aboutsummaryrefslogtreecommitdiff
path: root/opa/chapter.tex
blob: 3d163e235736048f42a3e879cfc4945146596d9f (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
\chapter{A robust, automated strategy to collect high quality OPA tuning curves} \label{cha:opa}

\begin{dquote}
  Principle design features of the new EVV 2DIR optical delivery system include the following:
  \begin{ditemize}
    \item Pairs of motorized gimbal mount mirrors on each OPA to compensate beam pointing changes.
    \item Automated calibration of OPAs, delay stages and motorized mounts.
  \end{ditemize}
      
  \dsignature{Paul Donaldson, ``Improving ... EVV 2DIR Spectroscopy'' (2007)
    \cite{DonaldsonPaulMurray2007a}}  % appears on page 313
\end{dquote}

\clearpage

\section{Introduction}  % =========================================================================

In frequency-domain Multi-Resonant Coherent Multidimensional Spectroscopy (MR-CMDS), automated
Optical Parametric Amplifiers (OPAs) are used to actively scan excitation color axes. [CITE]  %
To accomplish these experiments, exquisite OPA performance is required.  %
During the experiment, motors inside the OPA move to pre-recorded positions to optimize output at
the desired color.  %
Parametric conversion (``mixing'') strategies are now readily avalible, extending the 800 nm pumped
OPA tuning range into the visible, near-infrared, and mid-infrared.  %

OPAs are very sensitive to changes in upstream lasers and lab conditions, so OPA tuning is
regularly required.  %
Manual OPA tuning can easily take a full day. %
Furthermore, manual tuning typically results in inferior tuning curves, since it is difficult for
humans to consider all available information simultaneously.  %
Automated OPA tuning makes OPA upkeep easier, faster and more reproducible, facilitating higher
throughput, higher quality frequency domain experiments. %
The major challenges in automated OPA tuning are:
\begin{enumerate}
  \item Expensive to take high resoltion data.
  \item Need smooth curves for interpolation, especially at edges where output is low.
  \item Optimization metrics are not necessarily separable along motor dimensions.
\end{enumerate}

In this chapter I describe my strategy for automatically collecting high resolution OPA tuning
curves.  %
While I have strategies for all four kinds of OPAs used in the Wright Group, I focus on the
femtosecond TOPAS-C models because they are by far the most challenging model to calibrate.  %

\section{Curves} \label{opa:sec:curves}  % ========================================================

OPA tuning curves are the functional correspondence between desired output color and motor
positions.  %
In theory, these could be recorded as analytical functions derived in an \textit{ab initio} way
from known phase matching and dispersion relations.  %
In practice, ideal tuning curves are determined empirically by simply monitoring OPA output at a
series of given motor combinations.  %
This practice of seeing how OPA output depends on motor positions is called ``tuning'' the OPA.  %

I have defined a Python class \python{Curve} which acts as a interface to OPA tuning curves.  %
Within the class, a series of discrete OPA output colors (``setpoints'') are defined, and the motor
positions are defined for each setpoint.  %
Since it is important that OPAs be settable to \emph{any} position within their output range, a
one-dimensional interpolator is used to determine the correct motor positions for \emph{any} valid
color.  %
There are three kinds of interpolators, linear, spline and polynomial.  %
The particular interpolator used depends on the model of OPA and the complexity of its tuning
curve.  %
The method \python{Curve.get_motor_positions} abstracts away this complexity, simply returning a
list of motor positions for the desired color(s).  %

OPAs often use multiple ``stages'' of interaction to create the desired output.  %
For example, an OPA might generate signal and idler in a first stage, then send that signal on to
be doubled in a second ``second harmonic signal'' (SHS) stage.  %
Depending on the experiment being performed, different stages of the OPA will be used.  %
One could approach this complexity by simply creating an entirely separate curve for each
combination of stages, but this would result in the same information being duplicated in many
different curves.  %
Instead, I have chosen to use a nested approach that directly reflects the approach that the
hardware uses.  %
Curve objects can have ``subcurves'' which define the behavior of the proceeding stage.  %
In the example above, the parent curve would control the second harmonic signal stage.  %
For each SHS position, the parent would define a desired signal color for the first stage to
create.  %
This is passed to the subcurve, which defines the motor positions needed in the first stage to
achieve optimal conversion at the desired \emph{signal} color.  %
In this way, each stage can be tuned separately and the tuning of an upstream stage is immediately
propagated to all downstream stages.  %

% BJT: consider putting an example curve figure

\section{TOPAS-C}  % ==============================================================================

The TOPAS-C is a popular commercially available motorized OPA.  %
It consists of a large initial stage where signal and idler are generated, and a series of optional
mixing stages where further up- or down-conversion can occur to widen the total range of output
frequencies.  %
\autoref{opa:fig:ranges} shows all of the possible output ranges of the TOPAS.  %
It ranges from the mid infrared (accessible through difference frequency generation) to the
ultraviolet (accessible through multiple second harmonic upconversion).  %

% TODO: introduction to the internal design of the OPA

\begin{figure}
  \includegraphics[width=\textwidth]{opa/OPA_ranges}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:ranges}
\end{figure}

\begin{figure}
  \includegraphics[width=\textwidth]{opa/TOPAS-C}
  \caption[TOPAS-C internal optics and beam path.]{
    TOPAS-C internal optics and beam path.  %
    Image taken from manual, originally generated by Light Conversion [CITE].  %
  }
  \label{opa:fig:TOPAS-C}
\end{figure}

\begin{figure}
  \includegraphics[width=\textwidth]{opa/OPA_powers}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:preamp}
\end{figure}

\section{Preamp}  % ===============================================================================

In TOPAS-C OPAs, a small portion of input light is used to generate a signal seed in a BBO crystal
``C1''.  %
A motorized delay stage ``D1'' is used to temporally overlap a particular color in chirped white
light with 800 nm pump.  %
C1 angle is tuned to optimize phase matching.  %
Measured seed intensity and color for all combinations of C1 and D1 position are shown in
\autoref{fig:preamp}.  %

Output color and intensity are not separable along the preamp motor axes.  %
We therefore use a multidimensional fitting strategy to find the best preamp motor positions, as
shown below.  %

% TODO: procedure

A representative preamp tune procedure output image is shown in \autoref{fig:autotune_preamp}.  %
The thick black line is the final output curve.  %
The dark grey lines are the contours of constant color.  %
The colorbar shows the Delaunay-interpolated intensity values for each motor position.  %

Preamp tuning takes less than 20 minutes, in large part due to a NIR array detector which collects
the full spectrum at each motor position.  %

\begin{figure}
  \includegraphics[width=\textwidth]{opa/preamp}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:preamp}
\end{figure}

\begin{figure}
  \includegraphics[width=\linewidth]{opa/preamp_flowchart}
  \caption{
    CAPTION TODO
  }
\end{figure}

\begin{figure}
  \includegraphics[width=\linewidth]{opa/autotune_preamp}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:autotune_preamp}
\end{figure}

\section{Poweramp}  % =============================================================================

Once generated, the seed goes on to be amplified in a second BBO crystal ``C2'' with the rest of
the 800 nm pump.  %
Optimizing this amplification step is primarily a matter of setting C2 angle.  %
A small delay correction ``D2'' is necessary to account for dispersion in the seed optics.  %
To fully explore poweramp behavior, we need to tak a C2-D23 scan for each seed color.  %
Measured output intensity and color in this 3D space is represented in \autoref{fig:poweramp}.  %
Note that the motor axes are scans about the previously recorded tuning curve value.  %

The best position (zero displacement along both axes) is chosen to maximize output intensity while
keeping the output color identical to the seed color.  %
Optimizing for zero detuining rather than simply for output intensity has led to better OPA
performance and stability.  %
Like in the preamp case, color and intensity are not fully separable along the poweramp motor
dimensions (this is especially true at the edge output colors).  %
In the poweramp, the increased dimensionaity makes it too expensive to do a full multidimensional
tuning procedure.  %
Instead we emply an iterative procedure as diagrammed below.  %

% TODO: procedure

We always end the iteration(s) with C2 so that the OPA's color calibration is as good as
possible.  %
Typically only one iteration is required but multiple iterations may be necessary if dramatic OPA
realignment has occurred.  %
In total, poweramp tuning typically takes less than 1 hour. %
Representative procedure output images for D2 (\autoref{op:fig:d2}) and C2 (\autoref{opa:fig:c2})
are shown.  %

For the D2 figure, the lower panel shows the intensity of the data taken.  %
Note the thick grey line, which represents the chosen points before the final spline step.  %
The top panel compares the old tuning curve (thin) with the output tuning curve (thick).  %
For the C2 image, the bottom panel represents the color of each fit mapped onto detuning.  %
Each separate marker color represents a different setpoint.  %
As with D2, the C2 upper panel compares the old tuning curve (thin black) with the output tuning
curve (colored X's).  %

\begin{figure}
  \includegraphics[width=\linewidth]{opa/poweramp}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:poweramp}
\end{figure}

\begin{figure}
  \includegraphics[width=\linewidth]{opa/poweramp_flowchart}
  \caption{
    CAPTION TODO
  }
\end{figure}

\begin{figure}
  \includegraphics[width=\textwidth]{opa/d2}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:d2}
\end{figure}

\begin{figure}
  \includegraphics[width=\textwidth]{opa/c2}
  \caption{
    CAPTION TODO
  }
  \label{opa:fig:c2}
\end{figure}

\section{Mixers}  % ===============================================================================

[DESCRIPTION OF MIXERS]

\section{Generalizability}  % =====================================================================

\begin{figure}
  \includegraphics[width=\textwidth]{"opa/signal_and_idler_motortune"}
  \caption[CAPTION TODO]{
    CAPTION TODO
  }
\end{figure}

\section{Future directions}  % ====================================================================

% TODO: discuss Attune