size contribute new variables (dimensions).
\end{frame}
\begin{frame}{Domains of CMDS}
CMDS can be collected in two domains:
\begin{itemize}
\item time domain
\item frequency domain
\end{itemize}
\end{frame}
\begin{frame}{Time domain}
Multiple broadband pulses are scanned in \emph{time} to collect a multidimensional interferogram
(analogous to FTIR, NMR).
\vspace{\baselineskip} \\
A local oscillator must be used to measure the \emph{phase} of the output.
\vspace{\baselineskip} \\
This technique is...
\begin{itemize}
\item fast (even single shot)
\item robust
\end{itemize}
pulse shapers have made time-domain CMDS (2DIR) almost routine.
\end{frame}
\begin{frame}{Frequency domain}
In the Wright Group, we focus on \emph{frequency} domain ``Multi-Resonant'' (MR)-CMDS.
\vspace{\baselineskip} \\
Automated Optical Parametric Amplifiers (OPAs) are used to produce relatively narrow-band pulses.
Multidimensional spectra are collected ``directly'' by scanning OPAs against each-other.
\vspace{\baselineskip} \\
This strategy is...
\begin{itemize}
\item slow (must directly visit each pixel)
\item fragile (many crucial moving pieces)
\end{itemize}
but! It is incredibly flexible.
\end{frame}
\begin{frame}{Selection rules}
MR-CMDS can easily collect data without an external local oscillator.
\vspace{\baselineskip} \\
This means... [BOYLE]
\end{frame}
\begin{frame}{MR-CMDS theory}
\end{frame}
\begin{frame}{Mixed domain}
[FIGURES FROM DAN'S PAPER]
\end{frame}
\end{document}
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